A unified framework for image retrieval using keyword and visual features.
Jing, Feng; Li, Mingling; Zhang, Hong-Jiang; Zhang, Bo
2005-07-01
In this paper, a unified image retrieval framework based on both keyword annotations and visual features is proposed. In this framework, a set of statistical models are built based on visual features of a small set of manually labeled images to represent semantic concepts and used to propagate keywords to other unlabeled images. These models are updated periodically when more images implicitly labeled by users become available through relevance feedback. In this sense, the keyword models serve the function of accumulation and memorization of knowledge learned from user-provided relevance feedback. Furthermore, two sets of effective and efficient similarity measures and relevance feedback schemes are proposed for query by keyword scenario and query by image example scenario, respectively. Keyword models are combined with visual features in these schemes. In particular, a new, entropy-based active learning strategy is introduced to improve the efficiency of relevance feedback for query by keyword. Furthermore, a new algorithm is proposed to estimate the keyword features of the search concept for query by image example. It is shown to be more appropriate than two existing relevance feedback algorithms. Experimental results demonstrate the effectiveness of the proposed framework.
A unified data representation theory for network visualization, ordering and coarse-graining
Kovács, István A.; Mizsei, Réka; Csermely, Péter
2015-01-01
Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form. PMID:26348923
Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A.
2016-01-01
Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving “live partial-area taxonomies” is demonstrated. PMID:27345947
Ochs, Christopher; Geller, James; Perl, Yehoshua; Musen, Mark A
2016-08-01
Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated. Copyright © 2016 Elsevier Inc. All rights reserved.
2017-05-25
Operations, and Unified Land Operations) and the US Army’s leader development model identifies how the education , training, and experience of field-grade...officers have failed in their incorporation of the framework because they lack the education , training, and experience for the use of the framework... education , training, and experience of field-grade officers at the division level have influenced their use of the operational framework. The cause for
A unified account of perceptual layering and surface appearance in terms of gamut relativity.
Vladusich, Tony; McDonnell, Mark D
2014-01-01
When we look at the world--or a graphical depiction of the world--we perceive surface materials (e.g. a ceramic black and white checkerboard) independently of variations in illumination (e.g. shading or shadow) and atmospheric media (e.g. clouds or smoke). Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye. One way to understand how these percepts arise is to assume that the visual system parses patterns of light into layered perceptual representations of surfaces, illumination and atmospheric media, one seen through another. Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking. Here we present the first general computational model of perceptual layering and surface appearance--based on a boarder theoretical framework called gamut relativity--that is consistent with these demonstrations. The model (a) qualitatively explains striking effects of perceptual transparency, figure-ground separation and lightness, (b) quantitatively accounts for the role of stimulus- and task-driven constraints on perceptual matching performance, and (c) unifies two prominent theoretical frameworks for understanding surface appearance. The model thereby provides novel insights into the remarkable capacity of the human visual system to represent and identify surface materials, illumination and atmospheric media, which can be exploited in computer graphics applications.
A Unified Account of Perceptual Layering and Surface Appearance in Terms of Gamut Relativity
Vladusich, Tony; McDonnell, Mark D.
2014-01-01
When we look at the world—or a graphical depiction of the world—we perceive surface materials (e.g. a ceramic black and white checkerboard) independently of variations in illumination (e.g. shading or shadow) and atmospheric media (e.g. clouds or smoke). Such percepts are partly based on the way physical surfaces and media reflect and transmit light and partly on the way the human visual system processes the complex patterns of light reaching the eye. One way to understand how these percepts arise is to assume that the visual system parses patterns of light into layered perceptual representations of surfaces, illumination and atmospheric media, one seen through another. Despite a great deal of previous experimental and modelling work on layered representation, however, a unified computational model of key perceptual demonstrations is still lacking. Here we present the first general computational model of perceptual layering and surface appearance—based on a boarder theoretical framework called gamut relativity—that is consistent with these demonstrations. The model (a) qualitatively explains striking effects of perceptual transparency, figure-ground separation and lightness, (b) quantitatively accounts for the role of stimulus- and task-driven constraints on perceptual matching performance, and (c) unifies two prominent theoretical frameworks for understanding surface appearance. The model thereby provides novel insights into the remarkable capacity of the human visual system to represent and identify surface materials, illumination and atmospheric media, which can be exploited in computer graphics applications. PMID:25402466
Scalable large format 3D displays
NASA Astrophysics Data System (ADS)
Chang, Nelson L.; Damera-Venkata, Niranjan
2010-02-01
We present a general framework for the modeling and optimization of scalable large format 3-D displays using multiple projectors. Based on this framework, we derive algorithms that can robustly optimize the visual quality of an arbitrary combination of projectors (e.g. tiled, superimposed, combinations of the two) without manual adjustment. The framework creates for the first time a new unified paradigm that is agnostic to a particular configuration of projectors yet robustly optimizes for the brightness, contrast, and resolution of that configuration. In addition, we demonstrate that our algorithms support high resolution stereoscopic video at real-time interactive frame rates achieved on commodity graphics hardware. Through complementary polarization, the framework creates high quality multi-projector 3-D displays at low hardware and operational cost for a variety of applications including digital cinema, visualization, and command-and-control walls.
Franz, A; Triesch, J
2010-12-01
The perception of the unity of objects, their permanence when out of sight, and the ability to perceive continuous object trajectories even during occlusion belong to the first and most important capacities that infants have to acquire. Despite much research a unified model of the development of these abilities is still missing. Here we make an attempt to provide such a unified model. We present a recurrent artificial neural network that learns to predict the motion of stimuli occluding each other and that develops representations of occluded object parts. It represents completely occluded, moving objects for several time steps and successfully predicts their reappearance after occlusion. This framework allows us to account for a broad range of experimental data. Specifically, the model explains how the perception of object unity develops, the role of the width of the occluders, and it also accounts for differences between data for moving and stationary stimuli. We demonstrate that these abilities can be acquired by learning to predict the sensory input. The model makes specific predictions and provides a unifying framework that has the potential to be extended to other visual event categories. Copyright © 2010 Elsevier Inc. All rights reserved.
Montijn, Jorrit Steven; Klink, P Christaan; van Wezel, Richard J A
2012-01-01
Divisive normalization models of covert attention commonly use spike rate modulations as indicators of the effect of top-down attention. In addition, an increasing number of studies have shown that top-down attention increases the synchronization of neuronal oscillations as well, particularly in gamma-band frequencies (25-100 Hz). Although modulations of spike rate and synchronous oscillations are not mutually exclusive as mechanisms of attention, there has thus far been little effort to integrate these concepts into a single framework of attention. Here, we aim to provide such a unified framework by expanding the normalization model of attention with a multi-level hierarchical structure and a time dimension; allowing the simulation of a recently reported backward progression of attentional effects along the visual cortical hierarchy. A simple cascade of normalization models simulating different cortical areas is shown to cause signal degradation and a loss of stimulus discriminability over time. To negate this degradation and ensure stable neuronal stimulus representations, we incorporate a kind of oscillatory phase entrainment into our model that has previously been proposed as the "communication-through-coherence" (CTC) hypothesis. Our analysis shows that divisive normalization and oscillation models can complement each other in a unified account of the neural mechanisms of selective visual attention. The resulting hierarchical normalization and oscillation (HNO) model reproduces several additional spatial and temporal aspects of attentional modulation and predicts a latency effect on neuronal responses as a result of cued attention.
Montijn, Jorrit Steven; Klink, P. Christaan; van Wezel, Richard J. A.
2012-01-01
Divisive normalization models of covert attention commonly use spike rate modulations as indicators of the effect of top-down attention. In addition, an increasing number of studies have shown that top-down attention increases the synchronization of neuronal oscillations as well, particularly in gamma-band frequencies (25–100 Hz). Although modulations of spike rate and synchronous oscillations are not mutually exclusive as mechanisms of attention, there has thus far been little effort to integrate these concepts into a single framework of attention. Here, we aim to provide such a unified framework by expanding the normalization model of attention with a multi-level hierarchical structure and a time dimension; allowing the simulation of a recently reported backward progression of attentional effects along the visual cortical hierarchy. A simple cascade of normalization models simulating different cortical areas is shown to cause signal degradation and a loss of stimulus discriminability over time. To negate this degradation and ensure stable neuronal stimulus representations, we incorporate a kind of oscillatory phase entrainment into our model that has previously been proposed as the “communication-through-coherence” (CTC) hypothesis. Our analysis shows that divisive normalization and oscillation models can complement each other in a unified account of the neural mechanisms of selective visual attention. The resulting hierarchical normalization and oscillation (HNO) model reproduces several additional spatial and temporal aspects of attentional modulation and predicts a latency effect on neuronal responses as a result of cued attention. PMID:22586372
ViSA: A Neurodynamic Model for Visuo-Spatial Working Memory, Attentional Blink, and Conscious Access
ERIC Educational Resources Information Center
Simione, Luca; Raffone, Antonino; Wolters, Gezinus; Salmas, Paola; Nakatani, Chie; Belardinelli, Marta Olivetti; van Leeuwen, Cees
2012-01-01
Two separate lines of study have clarified the role of selectivity in conscious access to visual information. Both involve presenting multiple targets and distracters: one "simultaneously" in a spatially distributed fashion, the other "sequentially" at a single location. To understand their findings in a unified framework, we propose a…
A Graph-Embedding Approach to Hierarchical Visual Word Mergence.
Wang, Lei; Liu, Lingqiao; Zhou, Luping
2017-02-01
Appropriately merging visual words are an effective dimension reduction method for the bag-of-visual-words model in image classification. The approach of hierarchically merging visual words has been extensively employed, because it gives a fully determined merging hierarchy. Existing supervised hierarchical merging methods take different approaches and realize the merging process with various formulations. In this paper, we propose a unified hierarchical merging approach built upon the graph-embedding framework. Our approach is able to merge visual words for any scenario, where a preferred structure and an undesired structure are defined, and, therefore, can effectively attend to all kinds of requirements for the word-merging process. In terms of computational efficiency, we show that our algorithm can seamlessly integrate a fast search strategy developed in our previous work and, thus, well maintain the state-of-the-art merging speed. To the best of our survey, the proposed approach is the first one that addresses the hierarchical visual word mergence in such a flexible and unified manner. As demonstrated, it can maintain excellent image classification performance even after a significant dimension reduction, and outperform all the existing comparable visual word-merging methods. In a broad sense, our work provides an open platform for applying, evaluating, and developing new criteria for hierarchical word-merging tasks.
Benefits of a Unified LaSRS++ Simulation for NAS-Wide and High-Fidelity Modeling
NASA Technical Reports Server (NTRS)
Glaab, Patricia; Madden, Michael
2014-01-01
The LaSRS++ high-fidelity vehicle simulation was extended in 2012 to support a NAS-wide simulation mode. Since the initial proof-of-concept, the LaSRS++ NAS-wide simulation is maturing into a research-ready tool. A primary benefit of this new capability is the consolidation of the two modeling paradigms under a single framework to save cost, facilitate iterative concept testing between the two tools, and to promote communication and model sharing between user communities at Langley. Specific benefits of each type of modeling are discussed along with the expected benefits of the unified framework. Current capability details of the LaSRS++ NAS-wide simulations are provided, including the visualization tool, live data interface, trajectory generators, terminal routing for arrivals and departures, maneuvering, re-routing, navigation, winds, and turbulence. The plan for future development is also described.
Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa
2017-01-01
The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.
Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko
2016-06-01
Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.
A State Space Model for Spatial Updating of Remembered Visual Targets during Eye Movements
Mohsenzadeh, Yalda; Dash, Suryadeep; Crawford, J. Douglas
2016-01-01
In the oculomotor system, spatial updating is the ability to aim a saccade toward a remembered visual target position despite intervening eye movements. Although this has been the subject of extensive experimental investigation, there is still no unifying theoretical framework to explain the neural mechanism for this phenomenon, and how it influences visual signals in the brain. Here, we propose a unified state-space model (SSM) to account for the dynamics of spatial updating during two types of eye movement; saccades and smooth pursuit. Our proposed model is a non-linear SSM and implemented through a recurrent radial-basis-function neural network in a dual Extended Kalman filter (EKF) structure. The model parameters and internal states (remembered target position) are estimated sequentially using the EKF method. The proposed model replicates two fundamental experimental observations: continuous gaze-centered updating of visual memory-related activity during smooth pursuit, and predictive remapping of visual memory activity before and during saccades. Moreover, our model makes the new prediction that, when uncertainty of input signals is incorporated in the model, neural population activity and receptive fields expand just before and during saccades. These results suggest that visual remapping and motor updating are part of a common visuomotor mechanism, and that subjective perceptual constancy arises in part from training the visual system on motor tasks. PMID:27242452
Toward Model Building for Visual Aesthetic Perception
Lughofer, Edwin; Zeng, Xianyi
2017-01-01
Several models of visual aesthetic perception have been proposed in recent years. Such models have drawn on investigations into the neural underpinnings of visual aesthetics, utilizing neurophysiological techniques and brain imaging techniques including functional magnetic resonance imaging, magnetoencephalography, and electroencephalography. The neural mechanisms underlying the aesthetic perception of the visual arts have been explained from the perspectives of neuropsychology, brain and cognitive science, informatics, and statistics. Although corresponding models have been constructed, the majority of these models contain elements that are difficult to be simulated or quantified using simple mathematical functions. In this review, we discuss the hypotheses, conceptions, and structures of six typical models for human aesthetic appreciation in the visual domain: the neuropsychological, information processing, mirror, quartet, and two hierarchical feed-forward layered models. Additionally, the neural foundation of aesthetic perception, appreciation, or judgement for each model is summarized. The development of a unified framework for the neurobiological mechanisms underlying the aesthetic perception of visual art and the validation of this framework via mathematical simulation is an interesting challenge in neuroaesthetics research. This review aims to provide information regarding the most promising proposals for bridging the gap between visual information processing and brain activity involved in aesthetic appreciation. PMID:29270194
14 CFR 1221.108 - Establishment of the NASA Unified Visual Communications System.
Code of Federal Regulations, 2012 CFR
2012-01-01
... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Establishment of the NASA Unified Visual... ADMINISTRATION THE NASA SEAL AND OTHER DEVICES, AND THE CONGRESSIONAL SPACE MEDAL OF HONOR NASA Seal, NASA Insignia, NASA Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual...
14 CFR § 1221.108 - Establishment of the NASA Unified Visual Communications System.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Establishment of the NASA Unified Visual... ADMINISTRATION THE NASA SEAL AND OTHER DEVICES, AND THE CONGRESSIONAL SPACE MEDAL OF HONOR NASA Seal, NASA Insignia, NASA Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual...
14 CFR 1221.108 - Establishment of the NASA Unified Visual Communications System.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Establishment of the NASA Unified Visual... ADMINISTRATION THE NASA SEAL AND OTHER DEVICES, AND THE CONGRESSIONAL SPACE MEDAL OF HONOR NASA Seal, NASA Insignia, NASA Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual...
Lappi, Otto; Mole, Callum
2018-06-11
The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engineering, which share an underlying architecture but have historically developed in very separate ways. The authors then show how these traditions can be naturally (re)integrated with each other and with contemporary neuroscience, to better understand the skill and gaze strategies involved. They then propose a conceptual model that (a) gives a unified account to the coordination of gaze and steering control, (b) incorporates higher-level path planning, and (c) draws on the literature on paired forward and inverse models in predictive control. Although each of these (a-c) has been considered before (also in the context of driving), integrating them into a single framework and the authors' multiple waypoint identification hypothesis within that framework are novel. The proposed hypothesis is relevant to all forms of visually guided locomotion. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Chen, Zhenzhong; Han, Junwei; Ngan, King Ngi
2005-10-01
MPEG-4 treats a scene as a composition of several objects or so-called video object planes (VOPs) that are separately encoded and decoded. Such a flexible video coding framework makes it possible to code different video object with different distortion scale. It is necessary to analyze the priority of the video objects according to its semantic importance, intrinsic properties and psycho-visual characteristics such that the bit budget can be distributed properly to video objects to improve the perceptual quality of the compressed video. This paper aims to provide an automatic video object priority definition method based on object-level visual attention model and further propose an optimization framework for video object bit allocation. One significant contribution of this work is that the human visual system characteristics are incorporated into the video coding optimization process. Another advantage is that the priority of the video object can be obtained automatically instead of fixing weighting factors before encoding or relying on the user interactivity. To evaluate the performance of the proposed approach, we compare it with traditional verification model bit allocation and the optimal multiple video object bit allocation algorithms. Comparing with traditional bit allocation algorithms, the objective quality of the object with higher priority is significantly improved under this framework. These results demonstrate the usefulness of this unsupervised subjective quality lifting framework.
An information model for managing multi-dimensional gridded data in a GIS
NASA Astrophysics Data System (ADS)
Xu, H.; Abdul-Kadar, F.; Gao, P.
2016-04-01
Earth observation agencies like NASA and NOAA produce huge volumes of historical, near real-time, and forecasting data representing terrestrial, atmospheric, and oceanic phenomena. The data drives climatological and meteorological studies, and underpins operations ranging from weather pattern prediction and forest fire monitoring to global vegetation analysis. These gridded data sets are distributed mostly as files in HDF, GRIB, or netCDF format and quantify variables like precipitation, soil moisture, or sea surface temperature, along one or more dimensions like time and depth. Although the data cube is a well-studied model for storing and analyzing multi-dimensional data, the GIS community remains in need of a solution that simplifies interactions with the data, and elegantly fits with existing database schemas and dissemination protocols. This paper presents an information model that enables Geographic Information Systems (GIS) to efficiently catalog very large heterogeneous collections of geospatially-referenced multi-dimensional rasters—towards providing unified access to the resulting multivariate hypercubes. We show how the implementation of the model encapsulates format-specific variations and provides unified access to data along any dimension. We discuss how this framework lends itself to familiar GIS concepts like image mosaics, vector field visualization, layer animation, distributed data access via web services, and scientific computing. Global data sources like MODIS from USGS and HYCOM from NOAA illustrate how one would employ this framework for cataloging, querying, and intuitively visualizing such hypercubes. ArcGIS—an established platform for processing, analyzing, and visualizing geospatial data—serves to demonstrate how this integration brings the full power of GIS to the scientific community.
Townsend, James T; Eidels, Ami
2011-08-01
Increasing the number of available sources of information may impair or facilitate performance, depending on the capacity of the processing system. Tests performed on response time distributions are proving to be useful tools in determining the workload capacity (as well as other properties) of cognitive systems. In this article, we develop a framework and relevant mathematical formulae that represent different capacity assays (Miller's race model bound, Grice's bound, and Townsend's capacity coefficient) in the same space. The new space allows a direct comparison between the distinct bounds and the capacity coefficient values and helps explicate the relationships among the different measures. An analogous common space is proposed for the AND paradigm, relating the capacity index to the Colonius-Vorberg bounds. We illustrate the effectiveness of the unified spaces by presenting data from two simulated models (standard parallel, coactive) and a prototypical visual detection experiment. A conversion table for the unified spaces is provided.
Code of Federal Regulations, 2010 CFR
2010-01-01
..., and the Agency's Unified Visual Communications System § 1221.100 Scope. This subpart sets forth the... Unified Visual Communications System and prescribes the policy and guidelines for implementation of the...
The visual system’s internal model of the world
Lee, Tai Sing
2015-01-01
The Bayesian paradigm has provided a useful conceptual theory for understanding perceptual computation in the brain. While the detailed neural mechanisms of Bayesian inference are not fully understood, recent computational and neurophysiological works have illuminated the underlying computational principles and representational architecture. The fundamental insights are that the visual system is organized as a modular hierarchy to encode an internal model of the world, and that perception is realized by statistical inference based on such internal model. In this paper, I will discuss and analyze the varieties of representational schemes of these internal models and how they might be used to perform learning and inference. I will argue for a unified theoretical framework for relating the internal models to the observed neural phenomena and mechanisms in the visual cortex. PMID:26566294
A Unified Air-Sea Visualization System: Survey on Gridding Structures
NASA Technical Reports Server (NTRS)
Anand, Harsh; Moorhead, Robert
1995-01-01
The goal is to develop a Unified Air-Sea Visualization System (UASVS) to enable the rapid fusion of observational, archival, and model data for verification and analysis. To design and develop UASVS, modelers were polled to determine the gridding structures and visualization systems used, and their needs with respect to visual analysis. A basic UASVS requirement is to allow a modeler to explore multiple data sets within a single environment, or to interpolate multiple datasets onto one unified grid. From this survey, the UASVS should be able to visualize 3D scalar/vector fields; render isosurfaces; visualize arbitrary slices of the 3D data; visualize data defined on spectral element grids with the minimum number of interpolation stages; render contours; produce 3D vector plots and streamlines; provide unified visualization of satellite images, observations and model output overlays; display the visualization on a projection of the users choice; implement functions so the user can derive diagnostic values; animate the data to see the time-evolution; animate ocean and atmosphere at different rates; store the record of cursor movement, smooth the path, and animate a window around the moving path; repeatedly start and stop the visual time-stepping; generate VHS tape animations; work on a variety of workstations; and allow visualization across clusters of workstations and scalable high performance computer systems.
Stochastic correlative firing for figure-ground segregation.
Chen, Zhe
2005-03-01
Segregation of sensory inputs into separate objects is a central aspect of perception and arises in all sensory modalities. The figure-ground segregation problem requires identifying an object of interest in a complex scene, in many cases given binaural auditory or binocular visual observations. The computations required for visual and auditory figure-ground segregation share many common features and can be cast within a unified framework. Sensory perception can be viewed as a problem of optimizing information transmission. Here we suggest a stochastic correlative firing mechanism and an associative learning rule for figure-ground segregation in several classic sensory perception tasks, including the cocktail party problem in binaural hearing, binocular fusion of stereo images, and Gestalt grouping in motion perception.
Unifying Terrain Awareness for the Visually Impaired through Real-Time Semantic Segmentation
Yang, Kailun; Wang, Kaiwei; Romera, Eduardo; Hu, Weijian; Sun, Dongming; Sun, Junwei; Cheng, Ruiqi; Chen, Tianxue; López, Elena
2018-01-01
Navigational assistance aims to help visually-impaired people to ambulate the environment safely and independently. This topic becomes challenging as it requires detecting a wide variety of scenes to provide higher level assistive awareness. Vision-based technologies with monocular detectors or depth sensors have sprung up within several years of research. These separate approaches have achieved remarkable results with relatively low processing time and have improved the mobility of impaired people to a large extent. However, running all detectors jointly increases the latency and burdens the computational resources. In this paper, we put forward seizing pixel-wise semantic segmentation to cover navigation-related perception needs in a unified way. This is critical not only for the terrain awareness regarding traversable areas, sidewalks, stairs and water hazards, but also for the avoidance of short-range obstacles, fast-approaching pedestrians and vehicles. The core of our unification proposal is a deep architecture, aimed at attaining efficient semantic understanding. We have integrated the approach in a wearable navigation system by incorporating robust depth segmentation. A comprehensive set of experiments prove the qualified accuracy over state-of-the-art methods while maintaining real-time speed. We also present a closed-loop field test involving real visually-impaired users, demonstrating the effectivity and versatility of the assistive framework. PMID:29748508
Biasing spatial attention with semantic information: an event coding approach.
Amer, Tarek; Gozli, Davood G; Pratt, Jay
2017-04-21
We investigated the influence of conceptual processing on visual attention from the standpoint of Theory of Event Coding (TEC). The theory makes two predictions: first, an important factor in determining the influence of event 1 on processing event 2 is whether features of event 1 are bound into a unified representation (i.e., selection or retrieval of event 1). Second, whether processing the two events facilitates or interferes with each other should depend on the extent to which their constituent features overlap. In two experiments, participants performed a visual-attention cueing task, in which the visual target (event 2) was preceded by a relevant or irrelevant explicit (e.g., "UP") or implicit (e.g., "HAPPY") spatial-conceptual cue (event 1). Consistent with TEC, we found relevant explicit cues (which featurally overlap to a greater extent with the target) and implicit cues (which featurally overlap to a lesser extent), respectively, facilitated and interfered with target processing at compatible locations. Irrelevant explicit and implicit cues, on the other hand, both facilitated target processing, presumably because they were less likely selected or retrieved as an integrated and unified event file. We argue that such effects, often described as "attentional cueing", are better accounted for within the event coding framework.
Toward a Unified Theory of Visual Area V4
Roe, Anna W.; Chelazzi, Leonardo; Connor, Charles E.; Conway, Bevil R.; Fujita, Ichiro; Gallant, Jack L.; Lu, Haidong; Vanduffel, Wim
2016-01-01
Visual area V4 is a midtier cortical area in the ventral visual pathway. It is crucial for visual object recognition and has been a focus of many studies on visual attention. However, there is no unifying view of V4’s role in visual processing. Neither is there an understanding of how its role in feature processing interfaces with its role in visual attention. This review captures our current knowledge of V4, largely derived from electrophysiological and imaging studies in the macaque monkey. Based on recent discovery of functionally specific domains in V4, we propose that the unifying function of V4 circuitry is to enable selective extraction of specific functional domain-based networks, whether it be by bottom-up specification of object features or by top-down attentionally driven selection. PMID:22500626
ERIC Educational Resources Information Center
Hong, Sunggye; Rosenblum, L. Penny; Campbell, Amy Frank
2017-01-01
Introduction: This study analyzed survey responses from 141 teachers of students with visual impairments who shared their experiences about the implementation of Unified English Braille (UEB). Methods: Teachers of students with visual impairments in the United States completed an online survey during spring 2016. Results: Although most respondents…
Unsupervised Deep Hashing With Pseudo Labels for Scalable Image Retrieval.
Zhang, Haofeng; Liu, Li; Long, Yang; Shao, Ling
2018-04-01
In order to achieve efficient similarity searching, hash functions are designed to encode images into low-dimensional binary codes with the constraint that similar features will have a short distance in the projected Hamming space. Recently, deep learning-based methods have become more popular, and outperform traditional non-deep methods. However, without label information, most state-of-the-art unsupervised deep hashing (DH) algorithms suffer from severe performance degradation for unsupervised scenarios. One of the main reasons is that the ad-hoc encoding process cannot properly capture the visual feature distribution. In this paper, we propose a novel unsupervised framework that has two main contributions: 1) we convert the unsupervised DH model into supervised by discovering pseudo labels; 2) the framework unifies likelihood maximization, mutual information maximization, and quantization error minimization so that the pseudo labels can maximumly preserve the distribution of visual features. Extensive experiments on three popular data sets demonstrate the advantages of the proposed method, which leads to significant performance improvement over the state-of-the-art unsupervised hashing algorithms.
A stochastically fully connected conditional random field framework for super resolution OCT
NASA Astrophysics Data System (ADS)
Boroomand, A.; Tan, B.; Wong, A.; Bizheva, K.
2017-02-01
A number of factors can degrade the resolution and contrast of OCT images, such as: (1) changes of the OCT pointspread function (PSF) resulting from wavelength dependent scattering and absorption of light along the imaging depth (2) speckle noise, as well as (3) motion artifacts. We propose a new Super Resolution OCT (SR OCT) imaging framework that takes advantage of a Stochastically Fully Connected Conditional Random Field (SF-CRF) model to generate a Super Resolved OCT (SR OCT) image of higher quality from a set of Low-Resolution OCT (LR OCT) images. The proposed SF-CRF SR OCT imaging is able to simultaneously compensate for all of the factors mentioned above, that degrade the OCT image quality, using a unified computational framework. The proposed SF-CRF SR OCT imaging framework was tested on a set of simulated LR human retinal OCT images generated from a high resolution, high contrast retinal image, and on a set of in-vivo, high resolution, high contrast rat retinal OCT images. The reconstructed SR OCT images show considerably higher spatial resolution, less speckle noise and higher contrast compared to other tested methods. Visual assessment of the results demonstrated the usefulness of the proposed approach in better preservation of fine details and structures of the imaged sample, retaining biological tissue boundaries while reducing speckle noise using a unified computational framework. Quantitative evaluation using both Contrast to Noise Ratio (CNR) and Edge Preservation (EP) parameter also showed superior performance of the proposed SF-CRF SR OCT approach compared to other image processing approaches.
EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.
Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D
2012-01-01
Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.
Phase noise suppression for coherent optical block transmission systems: a unified framework.
Yang, Chuanchuan; Yang, Feng; Wang, Ziyu
2011-08-29
A unified framework for phase noise suppression is proposed in this paper, which could be applied in any coherent optical block transmission systems, including coherent optical orthogonal frequency-division multiplexing (CO-OFDM), coherent optical single-carrier frequency-domain equalization block transmission (CO-SCFDE), etc. Based on adaptive modeling of phase noise, unified observation equations for different coherent optical block transmission systems are constructed, which lead to unified phase noise estimation and suppression. Numerical results demonstrate that the proposal is powerful in mitigating laser phase noise.
Toward statistical modeling of saccadic eye-movement and visual saliency.
Sun, Xiaoshuai; Yao, Hongxun; Ji, Rongrong; Liu, Xian-Ming
2014-11-01
In this paper, we present a unified statistical framework for modeling both saccadic eye movements and visual saliency. By analyzing the statistical properties of human eye fixations on natural images, we found that human attention is sparsely distributed and usually deployed to locations with abundant structural information. This observations inspired us to model saccadic behavior and visual saliency based on super-Gaussian component (SGC) analysis. Our model sequentially obtains SGC using projection pursuit, and generates eye movements by selecting the location with maximum SGC response. Besides human saccadic behavior simulation, we also demonstrated our superior effectiveness and robustness over state-of-the-arts by carrying out dense experiments on synthetic patterns and human eye fixation benchmarks. Multiple key issues in saliency modeling research, such as individual differences, the effects of scale and blur, are explored in this paper. Based on extensive qualitative and quantitative experimental results, we show promising potentials of statistical approaches for human behavior research.
Code of Federal Regulations, 2010 CFR
2010-01-01
..., and the Agency's Unified Visual Communications System § 1221.101 Policy. (a) The NASA Seal, the NASA Insignia, NASA Logotype, NASA Program Identifiers, the NASA Flags, and the Agency's Unified Visual Communications System, as prescribed in § 1221.102 through § 1221.108 of this subpart, shall be used exclusively...
A Unified Framework for Analyzing and Designing for Stationary Arterial Networks
DOT National Transportation Integrated Search
2017-05-17
This research aims to develop a unified theoretical and simulation framework for analyzing and designing signals for stationary arterial networks. Existing traffic flow models used in design and analysis of signal control strategies are either too si...
A unified framework for physical print quality
NASA Astrophysics Data System (ADS)
Eid, Ahmed; Cooper, Brian; Rippetoe, Ed
2007-01-01
In this paper we present a unified framework for physical print quality. This framework includes a design for a testbed, testing methodologies and quality measures of physical print characteristics. An automatic belt-fed flatbed scanning system is calibrated to acquire L* data for a wide range of flat field imagery. Testing methodologies based on wavelet pre-processing and spectral/statistical analysis are designed. We apply the proposed framework to three common printing artifacts: banding, jitter, and streaking. Since these artifacts are directional, wavelet based approaches are used to extract one artifact at a time and filter out other artifacts. Banding is characterized as a medium-to-low frequency, vertical periodic variation down the page. The same definition is applied to the jitter artifact, except that the jitter signal is characterized as a high-frequency signal above the banding frequency range. However, streaking is characterized as a horizontal aperiodic variation in the high-to-medium frequency range. Wavelets at different levels are applied to the input images in different directions to extract each artifact within specified frequency bands. Following wavelet reconstruction, images are converted into 1-D signals describing the artifact under concern. Accurate spectral analysis using a DFT with Blackman-Harris windowing technique is used to extract the power (strength) of periodic signals (banding and jitter). Since streaking is an aperiodic signal, a statistical measure is used to quantify the streaking strength. Experiments on 100 print samples scanned at 600 dpi from 10 different printers show high correlation (75% to 88%) between the ranking of these samples by the proposed metrologies and experts' visual ranking.
Control of Distributed Parameter Systems
1990-08-01
vari- ant of the general Lotka - Volterra model for interspecific competition. The variant described the emergence of one subpopulation from another as a...distribut ion unlimited. I&. ARSTRACT (MAUMUnw2O1 A unified arioroximation framework for Parameter estimation In general linear POE models has been completed...unified approximation framework for parameter estimation in general linear PDE models. This framework has provided the theoretical basis for a number of
Quantum Computing Architectural Design
NASA Astrophysics Data System (ADS)
West, Jacob; Simms, Geoffrey; Gyure, Mark
2006-03-01
Large scale quantum computers will invariably require scalable architectures in addition to high fidelity gate operations. Quantum computing architectural design (QCAD) addresses the problems of actually implementing fault-tolerant algorithms given physical and architectural constraints beyond those of basic gate-level fidelity. Here we introduce a unified framework for QCAD that enables the scientist to study the impact of varying error correction schemes, architectural parameters including layout and scheduling, and physical operations native to a given architecture. Our software package, aptly named QCAD, provides compilation, manipulation/transformation, multi-paradigm simulation, and visualization tools. We demonstrate various features of the QCAD software package through several examples.
Panoptes: web-based exploration of large scale genome variation data.
Vauterin, Paul; Jeffery, Ben; Miles, Alistair; Amato, Roberto; Hart, Lee; Wright, Ian; Kwiatkowski, Dominic
2017-10-15
The size and complexity of modern large-scale genome variation studies demand novel approaches for exploring and sharing the data. In order to unlock the potential of these data for a broad audience of scientists with various areas of expertise, a unified exploration framework is required that is accessible, coherent and user-friendly. Panoptes is an open-source software framework for collaborative visual exploration of large-scale genome variation data and associated metadata in a web browser. It relies on technology choices that allow it to operate in near real-time on very large datasets. It can be used to browse rich, hybrid content in a coherent way, and offers interactive visual analytics approaches to assist the exploration. We illustrate its application using genome variation data of Anopheles gambiae, Plasmodium falciparum and Plasmodium vivax. Freely available at https://github.com/cggh/panoptes, under the GNU Affero General Public License. paul.vauterin@gmail.com. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Rating knowledge sharing in cross-domain collaborative filtering.
Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi
2015-05-01
Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.
NASA Astrophysics Data System (ADS)
Maechling, P. J.; Taborda, R.; Callaghan, S.; Shaw, J. H.; Plesch, A.; Olsen, K. B.; Jordan, T. H.; Goulet, C. A.
2017-12-01
Crustal seismic velocity models and datasets play a key role in regional three-dimensional numerical earthquake ground-motion simulation, full waveform tomography, modern physics-based probabilistic earthquake hazard analysis, as well as in other related fields including geophysics, seismology, and earthquake engineering. The standard material properties provided by a seismic velocity model are P- and S-wave velocities and density for any arbitrary point within the geographic volume for which the model is defined. Many seismic velocity models and datasets are constructed by synthesizing information from multiple sources and the resulting models are delivered to users in multiple file formats, such as text files, binary files, HDF-5 files, structured and unstructured grids, and through computer applications that allow for interactive querying of material properties. The Southern California Earthquake Center (SCEC) has developed the Unified Community Velocity Model (UCVM) software framework to facilitate the registration and distribution of existing and future seismic velocity models to the SCEC community. The UCVM software framework is designed to provide a standard query interface to multiple, alternative velocity models, even if the underlying velocity models are defined in different formats or use different geographic projections. The UCVM framework provides a comprehensive set of open-source tools for querying seismic velocity model properties, combining regional 3D models and 1D background models, visualizing 3D models, and generating computational models in the form of regular grids or unstructured meshes that can be used as inputs for ground-motion simulations. The UCVM framework helps researchers compare seismic velocity models and build equivalent simulation meshes from alternative velocity models. These capabilities enable researchers to evaluate the impact of alternative velocity models in ground-motion simulations and seismic hazard analysis applications. In this poster, we summarize the key components of the UCVM framework and describe the impact it has had in various computational geoscientific applications.
Unified Program Design: Organizing Existing Programming Models, Delivery Options, and Curriculum
ERIC Educational Resources Information Center
Rubenstein, Lisa DaVia; Ridgley, Lisa M.
2017-01-01
A persistent problem in the field of gifted education has been the lack of categorization and delineation of gifted programming options. To address this issue, we propose Unified Program Design as a structural framework for gifted program models. This framework defines gifted programs as the combination of delivery methods and curriculum models.…
A Unified Framework for Complex Networks with Degree Trichotomy Based on Markov Chains.
Hui, David Shui Wing; Chen, Yi-Chao; Zhang, Gong; Wu, Weijie; Chen, Guanrong; Lui, John C S; Li, Yingtao
2017-06-16
This paper establishes a Markov chain model as a unified framework for describing the evolution processes in complex networks. The unique feature of the proposed model is its capability in addressing the formation mechanism that can reflect the "trichotomy" observed in degree distributions, based on which closed-form solutions can be derived. Important special cases of the proposed unified framework are those classical models, including Poisson, Exponential, Power-law distributed networks. Both simulation and experimental results demonstrate a good match of the proposed model with real datasets, showing its superiority over the classical models. Implications of the model to various applications including citation analysis, online social networks, and vehicular networks design, are also discussed in the paper.
VisRseq: R-based visual framework for analysis of sequencing data
2015-01-01
Background Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. Results We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. Conclusions To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights. PMID:26328469
VisRseq: R-based visual framework for analysis of sequencing data.
Younesy, Hamid; Möller, Torsten; Lorincz, Matthew C; Karimi, Mohammad M; Jones, Steven J M
2015-01-01
Several tools have been developed to enable biologists to perform initial browsing and exploration of sequencing data. However the computational tool set for further analyses often requires significant computational expertise to use and many of the biologists with the knowledge needed to interpret these data must rely on programming experts. We present VisRseq, a framework for analysis of sequencing datasets that provides a computationally rich and accessible framework for integrative and interactive analyses without requiring programming expertise. We achieve this aim by providing R apps, which offer a semi-auto generated and unified graphical user interface for computational packages in R and repositories such as Bioconductor. To address the interactivity limitation inherent in R libraries, our framework includes several native apps that provide exploration and brushing operations as well as an integrated genome browser. The apps can be chained together to create more powerful analysis workflows. To validate the usability of VisRseq for analysis of sequencing data, we present two case studies performed by our collaborators and report their workflow and insights.
Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita
2013-01-01
Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration.
Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita
2013-01-01
Objective Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. Materials and methods We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Results Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. Conclusions We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration. PMID:23571850
Incubation, Insight, and Creative Problem Solving: A Unified Theory and a Connectionist Model
ERIC Educational Resources Information Center
Helie, Sebastien; Sun, Ron
2010-01-01
This article proposes a unified framework for understanding creative problem solving, namely, the explicit-implicit interaction theory. This new theory of creative problem solving constitutes an attempt at providing a more unified explanation of relevant phenomena (in part by reinterpreting/integrating various fragmentary existing theories of…
A physiologically-based model for simulation of color vision deficiency.
Machado, Gustavo M; Oliveira, Manuel M; Fernandes, Leandro A F
2009-01-01
Color vision deficiency (CVD) affects approximately 200 million people worldwide, compromising the ability of these individuals to effectively perform color and visualization-related tasks. This has a significant impact on their private and professional lives. We present a physiologically-based model for simulating color vision. Our model is based on the stage theory of human color vision and is derived from data reported in electrophysiological studies. It is the first model to consistently handle normal color vision, anomalous trichromacy, and dichromacy in a unified way. We have validated the proposed model through an experimental evaluation involving groups of color vision deficient individuals and normal color vision ones. Our model can provide insights and feedback on how to improve visualization experiences for individuals with CVD. It also provides a framework for testing hypotheses about some aspects of the retinal photoreceptors in color vision deficient individuals.
Computational motor control: feedback and accuracy.
Guigon, Emmanuel; Baraduc, Pierre; Desmurget, Michel
2008-02-01
Speed/accuracy trade-off is a ubiquitous phenomenon in motor behaviour, which has been ascribed to the presence of signal-dependent noise (SDN) in motor commands. Although this explanation can provide a quantitative account of many aspects of motor variability, including Fitts' law, the fact that this law is frequently violated, e.g. during the acquisition of new motor skills, remains unexplained. Here, we describe a principled approach to the influence of noise on motor behaviour, in which motor variability results from the interplay between sensory and motor execution noises in an optimal feedback-controlled system. In this framework, we first show that Fitts' law arises due to signal-dependent motor noise (SDN(m)) when sensory (proprioceptive) noise is low, e.g. under visual feedback. Then we show that the terminal variability of non-visually guided movement can be explained by the presence of signal-dependent proprioceptive noise. Finally, we show that movement accuracy can be controlled by opposite changes in signal-dependent sensory (SDN(s)) and SDN(m), a phenomenon that could be ascribed to muscular co-contraction. As the model also explains kinematics, kinetics, muscular and neural characteristics of reaching movements, it provides a unified framework to address motor variability.
A unified framework of image latent feature learning on Sina microblog
NASA Astrophysics Data System (ADS)
Wei, Jinjin; Jin, Zhigang; Zhou, Yuan; Zhang, Rui
2015-10-01
Large-scale user-contributed images with texts are rapidly increasing on the social media websites, such as Sina microblog. However, the noise and incomplete correspondence between the images and the texts give rise to the difficulty in precise image retrieval and ranking. In this paper, a hypergraph-based learning framework is proposed for image ranking, which simultaneously utilizes visual feature, textual content and social link information to estimate the relevance between images. Representing each image as a vertex in the hypergraph, complex relationship between images can be reflected exactly. Then updating the weight of hyperedges throughout the hypergraph learning process, the effect of different edges can be adaptively modulated in the constructed hypergraph. Furthermore, the popularity degree of the image is employed to re-rank the retrieval results. Comparative experiments on a large-scale Sina microblog data-set demonstrate the effectiveness of the proposed approach.
ERIC Educational Resources Information Center
Center for Mental Health in Schools at UCLA, 2005
2005-01-01
This report was developed to highlight the current state of affairs and illustrate the value of a unifying framework and integrated infrastructure for the many initiatives, projects, programs, and services schools pursue in addressing barriers to learning and promoting healthy development. Specifically, it highlights how initiatives can be…
Toward semantic-based retrieval of visual information: a model-based approach
NASA Astrophysics Data System (ADS)
Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman
2002-07-01
This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.
Toward a unifying framework for evolutionary processes.
Paixão, Tiago; Badkobeh, Golnaz; Barton, Nick; Çörüş, Doğan; Dang, Duc-Cuong; Friedrich, Tobias; Lehre, Per Kristian; Sudholt, Dirk; Sutton, Andrew M; Trubenová, Barbora
2015-10-21
The theory of population genetics and evolutionary computation have been evolving separately for nearly 30 years. Many results have been independently obtained in both fields and many others are unique to its respective field. We aim to bridge this gap by developing a unifying framework for evolutionary processes that allows both evolutionary algorithms and population genetics models to be cast in the same formal framework. The framework we present here decomposes the evolutionary process into its several components in order to facilitate the identification of similarities between different models. In particular, we propose a classification of evolutionary operators based on the defining properties of the different components. We cast several commonly used operators from both fields into this common framework. Using this, we map different evolutionary and genetic algorithms to different evolutionary regimes and identify candidates with the most potential for the translation of results between the fields. This provides a unified description of evolutionary processes and represents a stepping stone towards new tools and results to both fields. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
A Unified Classification Framework for FP, DP and CP Data at X-Band in Southern China
NASA Astrophysics Data System (ADS)
Xie, Lei; Zhang, Hong; Li, Hhongzhong; Wang, Chao
2015-04-01
The main objective of this paper is to introduce an unified framework for crop classification in Southern China using data in fully polarimetric (FP), dual-pol (DP) and compact polarimetric (CP) modes. The TerraSAR-X data acquired over the Leizhou Peninsula, South China are used in our experiments. The study site involves four main crops (rice, banana, sugarcane eucalyptus). Through exploring the similarities between data in these three modes, a knowledge-based characteristic space is created and the unified framework is presented. The overall classification accuracies for data in the FP, coherent HH/VV are about 95%, and is about 91% in CP modes, which suggests that the proposed classification scheme is effective and promising. Compared with the Wishart Maximum Likelihood (ML) classifier, the proposed method exhibits higher classification accuracy.
The Unified Behavior Framework for the Simulation of Autonomous Agents
2015-03-01
1980s, researchers have designed a variety of robot control architectures intending to imbue robots with some degree of autonomy. A recently developed ...Identification Friend or Foe viii THE UNIFIED BEHAVIOR FRAMEWORK FOR THE SIMULATION OF AUTONOMOUS AGENTS I. Introduction The development of autonomy has...room for research by utilizing methods like simulation and modeling that consume less time and fewer monetary resources. A recently developed reactive
Kiefer, Markus; Ansorge, Ulrich; Haynes, John-Dylan; Hamker, Fred; Mattler, Uwe; Verleger, Rolf; Niedeggen, Michael
2011-01-01
Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research. PMID:22253669
Marchand-Krynski, Marie-Ève; Bélanger, Anne-Marie; Morin-Moncet, Olivier; Beauchamp, Miriam H; Leonard, Gabriel
2018-01-01
This study examined cognitive predictors of sequential motor skills in 215 children with dyslexia and/or attention deficit/hyperactivity disorder (ADHD). Visual working memory and math fluency abilities contributed significantly to performance of sequential motor abilities in children with dyslexia (N = 67), ADHD (N = 66) and those with a comorbid diagnosis (N = 82), generally without differentiation between groups. In addition, primary diagnostic features of each disorder, such as reading and inattention, did not contribute to the variance in motor skill performance of these children. The results support a unifying framework of motor impairment in children with neurodevelopmental disorders such as dyslexia and ADHD.
A Unified Probabilistic Framework for Dose–Response Assessment of Human Health Effects
Slob, Wout
2015-01-01
Background When chemical health hazards have been identified, probabilistic dose–response assessment (“hazard characterization”) quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework. Objectives We developed a unified framework for probabilistic dose–response assessment. Methods We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose–response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, “effect metrics” can be specified to define “toxicologically equivalent” sizes for this underlying individual response; and d) dose–response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose–response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets. Results Probabilistically derived exposure limits are based on estimating a “target human dose” (HDMI), which requires risk management–informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%–10% effect sizes. Conclusions Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions. Citation Chiu WA, Slob W. 2015. A unified probabilistic framework for dose–response assessment of human health effects. Environ Health Perspect 123:1241–1254; http://dx.doi.org/10.1289/ehp.1409385 PMID:26006063
Canessa, Andrea; Gibaldi, Agostino; Chessa, Manuela; Fato, Marco; Solari, Fabio; Sabatini, Silvio P.
2017-01-01
Binocular stereopsis is the ability of a visual system, belonging to a live being or a machine, to interpret the different visual information deriving from two eyes/cameras for depth perception. From this perspective, the ground-truth information about three-dimensional visual space, which is hardly available, is an ideal tool both for evaluating human performance and for benchmarking machine vision algorithms. In the present work, we implemented a rendering methodology in which the camera pose mimics realistic eye pose for a fixating observer, thus including convergent eye geometry and cyclotorsion. The virtual environment we developed relies on highly accurate 3D virtual models, and its full controllability allows us to obtain the stereoscopic pairs together with the ground-truth depth and camera pose information. We thus created a stereoscopic dataset: GENUA PESTO—GENoa hUman Active fixation database: PEripersonal space STereoscopic images and grOund truth disparity. The dataset aims to provide a unified framework useful for a number of problems relevant to human and computer vision, from scene exploration and eye movement studies to 3D scene reconstruction. PMID:28350382
Gestalten of today: early processing of visual contours and surfaces.
Kovács, I
1996-12-01
While much is known about the specialized, parallel processing streams of low-level vision that extract primary visual cues, there is only limited knowledge about the dynamic interactions between them. How are the fragments, caught by local analyzers, assembled together to provide us with a unified percept? How are local discontinuities in texture, motion or depth evaluated with respect to object boundaries and surface properties? These questions are presented within the framework of orientation-specific spatial interactions of early vision. Key observations of psychophysics, anatomy and neurophysiology on interactions of various spatial and temporal ranges are reviewed. Aspects of the functional architecture and possible neural substrates of local orientation-specific interactions are discussed, underlining their role in the integration of information across the visual field, and particularly in contour integration. Examples are provided demonstrating that global context, such as contour closure and figure-ground assignment, affects these local interactions. It is illustrated that figure-ground assignment is realized early in visual processing, and that the pattern of early interactions also brings about an effective and sparse coding of visual shape. Finally, it is concluded that the underlying functional architecture is not only dynamic and context dependent, but the pattern of connectivity depends as much on past experience as on actual stimulation.
ConnectViz: Accelerated Approach for Brain Structural Connectivity Using Delaunay Triangulation.
Adeshina, A M; Hashim, R
2016-03-01
Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using compute unified device architecture, extending the previously proposed SurLens Visualization and computer aided hepatocellular carcinoma frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, USA. Significantly, our proposed framework is able to generate and extract points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.
ConnectViz: Accelerated approach for brain structural connectivity using Delaunay triangulation.
Adeshina, A M; Hashim, R
2015-02-06
Stroke is a cardiovascular disease with high mortality and long-term disability in the world. Normal functioning of the brain is dependent on the adequate supply of oxygen and nutrients to the brain complex network through the blood vessels. Stroke, occasionally a hemorrhagic stroke, ischemia or other blood vessel dysfunctions can affect patients during a cerebrovascular incident. Structurally, the left and the right carotid arteries, and the right and the left vertebral arteries are responsible for supplying blood to the brain, scalp and the face. However, a number of impairment in the function of the frontal lobes may occur as a result of any decrease in the flow of the blood through one of the internal carotid arteries. Such impairment commonly results in numbness, weakness or paralysis. Recently, the concepts of brain's wiring representation, the connectome, was introduced. However, construction and visualization of such brain network requires tremendous computation. Consequently, previously proposed approaches have been identified with common problems of high memory consumption and slow execution. Furthermore, interactivity in the previously proposed frameworks for brain network is also an outstanding issue. This study proposes an accelerated approach for brain connectomic visualization based on graph theory paradigm using Compute Unified Device Architecture (CUDA), extending the previously proposed SurLens Visualization and Computer Aided Hepatocellular Carcinoma (CAHECA) frameworks. The accelerated brain structural connectivity framework was evaluated with stripped brain datasets from the Department of Surgery, University of North Carolina, Chapel Hill, United States. Significantly, our proposed framework is able to generates and extracts points and edges of datasets, displays nodes and edges in the datasets in form of a network and clearly maps data volume to the corresponding brain surface. Moreover, with the framework, surfaces of the dataset were simultaneously displayed with the nodes and the edges. The framework is very efficient in providing greater interactivity as a way of representing the nodes and the edges intuitively, all achieved at a considerably interactive speed for instantaneous mapping of the datasets' features. Uniquely, the connectomic algorithm performed remarkably fast with normal hardware requirement specifications.
Robopedia: Leveraging Sensorpedia for Web-Enabled Robot Control
DOE Office of Scientific and Technical Information (OSTI.GOV)
Resseguie, David R
There is a growing interest in building Internetscale sensor networks that integrate sensors from around the world into a single unified system. In contrast, robotics application development has primarily focused on building specialized systems. These specialized systems take scalability and reliability into consideration, but generally neglect exploring the key components required to build a large scale system. Integrating robotic applications with Internet-scale sensor networks will unify specialized robotics applications and provide answers to large scale implementation concerns. We focus on utilizing Internet-scale sensor network technology to construct a framework for unifying robotic systems. Our framework web-enables a surveillance robot smore » sensor observations and provides a webinterface to the robot s actuators. This lets robots seamlessly integrate into web applications. In addition, the framework eliminates most prerequisite robotics knowledge, allowing for the creation of general web-based robotics applications. The framework also provides mechanisms to create applications that can interface with any robot. Frameworks such as this one are key to solving large scale mobile robotics implementation problems. We provide an overview of previous Internetscale sensor networks, Sensorpedia (an ad-hoc Internet-scale sensor network), our framework for integrating robots with Sensorpedia, two applications which illustrate our frameworks ability to support general web-based robotic control, and offer experimental results that illustrate our framework s scalability, feasibility, and resource requirements.« less
Physically Based Modeling and Simulation with Dynamic Spherical Volumetric Simplex Splines
Tan, Yunhao; Hua, Jing; Qin, Hong
2009-01-01
In this paper, we present a novel computational modeling and simulation framework based on dynamic spherical volumetric simplex splines. The framework can handle the modeling and simulation of genus-zero objects with real physical properties. In this framework, we first develop an accurate and efficient algorithm to reconstruct the high-fidelity digital model of a real-world object with spherical volumetric simplex splines which can represent with accuracy geometric, material, and other properties of the object simultaneously. With the tight coupling of Lagrangian mechanics, the dynamic volumetric simplex splines representing the object can accurately simulate its physical behavior because it can unify the geometric and material properties in the simulation. The visualization can be directly computed from the object’s geometric or physical representation based on the dynamic spherical volumetric simplex splines during simulation without interpolation or resampling. We have applied the framework for biomechanic simulation of brain deformations, such as brain shifting during the surgery and brain injury under blunt impact. We have compared our simulation results with the ground truth obtained through intra-operative magnetic resonance imaging and the real biomechanic experiments. The evaluations demonstrate the excellent performance of our new technique. PMID:20161636
Gravity as a Strong Prior: Implications for Perception and Action.
Jörges, Björn; López-Moliner, Joan
2017-01-01
In the future, humans are likely to be exposed to environments with altered gravity conditions, be it only visually (Virtual and Augmented Reality), or visually and bodily (space travel). As visually and bodily perceived gravity as well as an interiorized representation of earth gravity are involved in a series of tasks, such as catching, grasping, body orientation estimation and spatial inferences, humans will need to adapt to these new gravity conditions. Performance under earth gravity discrepant conditions has been shown to be relatively poor, and few studies conducted in gravity adaptation are rather discouraging. Especially in VR on earth, conflicts between bodily and visual gravity cues seem to make a full adaptation to visually perceived earth-discrepant gravities nearly impossible, and even in space, when visual and bodily cues are congruent, adaptation is extremely slow. We invoke a Bayesian framework for gravity related perceptual processes, in which earth gravity holds the status of a so called "strong prior". As other strong priors, the gravity prior has developed through years and years of experience in an earth gravity environment. For this reason, the reliability of this representation is extremely high and overrules any sensory information to its contrary. While also other factors such as the multisensory nature of gravity perception need to be taken into account, we present the strong prior account as a unifying explanation for empirical results in gravity perception and adaptation to earth-discrepant gravities.
A unified account of tilt illusions, association fields, and contour detection based on elastica.
Keemink, Sander W; van Rossum, Mark C W
2016-09-01
As expressed in the Gestalt law of good continuation, human perception tends to associate stimuli that form smooth continuations. Contextual modulation in primary visual cortex, in the form of association fields, is believed to play an important role in this process. Yet a unified and principled account of the good continuation law on the neural level is lacking. In this study we introduce a population model of primary visual cortex. Its contextual interactions depend on the elastica curvature energy of the smoothest contour connecting oriented bars. As expected, this model leads to association fields consistent with data. However, in addition the model displays tilt-illusions for stimulus configurations with grating and single bars that closely match psychophysics. Furthermore, the model explains not only pop-out of contours amid a variety of backgrounds, but also pop-out of single targets amid a uniform background. We thus propose that elastica is a unifying principle of the visual cortical network. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Two Distinct Scene-Processing Networks Connecting Vision and Memory.
Baldassano, Christopher; Esteva, Andre; Fei-Fei, Li; Beck, Diane M
2016-01-01
A number of regions in the human brain are known to be involved in processing natural scenes, but the field has lacked a unifying framework for understanding how these different regions are organized and interact. We provide evidence from functional connectivity and meta-analyses for a new organizational principle, in which scene processing relies upon two distinct networks that split the classically defined parahippocampal place area (PPA). The first network of strongly connected regions consists of the occipital place area/transverse occipital sulcus and posterior PPA, which contain retinotopic maps and are not strongly coupled to the hippocampus at rest. The second network consists of the caudal inferior parietal lobule, retrosplenial complex, and anterior PPA, which connect to the hippocampus (especially anterior hippocampus), and are implicated in both visual and nonvisual tasks, including episodic memory and navigation. We propose that these two distinct networks capture the primary functional division among scene-processing regions, between those that process visual features from the current view of a scene and those that connect information from a current scene view with a much broader temporal and spatial context. This new framework for understanding the neural substrates of scene-processing bridges results from many lines of research, and makes specific functional predictions.
NASA Astrophysics Data System (ADS)
Chun, Won-Suk; Napoli, Joshua; Cossairt, Oliver S.; Dorval, Rick K.; Hall, Deirdre M.; Purtell, Thomas J., II; Schooler, James F.; Banker, Yigal; Favalora, Gregg E.
2005-03-01
We present a software and hardware foundation to enable the rapid adoption of 3-D displays. Different 3-D displays - such as multiplanar, multiview, and electroholographic displays - naturally require different rendering methods. The adoption of these displays in the marketplace will be accelerated by a common software framework. The authors designed the SpatialGL API, a new rendering framework that unifies these display methods under one interface. SpatialGL enables complementary visualization assets to coexist through a uniform infrastructure. Also, SpatialGL supports legacy interfaces such as the OpenGL API. The authors" first implementation of SpatialGL uses multiview and multislice rendering algorithms to exploit the performance of modern graphics processing units (GPUs) to enable real-time visualization of 3-D graphics from medical imaging, oil & gas exploration, and homeland security. At the time of writing, SpatialGL runs on COTS workstations (both Windows and Linux) and on Actuality"s high-performance embedded computational engine that couples an NVIDIA GeForce 6800 Ultra GPU, an AMD Athlon 64 processor, and a proprietary, high-speed, programmable volumetric frame buffer that interfaces to a 1024 x 768 x 3 digital projector. Progress is illustrated using an off-the-shelf multiview display, Actuality"s multiplanar Perspecta Spatial 3D System, and an experimental multiview display. The experimental display is a quasi-holographic view-sequential system that generates aerial imagery measuring 30 mm x 25 mm x 25 mm, providing 198 horizontal views.
Bayesian modeling of cue interaction: bistability in stereoscopic slant perception.
van Ee, Raymond; Adams, Wendy J; Mamassian, Pascal
2003-07-01
Our two eyes receive different views of a visual scene, and the resulting binocular disparities enable us to reconstruct its three-dimensional layout. However, the visual environment is also rich in monocular depth cues. We examined the resulting percept when observers view a scene in which there are large conflicts between the surface slant signaled by binocular disparities and the slant signaled by monocular perspective. For a range of disparity-perspective cue conflicts, many observers experience bistability: They are able to perceive two distinct slants and to flip between the two percepts in a controlled way. We present a Bayesian model that describes the quantitative aspects of perceived slant on the basis of the likelihoods of both perspective and disparity slant information combined with prior assumptions about the shape and orientation of objects in the scene. Our Bayesian approach can be regarded as an overarching framework that allows researchers to study all cue integration aspects-including perceptual decisions--in a unified manner.
Integrating Satellite, Radar and Surface Observation with Time and Space Matching
NASA Astrophysics Data System (ADS)
Ho, Y.; Weber, J.
2015-12-01
The Integrated Data Viewer (IDV) from Unidata is a Java™-based software framework for analyzing and visualizing geoscience data. It brings together the ability to display and work with satellite imagery, gridded data, surface observations, balloon soundings, NWS WSR-88D Level II and Level III RADAR data, and NOAA National Profiler Network data, all within a unified interface. Applying time and space matching on the satellite, radar and surface observation datasets will automatically synchronize the display from different data sources and spatially subset to match the display area in the view window. These features allow the IDV users to effectively integrate these observations and provide 3 dimensional views of the weather system to better understand the underlying dynamics and physics of weather phenomena.
Volcano plots in analyzing differential expressions with mRNA microarrays.
Li, Wentian
2012-12-01
A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.
Prior expectations facilitate metacognition for perceptual decision.
Sherman, M T; Seth, A K; Barrett, A B; Kanai, R
2015-09-01
The influential framework of 'predictive processing' suggests that prior probabilistic expectations influence, or even constitute, perceptual contents. This notion is evidenced by the facilitation of low-level perceptual processing by expectations. However, whether expectations can facilitate high-level components of perception remains unclear. We addressed this question by considering the influence of expectations on perceptual metacognition. To isolate the effects of expectation from those of attention we used a novel factorial design: expectation was manipulated by changing the probability that a Gabor target would be presented; attention was manipulated by instructing participants to perform or ignore a concurrent visual search task. We found that, independently of attention, metacognition improved when yes/no responses were congruent with expectations of target presence/absence. Results were modeled under a novel Bayesian signal detection theoretic framework which integrates bottom-up signal propagation with top-down influences, to provide a unified description of the mechanisms underlying perceptual decision and metacognition. Copyright © 2015 Elsevier Inc. All rights reserved.
An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization.
Jalba, Andrei C; Sobiecki, Andre; Telea, Alexandru C
2016-01-01
Computing skeletons of 2D shapes, and medial surface and curve skeletons of 3D shapes, is a challenging task. In particular, there is no unified framework that detects all types of skeletons using a single model, and also produces a multiscale representation which allows to progressively simplify, or regularize, all skeleton types. In this paper, we present such a framework. We model skeleton detection and regularization by a conservative mass transport process from a shape's boundary to its surface skeleton, next to its curve skeleton, and finally to the shape center. The resulting density field can be thresholded to obtain a multiscale representation of progressively simplified surface, or curve, skeletons. We detail a numerical implementation of our framework which is demonstrably stable and has high computational efficiency. We demonstrate our framework on several complex 2D and 3D shapes.
Desantis, Andrea; Haggard, Patrick
2016-01-01
To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events. PMID:27982063
Desantis, Andrea; Haggard, Patrick
2016-12-16
To maintain a temporally-unified representation of audio and visual features of objects in our environment, the brain recalibrates audio-visual simultaneity. This process allows adjustment for both differences in time of transmission and time for processing of audio and visual signals. In four experiments, we show that the cognitive processes for controlling instrumental actions also have strong influence on audio-visual recalibration. Participants learned that right and left hand button-presses each produced a specific audio-visual stimulus. Following one action the audio preceded the visual stimulus, while for the other action audio lagged vision. In a subsequent test phase, left and right button-press generated either the same audio-visual stimulus as learned initially, or the pair associated with the other action. We observed recalibration of simultaneity only for previously-learned audio-visual outcomes. Thus, learning an action-outcome relation promotes temporal grouping of the audio and visual events within the outcome pair, contributing to the creation of a temporally unified multisensory object. This suggests that learning action-outcome relations and the prediction of perceptual outcomes can provide an integrative temporal structure for our experiences of external events.
Unipro UGENE: a unified bioinformatics toolkit.
Okonechnikov, Konstantin; Golosova, Olga; Fursov, Mikhail
2012-04-15
Unipro UGENE is a multiplatform open-source software with the main goal of assisting molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality. UGENE binaries are freely available for MS Windows, Linux and Mac OS X at http://ugene.unipro.ru/download.html. UGENE code is licensed under the GPLv2; the information about the code licensing and copyright of integrated tools can be found in the LICENSE.3rd_party file provided with the source bundle.
CoCoNUT: an efficient system for the comparison and analysis of genomes
2008-01-01
Background Comparative genomics is the analysis and comparison of genomes from different species. This area of research is driven by the large number of sequenced genomes and heavily relies on efficient algorithms and software to perform pairwise and multiple genome comparisons. Results Most of the software tools available are tailored for one specific task. In contrast, we have developed a novel system CoCoNUT (Computational Comparative geNomics Utility Toolkit) that allows solving several different tasks in a unified framework: (1) finding regions of high similarity among multiple genomic sequences and aligning them, (2) comparing two draft or multi-chromosomal genomes, (3) locating large segmental duplications in large genomic sequences, and (4) mapping cDNA/EST to genomic sequences. Conclusion CoCoNUT is competitive with other software tools w.r.t. the quality of the results. The use of state of the art algorithms and data structures allows CoCoNUT to solve comparative genomics tasks more efficiently than previous tools. With the improved user interface (including an interactive visualization component), CoCoNUT provides a unified, versatile, and easy-to-use software tool for large scale studies in comparative genomics. PMID:19014477
A unified probabilistic framework for spontaneous facial action modeling and understanding.
Tong, Yan; Chen, Jixu; Ji, Qiang
2010-02-01
Facial expression is a natural and powerful means of human communication. Recognizing spontaneous facial actions, however, is very challenging due to subtle facial deformation, frequent head movements, and ambiguous and uncertain facial motion measurements. Because of these challenges, current research in facial expression recognition is limited to posed expressions and often in frontal view. A spontaneous facial expression is characterized by rigid head movements and nonrigid facial muscular movements. More importantly, it is the coherent and consistent spatiotemporal interactions among rigid and nonrigid facial motions that produce a meaningful facial expression. Recognizing this fact, we introduce a unified probabilistic facial action model based on the Dynamic Bayesian network (DBN) to simultaneously and coherently represent rigid and nonrigid facial motions, their spatiotemporal dependencies, and their image measurements. Advanced machine learning methods are introduced to learn the model based on both training data and subjective prior knowledge. Given the model and the measurements of facial motions, facial action recognition is accomplished through probabilistic inference by systematically integrating visual measurements with the facial action model. Experiments show that compared to the state-of-the-art techniques, the proposed system yields significant improvements in recognizing both rigid and nonrigid facial motions, especially for spontaneous facial expressions.
The manager's guide to NASA graphics standards
NASA Technical Reports Server (NTRS)
1980-01-01
NASA managers have the responsibility to initiate and carry out communication projects with a degree of sophistication that properly reflects the agency's substantial work. Over the course of the last decade, it has become more important to clearly communicate NASA's objectives in aeronautical research, space exploration, and related sciences. Many factors come into play when preparing communication materials for internal and external use. Three overriding factors are: producing the materials by the most cost-efficient method; ensuring that each item reflects the vitality, knowledge, and precision of NASA; and portraying all visual materials with a unified appearance. This guide will serve as the primary tool in meeting these criteria. This publication spells out the many benefits inherent in the Unified Visual Communication System and describes how the system was developed. The last section lists the graphic coordinators at headquarters and the centers who can assist with graphic projects. By understanding the Unified Visual Communication System, NASA managers will be able to manage a project from inception through production in the most cost-effective manner while maintaining the quality of NASA communications.
Cusack, Lynette; Smith, Morgan; Hegney, Desley; Rees, Clare S; Breen, Lauren J; Witt, Regina R; Rogers, Cath; Williams, Allison; Cross, Wendy; Cheung, Kin
2016-01-01
Building nurses' resilience to complex and stressful practice environments is necessary to keep skilled nurses in the workplace and ensuring safe patient care. A unified theoretical framework titled Health Services Workplace Environmental Resilience Model (HSWERM), is presented to explain the environmental factors in the workplace that promote nurses' resilience. The framework builds on a previously-published theoretical model of individual resilience, which identified the key constructs of psychological resilience as self-efficacy, coping and mindfulness, but did not examine environmental factors in the workplace that promote nurses' resilience. This unified theoretical framework was developed using a literary synthesis drawing on data from international studies and literature reviews on the nursing workforce in hospitals. The most frequent workplace environmental factors were identified, extracted and clustered in alignment with key constructs for psychological resilience. Six major organizational concepts emerged that related to a positive resilience-building workplace and formed the foundation of the theoretical model. Three concepts related to nursing staff support (professional, practice, personal) and three related to nursing staff development (professional, practice, personal) within the workplace environment. The unified theoretical model incorporates these concepts within the workplace context, linking to the nurse, and then impacting on personal resilience and workplace outcomes, and its use has the potential to increase staff retention and quality of patient care.
A Unified Framework for Association Analysis with Multiple Related Phenotypes
Stephens, Matthew
2013-01-01
We consider the problem of assessing associations between multiple related outcome variables, and a single explanatory variable of interest. This problem arises in many settings, including genetic association studies, where the explanatory variable is genotype at a genetic variant. We outline a framework for conducting this type of analysis, based on Bayesian model comparison and model averaging for multivariate regressions. This framework unifies several common approaches to this problem, and includes both standard univariate and standard multivariate association tests as special cases. The framework also unifies the problems of testing for associations and explaining associations – that is, identifying which outcome variables are associated with genotype. This provides an alternative to the usual, but conceptually unsatisfying, approach of resorting to univariate tests when explaining and interpreting significant multivariate findings. The method is computationally tractable genome-wide for modest numbers of phenotypes (e.g. 5–10), and can be applied to summary data, without access to raw genotype and phenotype data. We illustrate the methods on both simulated examples, and to a genome-wide association study of blood lipid traits where we identify 18 potential novel genetic associations that were not identified by univariate analyses of the same data. PMID:23861737
Ridgeway, Jennifer L; Wang, Zhen; Finney Rutten, Lila J; van Ryn, Michelle; Griffin, Joan M; Murad, M Hassan; Asiedu, Gladys B; Egginton, Jason S; Beebe, Timothy J
2017-08-04
There exists a paucity of work in the development and testing of theoretical models specific to childhood health disparities even though they have been linked to the prevalence of adult health disparities including high rates of chronic disease. We conducted a systematic review and thematic analysis of existing models of health disparities specific to children to inform development of a unified conceptual framework. We systematically reviewed articles reporting theoretical or explanatory models of disparities on a range of outcomes related to child health. We searched Ovid Medline In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid Embase, Ovid Cochrane Central Register of Controlled Trials, Ovid Cochrane Database of Systematic Reviews, and Scopus (database inception to 9 July 2015). A metanarrative approach guided the analysis process. A total of 48 studies presenting 48 models were included. This systematic review found multiple models but no consensus on one approach. However, we did discover a fair amount of overlap, such that the 48 models reviewed converged into the unified conceptual framework. The majority of models included factors in three domains: individual characteristics and behaviours (88%), healthcare providers and systems (63%), and environment/community (56%), . Only 38% of models included factors in the health and public policies domain. A disease-agnostic unified conceptual framework may inform integration of existing knowledge of child health disparities and guide future research. This multilevel framework can focus attention among clinical, basic and social science research on the relationships between policy, social factors, health systems and the physical environment that impact children's health outcomes. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
A Unified Probabilistic Framework for Dose-Response Assessment of Human Health Effects.
Chiu, Weihsueh A; Slob, Wout
2015-12-01
When chemical health hazards have been identified, probabilistic dose-response assessment ("hazard characterization") quantifies uncertainty and/or variability in toxicity as a function of human exposure. Existing probabilistic approaches differ for different types of endpoints or modes-of-action, lacking a unifying framework. We developed a unified framework for probabilistic dose-response assessment. We established a framework based on four principles: a) individual and population dose responses are distinct; b) dose-response relationships for all (including quantal) endpoints can be recast as relating to an underlying continuous measure of response at the individual level; c) for effects relevant to humans, "effect metrics" can be specified to define "toxicologically equivalent" sizes for this underlying individual response; and d) dose-response assessment requires making adjustments and accounting for uncertainty and variability. We then derived a step-by-step probabilistic approach for dose-response assessment of animal toxicology data similar to how nonprobabilistic reference doses are derived, illustrating the approach with example non-cancer and cancer datasets. Probabilistically derived exposure limits are based on estimating a "target human dose" (HDMI), which requires risk management-informed choices for the magnitude (M) of individual effect being protected against, the remaining incidence (I) of individuals with effects ≥ M in the population, and the percent confidence. In the example datasets, probabilistically derived 90% confidence intervals for HDMI values span a 40- to 60-fold range, where I = 1% of the population experiences ≥ M = 1%-10% effect sizes. Although some implementation challenges remain, this unified probabilistic framework can provide substantially more complete and transparent characterization of chemical hazards and support better-informed risk management decisions.
Gravity as a Strong Prior: Implications for Perception and Action
Jörges, Björn; López-Moliner, Joan
2017-01-01
In the future, humans are likely to be exposed to environments with altered gravity conditions, be it only visually (Virtual and Augmented Reality), or visually and bodily (space travel). As visually and bodily perceived gravity as well as an interiorized representation of earth gravity are involved in a series of tasks, such as catching, grasping, body orientation estimation and spatial inferences, humans will need to adapt to these new gravity conditions. Performance under earth gravity discrepant conditions has been shown to be relatively poor, and few studies conducted in gravity adaptation are rather discouraging. Especially in VR on earth, conflicts between bodily and visual gravity cues seem to make a full adaptation to visually perceived earth-discrepant gravities nearly impossible, and even in space, when visual and bodily cues are congruent, adaptation is extremely slow. We invoke a Bayesian framework for gravity related perceptual processes, in which earth gravity holds the status of a so called “strong prior”. As other strong priors, the gravity prior has developed through years and years of experience in an earth gravity environment. For this reason, the reliability of this representation is extremely high and overrules any sensory information to its contrary. While also other factors such as the multisensory nature of gravity perception need to be taken into account, we present the strong prior account as a unifying explanation for empirical results in gravity perception and adaptation to earth-discrepant gravities. PMID:28503140
A unified framework for approximation in inverse problems for distributed parameter systems
NASA Technical Reports Server (NTRS)
Banks, H. T.; Ito, K.
1988-01-01
A theoretical framework is presented that can be used to treat approximation techniques for very general classes of parameter estimation problems involving distributed systems that are either first or second order in time. Using the approach developed, one can obtain both convergence and stability (continuous dependence of parameter estimates with respect to the observations) under very weak regularity and compactness assumptions on the set of admissible parameters. This unified theory can be used for many problems found in the recent literature and in many cases offers significant improvements to existing results.
A general modeling framework for describing spatially structured population dynamics
Sample, Christine; Fryxell, John; Bieri, Joanna; Federico, Paula; Earl, Julia; Wiederholt, Ruscena; Mattsson, Brady; Flockhart, Tyler; Nicol, Sam; Diffendorfer, James E.; Thogmartin, Wayne E.; Erickson, Richard A.; Norris, D. Ryan
2017-01-01
Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network-based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life-history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network-based population is modeled with discrete time steps. Using both theoretical and real-world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network-based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles
In Search of a Unified Model of Language Contact
ERIC Educational Resources Information Center
Winford, Donald
2013-01-01
Much previous research has pointed to the need for a unified framework for language contact phenomena -- one that would include social factors and motivations, structural factors and linguistic constraints, and psycholinguistic factors involved in processes of language processing and production. While Contact Linguistics has devoted a great deal…
Web-GIS-based SARS epidemic situation visualization
NASA Astrophysics Data System (ADS)
Lu, Xiaolin
2004-03-01
In order to research, perform statistical analysis and broadcast the information of SARS epidemic situation according to the relevant spatial position, this paper proposed a unified global visualization information platform for SARS epidemic situation based on Web-GIS and scientific virtualization technology. To setup the unified global visual information platform, the architecture of Web-GIS based interoperable information system is adopted to enable public report SARS virus information to health cure center visually by using the web visualization technology. A GIS java applet is used to visualize the relationship between spatial graphical data and virus distribution, and other web based graphics figures such as curves, bars, maps and multi-dimensional figures are used to visualize the relationship between SARS virus tendency with time, patient number or locations. The platform is designed to display the SARS information in real time, simulate visually for real epidemic situation and offer an analyzing tools for health department and the policy-making government department to support the decision-making for preventing against the SARS epidemic virus. It could be used to analyze the virus condition through visualized graphics interface, isolate the areas of virus source, and control the virus condition within shortest time. It could be applied to the visualization field of SARS preventing systems for SARS information broadcasting, data management, statistical analysis, and decision supporting.
A unified account of gloss and lightness perception in terms of gamut relativity.
Vladusich, Tony
2013-08-01
A recently introduced computational theory of visual surface representation, termed gamut relativity, overturns the classical assumption that brightness, lightness, and transparency constitute perceptual dimensions corresponding to the physical dimensions of luminance, diffuse reflectance, and transmittance, respectively. Here I extend the theory to show how surface gloss and lightness can be understood in a unified manner in terms of the vector computation of "layered representations" of surface and illumination properties, rather than as perceptual dimensions corresponding to diffuse and specular reflectance, respectively. The theory simulates the effects of image histogram skewness on surface gloss/lightness and lightness constancy as a function of specular highlight intensity. More generally, gamut relativity clarifies, unifies, and generalizes a wide body of previous theoretical and experimental work aimed at understanding how the visual system parses the retinal image into layered representations of surface and illumination properties.
An integrated radar model solution for mission level performance and cost trades
NASA Astrophysics Data System (ADS)
Hodge, John; Duncan, Kerron; Zimmerman, Madeline; Drupp, Rob; Manno, Mike; Barrett, Donald; Smith, Amelia
2017-05-01
A fully integrated Mission-Level Radar model is in development as part of a multi-year effort under the Northrop Grumman Mission Systems (NGMS) sector's Model Based Engineering (MBE) initiative to digitally interconnect and unify previously separate performance and cost models. In 2016, an NGMS internal research and development (IR and D) funded multidisciplinary team integrated radio frequency (RF), power, control, size, weight, thermal, and cost models together using a commercial-off-the-shelf software, ModelCenter, for an Active Electronically Scanned Array (AESA) radar system. Each represented model was digitally connected with standard interfaces and unified to allow end-to-end mission system optimization and trade studies. The radar model was then linked to the Air Force's own mission modeling framework (AFSIM). The team first had to identify the necessary models, and with the aid of subject matter experts (SMEs) understand and document the inputs, outputs, and behaviors of the component models. This agile development process and collaboration enabled rapid integration of disparate models and the validation of their combined system performance. This MBE framework will allow NGMS to design systems more efficiently and affordably, optimize architectures, and provide increased value to the customer. The model integrates detailed component models that validate cost and performance at the physics level with high-level models that provide visualization of a platform mission. This connectivity of component to mission models allows hardware and software design solutions to be better optimized to meet mission needs, creating cost-optimal solutions for the customer, while reducing design cycle time through risk mitigation and early validation of design decisions.
Identification of vortices in complex flows
NASA Astrophysics Data System (ADS)
Chakraborty, P.; Balachandar, S.; Adrian, R. J.
2007-12-01
Dating back to Leonardo da Vinci's famous sketches of vortices in turbulent flows, fluid dynamicists for over five centuries have continued to visualize and interpret complex flows in terms of motion of vortices. Nevertheless, much debate surrounds the question of how to unambiguously define vortices in complex flows. This debate has resulted in the availability of many vortex identification criteria---mathematical statements of what constitutes a vortex. Here we review the popularly used local or point- wise vortex identification criteria. Based on local flow kinematics, we describe a unified framework to interpret the similarities and differences in the usage of these criteria. We discuss the limitations on the applicability of these criteria when there is a significant component of vortex interactions. Finally, we provide guidelines for applying these criteria to geophysical flows.
Bui Quoc, Emmanuel; Ribot, Jérôme; Quenech’Du, Nicole; Doutremer, Suzette; Lebas, Nicolas; Grantyn, Alexej; Aushana, Yonane; Milleret, Chantal
2011-01-01
In the mammalian primary visual cortex, the corpus callosum contributes to the unification of the visual hemifields that project to the two hemispheres. Its development depends on visual experience. When this is abnormal, callosal connections must undergo dramatic anatomical and physiological changes. However, data concerning these changes are sparse and incomplete. Thus, little is known about the impact of abnormal postnatal visual experience on the development of callosal connections and their role in unifying representation of the two hemifields. Here, the effects of early unilateral convergent strabismus (a model of abnormal visual experience) were fully characterized with respect to the development of the callosal connections in cat visual cortex, an experimental model for humans. Electrophysiological responses and 3D reconstruction of single callosal axons show that abnormally asymmetrical callosal connections develop after unilateral convergent strabismus, resulting from an extension of axonal branches of specific orders in the hemisphere ipsilateral to the deviated eye and a decreased number of nodes and terminals in the other (ipsilateral to the non-deviated eye). Furthermore this asymmetrical organization prevents the establishment of a unifying representation of the two visual hemifields. As a general rule, we suggest that crossed and uncrossed retino-geniculo-cortical pathways contribute successively to the development of the callosal maps in visual cortex. PMID:22275883
Cusack, Lynette; Smith, Morgan; Hegney, Desley; Rees, Clare S.; Breen, Lauren J.; Witt, Regina R.; Rogers, Cath; Williams, Allison; Cross, Wendy; Cheung, Kin
2016-01-01
Building nurses' resilience to complex and stressful practice environments is necessary to keep skilled nurses in the workplace and ensuring safe patient care. A unified theoretical framework titled Health Services Workplace Environmental Resilience Model (HSWERM), is presented to explain the environmental factors in the workplace that promote nurses' resilience. The framework builds on a previously-published theoretical model of individual resilience, which identified the key constructs of psychological resilience as self-efficacy, coping and mindfulness, but did not examine environmental factors in the workplace that promote nurses' resilience. This unified theoretical framework was developed using a literary synthesis drawing on data from international studies and literature reviews on the nursing workforce in hospitals. The most frequent workplace environmental factors were identified, extracted and clustered in alignment with key constructs for psychological resilience. Six major organizational concepts emerged that related to a positive resilience-building workplace and formed the foundation of the theoretical model. Three concepts related to nursing staff support (professional, practice, personal) and three related to nursing staff development (professional, practice, personal) within the workplace environment. The unified theoretical model incorporates these concepts within the workplace context, linking to the nurse, and then impacting on personal resilience and workplace outcomes, and its use has the potential to increase staff retention and quality of patient care. PMID:27242567
Stam, Henderikus J.
2015-01-01
The search for a so-called unified or integrated theory has long served as a goal for some psychologists, even if the search is often implicit. But if the established sciences do not have an explicitly unified set of theories, then why should psychology? After examining this question again I argue that psychology is in fact reasonably unified around its methods and its commitment to functional explanations, an indeterminate functionalism. The question of the place of the neurosciences in this framework is complex. On the one hand, the neuroscientific project will not likely renew and synthesize the disparate arms of psychology. On the other hand, their reformulation of what it means to be human will exert an influence in multiple ways. One way to capture that influence is to conceptualize the brain in terms of a technology that we interact with in a manner that we do not yet fully understand. In this way we maintain both a distance from neuro-reductionism and refrain from committing to an unfettered subjectivity. PMID:26500571
NASA Astrophysics Data System (ADS)
Abdi, Daniel S.; Giraldo, Francis X.
2016-09-01
A unified approach for the numerical solution of the 3D hyperbolic Euler equations using high order methods, namely continuous Galerkin (CG) and discontinuous Galerkin (DG) methods, is presented. First, we examine how classical CG that uses a global storage scheme can be constructed within the DG framework using constraint imposition techniques commonly used in the finite element literature. Then, we implement and test a simplified version in the Non-hydrostatic Unified Model of the Atmosphere (NUMA) for the case of explicit time integration and a diagonal mass matrix. Constructing CG within the DG framework allows CG to benefit from the desirable properties of DG such as, easier hp-refinement, better stability etc. Moreover, this representation allows for regional mixing of CG and DG depending on the flow regime in an area. The different flavors of CG and DG in the unified implementation are then tested for accuracy and performance using a suite of benchmark problems representative of cloud-resolving scale, meso-scale and global-scale atmospheric dynamics. The value of our unified approach is that we are able to show how to carry both CG and DG methods within the same code and also offer a simple recipe for modifying an existing CG code to DG and vice versa.
U.S. History Framework for the 2010 National Assessment of Educational Progress
ERIC Educational Resources Information Center
National Assessment Governing Board, 2009
2009-01-01
This framework identifies the main ideas, major events, key individuals, and unifying themes of American history as a basis for preparing the 2010 assessment. The framework recognizes that U.S. history includes powerful ideas, common and diverse traditions, economic developments, technological and scientific innovations, philosophical debates,…
Applying Laban's Movement Framework in Elementary Physical Education
ERIC Educational Resources Information Center
Langton, Terence W.
2007-01-01
This article recommends raising the bar in elementary physical education by using Laban's movement framework to develop curriculum content in the areas of games, gymnastics, and dance (with physical fitness concepts blended in) in order to help students achieve the NASPE content standards. The movement framework can permeate and unify an…
Sheth, Bhavin R.; Young, Ryan
2016-01-01
Evidence is strong that the visual pathway is segregated into two distinct streams—ventral and dorsal. Two proposals theorize that the pathways are segregated in function: The ventral stream processes information about object identity, whereas the dorsal stream, according to one model, processes information about either object location, and according to another, is responsible in executing movements under visual control. The models are influential; however recent experimental evidence challenges them, e.g., the ventral stream is not solely responsible for object recognition; conversely, its function is not strictly limited to object vision; the dorsal stream is not responsible by itself for spatial vision or visuomotor control; conversely, its function extends beyond vision or visuomotor control. In their place, we suggest a robust dichotomy consisting of a ventral stream selectively sampling high-resolution/focal spaces, and a dorsal stream sampling nearly all of space with reduced foveal bias. The proposal hews closely to the theme of embodied cognition: Function arises as a consequence of an extant sensory underpinning. A continuous, not sharp, segregation based on function emerges, and carries with it an undercurrent of an exploitation-exploration dichotomy. Under this interpretation, cells of the ventral stream, which individually have more punctate receptive fields that generally include the fovea or parafovea, provide detailed information about object shapes and features and lead to the systematic exploitation of said information; cells of the dorsal stream, which individually have large receptive fields, contribute to visuospatial perception, provide information about the presence/absence of salient objects and their locations for novel exploration and subsequent exploitation by the ventral stream or, under certain conditions, the dorsal stream. We leverage the dichotomy to unify neuropsychological cases under a common umbrella, account for the increased prevalence of multisensory integration in the dorsal stream under a Bayesian framework, predict conditions under which object recognition utilizes the ventral or dorsal stream, and explain why cells of the dorsal stream drive sensorimotor control and motion processing and have poorer feature selectivity. Finally, the model speculates on a dynamic interaction between the two streams that underscores a unified, seamless perception. Existing theories are subsumed under our proposal. PMID:27920670
Sheth, Bhavin R; Young, Ryan
2016-01-01
Evidence is strong that the visual pathway is segregated into two distinct streams-ventral and dorsal. Two proposals theorize that the pathways are segregated in function: The ventral stream processes information about object identity, whereas the dorsal stream, according to one model, processes information about either object location, and according to another, is responsible in executing movements under visual control. The models are influential; however recent experimental evidence challenges them, e.g., the ventral stream is not solely responsible for object recognition; conversely, its function is not strictly limited to object vision; the dorsal stream is not responsible by itself for spatial vision or visuomotor control; conversely, its function extends beyond vision or visuomotor control. In their place, we suggest a robust dichotomy consisting of a ventral stream selectively sampling high-resolution/ focal spaces, and a dorsal stream sampling nearly all of space with reduced foveal bias. The proposal hews closely to the theme of embodied cognition: Function arises as a consequence of an extant sensory underpinning. A continuous, not sharp, segregation based on function emerges, and carries with it an undercurrent of an exploitation-exploration dichotomy. Under this interpretation, cells of the ventral stream, which individually have more punctate receptive fields that generally include the fovea or parafovea, provide detailed information about object shapes and features and lead to the systematic exploitation of said information; cells of the dorsal stream, which individually have large receptive fields, contribute to visuospatial perception, provide information about the presence/absence of salient objects and their locations for novel exploration and subsequent exploitation by the ventral stream or, under certain conditions, the dorsal stream. We leverage the dichotomy to unify neuropsychological cases under a common umbrella, account for the increased prevalence of multisensory integration in the dorsal stream under a Bayesian framework, predict conditions under which object recognition utilizes the ventral or dorsal stream, and explain why cells of the dorsal stream drive sensorimotor control and motion processing and have poorer feature selectivity. Finally, the model speculates on a dynamic interaction between the two streams that underscores a unified, seamless perception. Existing theories are subsumed under our proposal.
NASA Astrophysics Data System (ADS)
Keane, Tommy P.; Cahill, Nathan D.; Tarduno, John A.; Jacobs, Robert A.; Pelz, Jeff B.
2014-02-01
Mobile eye-tracking provides the fairly unique opportunity to record and elucidate cognition in action. In our research, we are searching for patterns in, and distinctions between, the visual-search performance of experts and novices in the geo-sciences. Traveling to regions resultant from various geological processes as part of an introductory field studies course in geology, we record the prima facie gaze patterns of experts and novices when they are asked to determine the modes of geological activity that have formed the scene-view presented to them. Recording eye video and scene video in natural settings generates complex imagery that requires advanced applications of computer vision research to generate registrations and mappings between the views of separate observers. By developing such mappings, we could then place many observers into a single mathematical space where we can spatio-temporally analyze inter- and intra-subject fixations, saccades, and head motions. While working towards perfecting these mappings, we developed an updated experiment setup that allowed us to statistically analyze intra-subject eye-movement events without the need for a common domain. Through such analyses we are finding statistical differences between novices and experts in these visual-search tasks. In the course of this research we have developed a unified, open-source, software framework for processing, visualization, and interaction of mobile eye-tracking and high-resolution panoramic imagery.
Surfing a spike wave down the ventral stream.
VanRullen, Rufin; Thorpe, Simon J
2002-10-01
Numerous theories of neural processing, often motivated by experimental observations, have explored the computational properties of neural codes based on the absolute or relative timing of spikes in spike trains. Spiking neuron models and theories however, as well as their experimental counterparts, have generally been limited to the simulation or observation of isolated neurons, isolated spike trains, or reduced neural populations. Such theories would therefore seem inappropriate to capture the properties of a neural code relying on temporal spike patterns distributed across large neuronal populations. Here we report a range of computer simulations and theoretical considerations that were designed to explore the possibilities of one such code and its relevance for visual processing. In a unified framework where the relation between stimulus saliency and spike relative timing plays the central role, we describe how the ventral stream of the visual system could process natural input scenes and extract meaningful information, both rapidly and reliably. The first wave of spikes generated in the retina in response to a visual stimulation carries information explicitly in its spatio-temporal structure: the most salient information is represented by the first spikes over the population. This spike wave, propagating through a hierarchy of visual areas, is regenerated at each processing stage, where its temporal structure can be modified by (i). the selectivity of the cortical neurons, (ii). lateral interactions and (iii). top-down attentional influences from higher order cortical areas. The resulting model could account for the remarkable efficiency and rapidity of processing observed in the primate visual system.
Spiegel, Daniel P; Reynaud, Alexandre; Ruiz, Tatiana; Laguë-Beauvais, Maude; Hess, Robert; Farivar, Reza
2016-05-01
Vision is disrupted by traumatic brain injury (TBI), with vision-related complaints being amongst the most common in this population. Based on the neural responses of early visual cortical areas, injury to the visual cortex would be predicted to affect both 1(st) order and 2(nd) order contrast sensitivity functions (CSFs)-the height and/or the cut-off of the CSF are expected to be affected by TBI. Previous studies have reported disruptions only in 2(nd) order contrast sensitivity, but using a narrow range of parameters and divergent methodologies-no study has characterized the effect of TBI on the full CSF for both 1(st) and 2(nd) order stimuli. Such information is needed to properly understand the effect of TBI on contrast perception, which underlies all visual processing. Using a unified framework based on the quick contrast sensitivity function, we measured full CSFs for static and dynamic 1(st) and 2(nd) order stimuli. Our results provide a unique dataset showing alterations in sensitivity for both 1(st) and 2(nd) order visual stimuli. In particular, we show that TBI patients have increased sensitivity for 1(st) order motion stimuli and decreased sensitivity to orientation-defined and contrast-defined 2(nd) order stimuli. In addition, our data suggest that TBI patients' sensitivity for both 1(st) order stimuli and 2(nd) order contrast-defined stimuli is shifted towards higher spatial frequencies. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
NASA Technical Reports Server (NTRS)
Arnold, Steven M.; Bednarcyk, Brett A.; Hussain, Aquila; Katiyar, Vivek
2010-01-01
A unified framework is presented that enables coupled multiscale analysis of composite structures and associated graphical pre- and postprocessing within the Abaqus/CAE environment. The recently developed, free, Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software couples NASA's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with Abaqus/Standard and Abaqus/Explicit to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. The Graphical User Interfaces (FEAMAC-Pre and FEAMAC-Post), developed through collaboration between SIMULIA Erie and the NASA Glenn Research Center, enable users to employ a new FEAMAC module within Abaqus/CAE that provides access to the composite microscale. FEA IAC-Pre is used to define and store constituent material properties, set-up and store composite repeating unit cells, and assign composite materials as sections with all data being stored within the CAE database. Likewise FEAMAC-Post enables multiscale field quantity visualization (contour plots, X-Y plots), with point and click access to the microscale i.e., fiber and matrix fields).
Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H. L.; Onami, Shuichi
2015-01-01
Motivation: Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. Results: We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. Availability and implementation: A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Contact: sonami@riken.jp Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:25414366
Kyoda, Koji; Tohsato, Yukako; Ho, Kenneth H L; Onami, Shuichi
2015-04-01
Recent progress in live-cell imaging and modeling techniques has resulted in generation of a large amount of quantitative data (from experimental measurements and computer simulations) on spatiotemporal dynamics of biological objects such as molecules, cells and organisms. Although many research groups have independently dedicated their efforts to developing software tools for visualizing and analyzing these data, these tools are often not compatible with each other because of different data formats. We developed an open unified format, Biological Dynamics Markup Language (BDML; current version: 0.2), which provides a basic framework for representing quantitative biological dynamics data for objects ranging from molecules to cells to organisms. BDML is based on Extensible Markup Language (XML). Its advantages are machine and human readability and extensibility. BDML will improve the efficiency of development and evaluation of software tools for data visualization and analysis. A specification and a schema file for BDML are freely available online at http://ssbd.qbic.riken.jp/bdml/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.
NASA Astrophysics Data System (ADS)
Rubin, D.; Aldering, G.; Barbary, K.; Boone, K.; Chappell, G.; Currie, M.; Deustua, S.; Fagrelius, P.; Fruchter, A.; Hayden, B.; Lidman, C.; Nordin, J.; Perlmutter, S.; Saunders, C.; Sofiatti, C.; Supernova Cosmology Project, The
2015-11-01
While recent supernova (SN) cosmology research has benefited from improved measurements, current analysis approaches are not statistically optimal and will prove insufficient for future surveys. This paper discusses the limitations of current SN cosmological analyses in treating outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations. We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects. We apply the framework to real SN observations and demonstrate smaller statistical and systematic uncertainties. We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way. This analysis was primarily performed blinded, in that the basic framework was first validated on simulated data before transitioning to real data. We also discuss possible extensions of the method.
A Framework to Understand Extreme Space Weather Event Probability.
Jonas, Seth; Fronczyk, Kassandra; Pratt, Lucas M
2018-03-12
An extreme space weather event has the potential to disrupt or damage infrastructure systems and technologies that many societies rely on for economic and social well-being. Space weather events occur regularly, but extreme events are less frequent, with a small number of historical examples over the last 160 years. During the past decade, published works have (1) examined the physical characteristics of the extreme historical events and (2) discussed the probability or return rate of select extreme geomagnetic disturbances, including the 1859 Carrington event. Here we present initial findings on a unified framework approach to visualize space weather event probability, using a Bayesian model average, in the context of historical extreme events. We present disturbance storm time (Dst) probability (a proxy for geomagnetic disturbance intensity) across multiple return periods and discuss parameters of interest to policymakers and planners in the context of past extreme space weather events. We discuss the current state of these analyses, their utility to policymakers and planners, the current limitations when compared to other hazards, and several gaps that need to be filled to enhance space weather risk assessments. © 2018 Society for Risk Analysis.
Sheldon Glashow, the Electroweak Theory, and the Grand Unified Theory
] 'Glashow shared the 1979 Nobel Prize for physics with Steven Weinberg and Abdus Salam for unifying the particle physics and provides a framework for understanding how the early universe evolved and how the our universe came into being," says Lawrence R. Sulak, chairman of the Boston University physics
"UNICERT," or: Towards the Development of a Unified Language Certificate for German Universities.
ERIC Educational Resources Information Center
Voss, Bernd
The standardization of second language proficiency levels for university students in Germany is discussed. Problems with the current system, in which each university has developed its own program of study and proficiency certification, are examined and a framework for development of a unified language certificate for all universities is outlined.…
Crupi, Vincenzo; Nelson, Jonathan D; Meder, Björn; Cevolani, Gustavo; Tentori, Katya
2018-06-17
Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma-Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information-theoretic formalism. Copyright © 2018 Cognitive Science Society, Inc.
A unified framework for heat and mass transport at the atomic scale
NASA Astrophysics Data System (ADS)
Ponga, Mauricio; Sun, Dingyi
2018-04-01
We present a unified framework to simulate heat and mass transport in systems of particles. The proposed framework is based on kinematic mean field theory and uses a phenomenological master equation to compute effective transport rates between particles without the need to evaluate operators. We exploit this advantage and apply the model to simulate transport phenomena at the nanoscale. We demonstrate that, when calibrated to experimentally-measured transport coefficients, the model can accurately predict transient and steady state temperature and concentration profiles even in scenarios where the length of the device is comparable to the mean free path of the carriers. Through several example applications, we demonstrate the validity of our model for all classes of materials, including ones that, until now, would have been outside the domain of computational feasibility.
A unified theoretical framework for mapping models for the multi-state Hamiltonian.
Liu, Jian
2016-11-28
We propose a new unified theoretical framework to construct equivalent representations of the multi-state Hamiltonian operator and present several approaches for the mapping onto the Cartesian phase space. After mapping an F-dimensional Hamiltonian onto an F+1 dimensional space, creation and annihilation operators are defined such that the F+1 dimensional space is complete for any combined excitation. Commutation and anti-commutation relations are then naturally derived, which show that the underlying degrees of freedom are neither bosons nor fermions. This sets the scene for developing equivalent expressions of the Hamiltonian operator in quantum mechanics and their classical/semiclassical counterparts. Six mapping models are presented as examples. The framework also offers a novel way to derive such as the well-known Meyer-Miller model.
ERIC Educational Resources Information Center
Partnership for 21st Century Skills, 2009
2009-01-01
To help practitioners integrate skills into the teaching of core academic subjects, the Partnership for 21st Century Skills has developed a unified, collective vision for learning known as the Framework for 21st Century Learning. This Framework describes the skills, knowledge and expertise students must master to succeed in work and life; it is a…
Toward a Unified Validation Framework in Mixed Methods Research
ERIC Educational Resources Information Center
Dellinger, Amy B.; Leech, Nancy L.
2007-01-01
The primary purpose of this article is to further discussions of validity in mixed methods research by introducing a validation framework to guide thinking about validity in this area. To justify the use of this framework, the authors discuss traditional terminology and validity criteria for quantitative and qualitative research, as well as…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang Yinan; Shi Handuo; Xiong Zhaoxi
We present a unified universal quantum cloning machine, which combines several different existing universal cloning machines together, including the asymmetric case. In this unified framework, the identical pure states are projected equally into each copy initially constituted by input and one half of the maximally entangled states. We show explicitly that the output states of those universal cloning machines are the same. One importance of this unified cloning machine is that the cloning procession is always the symmetric projection, which reduces dramatically the difficulties for implementation. Also, it is found that this unified cloning machine can be directly modified tomore » the general asymmetric case. Besides the global fidelity and the single-copy fidelity, we also present all possible arbitrary-copy fidelities.« less
[Arabian food pyramid: unified framework for nutritional health messages].
Shokr, Adel M
2008-01-01
There are several ways to present nutritional health messages, particularly pyramidic indices, but they have many deficiencies such as lack of agreement on a unified or clear methodology for food grouping and ignoring nutritional group inter-relation and integration. This causes confusion for health educators and target individuals. This paper presents an Arabian food pyramid that aims to unify the bases of nutritional health messages, bringing together the function, contents, source and nutritional group servings and indicating the inter-relation and integration of nutritional groups. This provides comprehensive, integrated, simple and flexible health messages.
Jerath, Ravinder; Crawford, Molly W.; Barnes, Vernon A.
2015-01-01
The Global Workspace Theory and Information Integration Theory are two of the most currently accepted consciousness models; however, these models do not address many aspects of conscious experience. We compare these models to our previously proposed consciousness model in which the thalamus fills-in processed sensory information from corticothalamic feedback loops within a proposed 3D default space, resulting in the recreation of the internal and external worlds within the mind. This 3D default space is composed of all cells of the body, which communicate via gap junctions and electrical potentials to create this unified space. We use 3D illustrations to explain how both visual and non-visual sensory information may be filled-in within this dynamic space, creating a unified seamless conscious experience. This neural sensory memory space is likely generated by baseline neural oscillatory activity from the default mode network, other salient networks, brainstem, and reticular activating system. PMID:26379573
Using telephony data to facilitate discovery of clinical workflows.
Rucker, Donald W
2017-04-19
Discovery of clinical workflows to target for redesign using methods such as Lean and Six Sigma is difficult. VoIP telephone call pattern analysis may complement direct observation and EMR-based tools in understanding clinical workflows at the enterprise level by allowing visualization of institutional telecommunications activity. To build an analytic framework mapping repetitive and high-volume telephone call patterns in a large medical center to their associated clinical units using an enterprise unified communications server log file and to support visualization of specific call patterns using graphical networks. Consecutive call detail records from the medical center's unified communications server were parsed to cross-correlate telephone call patterns and map associated phone numbers to a cost center dictionary. Hashed data structures were built to allow construction of edge and node files representing high volume call patterns for display with an open source graph network tool. Summary statistics for an analysis of exactly one week's call detail records at a large academic medical center showed that 912,386 calls were placed with a total duration of 23,186 hours. Approximately half of all calling called number pairs had an average call duration under 60 seconds and of these the average call duration was 27 seconds. Cross-correlation of phone calls identified by clinical cost center can be used to generate graphical displays of clinical enterprise communications. Many calls are short. The compact data transfers within short calls may serve as automation or re-design targets. The large absolute amount of time medical center employees were engaged in VoIP telecommunications suggests that analysis of telephone call patterns may offer additional insights into core clinical workflows.
A Computational framework for telemedicine.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Foster, I.; von Laszewski, G.; Thiruvathukal, G. K.
1998-07-01
Emerging telemedicine applications require the ability to exploit diverse and geographically distributed resources. Highspeed networks are used to integrate advanced visualization devices, sophisticated instruments, large databases, archival storage devices, PCs, workstations, and supercomputers. This form of telemedical environment is similar to networked virtual supercomputers, also known as metacomputers. Metacomputers are already being used in many scientific application areas. In this article, we analyze requirements necessary for a telemedical computing infrastructure and compare them with requirements found in a typical metacomputing environment. We will show that metacomputing environments can be used to enable a more powerful and unified computational infrastructure formore » telemedicine. The Globus metacomputing toolkit can provide the necessary low level mechanisms to enable a large scale telemedical infrastructure. The Globus toolkit components are designed in a modular fashion and can be extended to support the specific requirements for telemedicine.« less
Visual management of large scale data mining projects.
Shah, I; Hunter, L
2000-01-01
This paper describes a unified framework for visualizing the preparations for, and results of, hundreds of machine learning experiments. These experiments were designed to improve the accuracy of enzyme functional predictions from sequence, and in many cases were successful. Our system provides graphical user interfaces for defining and exploring training datasets and various representational alternatives, for inspecting the hypotheses induced by various types of learning algorithms, for visualizing the global results, and for inspecting in detail results for specific training sets (functions) and examples (proteins). The visualization tools serve as a navigational aid through a large amount of sequence data and induced knowledge. They provided significant help in understanding both the significance and the underlying biological explanations of our successes and failures. Using these visualizations it was possible to efficiently identify weaknesses of the modular sequence representations and induction algorithms which suggest better learning strategies. The context in which our data mining visualization toolkit was developed was the problem of accurately predicting enzyme function from protein sequence data. Previous work demonstrated that approximately 6% of enzyme protein sequences are likely to be assigned incorrect functions on the basis of sequence similarity alone. In order to test the hypothesis that more detailed sequence analysis using machine learning techniques and modular domain representations could address many of these failures, we designed a series of more than 250 experiments using information-theoretic decision tree induction and naive Bayesian learning on local sequence domain representations of problematic enzyme function classes. In more than half of these cases, our methods were able to perfectly discriminate among various possible functions of similar sequences. We developed and tested our visualization techniques on this application.
Collusion-resistant multimedia fingerprinting: a unified framework
NASA Astrophysics Data System (ADS)
Wu, Min; Trappe, Wade; Wang, Z. Jane; Liu, K. J. Ray
2004-06-01
Digital fingerprints are unique labels inserted in different copies of the same content before distribution. Each digital fingerprint is assigned to an inteded recipient, and can be used to trace the culprits who use their content for unintended purposes. Attacks mounted by multiple users, known as collusion attacks, provide a cost-effective method for attenuating the identifying fingerprint from each coluder, thus collusion poses a reeal challenge to protect the digital media data and enforce usage policies. This paper examines a few major design methodologies for collusion-resistant fingerprinting of multimedia, and presents a unified framework that helps highlight the common issues and the uniqueness of different fingerprinting techniques.
A development framework for semantically interoperable health information systems.
Lopez, Diego M; Blobel, Bernd G M E
2009-02-01
Semantic interoperability is a basic challenge to be met for new generations of distributed, communicating and co-operating health information systems (HIS) enabling shared care and e-Health. Analysis, design, implementation and maintenance of such systems and intrinsic architectures have to follow a unified development methodology. The Generic Component Model (GCM) is used as a framework for modeling any system to evaluate and harmonize state of the art architecture development approaches and standards for health information systems as well as to derive a coherent architecture development framework for sustainable, semantically interoperable HIS and their components. The proposed methodology is based on the Rational Unified Process (RUP), taking advantage of its flexibility to be configured for integrating other architectural approaches such as Service-Oriented Architecture (SOA), Model-Driven Architecture (MDA), ISO 10746, and HL7 Development Framework (HDF). Existing architectural approaches have been analyzed, compared and finally harmonized towards an architecture development framework for advanced health information systems. Starting with the requirements for semantic interoperability derived from paradigm changes for health information systems, and supported in formal software process engineering methods, an appropriate development framework for semantically interoperable HIS has been provided. The usability of the framework has been exemplified in a public health scenario.
Rosenfeld, Daniel L; Burrow, Anthony L
2017-05-01
By departing from social norms regarding food behaviors, vegetarians acquire membership in a distinct social group and can develop a salient vegetarian identity. However, vegetarian identities are diverse, multidimensional, and unique to each individual. Much research has identified fundamental psychological aspects of vegetarianism, and an identity framework that unifies these findings into common constructs and conceptually defines variables is needed. Integrating psychological theories of identity with research on food choices and vegetarianism, this paper proposes a conceptual model for studying vegetarianism: The Unified Model of Vegetarian Identity (UMVI). The UMVI encompasses ten dimensions-organized into three levels (contextual, internalized, and externalized)-that capture the role of vegetarianism in an individual's self-concept. Contextual dimensions situate vegetarianism within contexts; internalized dimensions outline self-evaluations; and externalized dimensions describe enactments of identity through behavior. Together, these dimensions form a coherent vegetarian identity, characterizing one's thoughts, feelings, and behaviors regarding being vegetarian. By unifying dimensions that capture psychological constructs universally, the UMVI can prevent discrepancies in operationalization, capture the inherent diversity of vegetarian identities, and enable future research to generate greater insight into how people understand themselves and their food choices. Copyright © 2017 Elsevier Ltd. All rights reserved.
A Unified Theoretical Framework for Cognitive Sequencing.
Savalia, Tejas; Shukla, Anuj; Bapi, Raju S
2016-01-01
The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks.
A Unified Theoretical Framework for Cognitive Sequencing
Savalia, Tejas; Shukla, Anuj; Bapi, Raju S.
2016-01-01
The capacity to sequence information is central to human performance. Sequencing ability forms the foundation stone for higher order cognition related to language and goal-directed planning. Information related to the order of items, their timing, chunking and hierarchical organization are important aspects in sequencing. Past research on sequencing has emphasized two distinct and independent dichotomies: implicit vs. explicit and goal-directed vs. habits. We propose a theoretical framework unifying these two streams. Our proposal relies on brain's ability to implicitly extract statistical regularities from the stream of stimuli and with attentional engagement organizing sequences explicitly and hierarchically. Similarly, sequences that need to be assembled purposively to accomplish a goal require engagement of attentional processes. With repetition, these goal-directed plans become habits with concomitant disengagement of attention. Thus, attention and awareness play a crucial role in the implicit-to-explicit transition as well as in how goal-directed plans become automatic habits. Cortico-subcortical loops basal ganglia-frontal cortex and hippocampus-frontal cortex loops mediate the transition process. We show how the computational principles of model-free and model-based learning paradigms, along with a pivotal role for attention and awareness, offer a unifying framework for these two dichotomies. Based on this framework, we make testable predictions related to the potential influence of response-to-stimulus interval (RSI) on developing awareness in implicit learning tasks. PMID:27917146
Stenneken, Prisca; Egetemeir, Johanna; Schulte-Körne, Gerd; Müller, Hermann J; Schneider, Werner X; Finke, Kathrin
2011-10-01
The cognitive causes as well as the neurological and genetic basis of developmental dyslexia, a complex disorder of written language acquisition, are intensely discussed with regard to multiple-deficit models. Accumulating evidence has revealed dyslexics' impairments in a variety of tasks requiring visual attention. The heterogeneity of these experimental results, however, points to the need for measures that are sufficiently sensitive to differentiate between impaired and preserved attentional components within a unified framework. This first parameter-based group study of attentional components in developmental dyslexia addresses potentially altered attentional components that have recently been associated with parietal dysfunctions in dyslexia. We aimed to isolate the general attentional resources that might underlie reduced span performance, i.e., either a deficient working memory storage capacity, or a slowing in visual perceptual processing speed, or both. Furthermore, by analysing attentional selectivity in dyslexia, we addressed a potential lateralized abnormality of visual attention, i.e., a previously suggested rightward spatial deviation compared to normal readers. We investigated a group of high-achieving young adults with persisting dyslexia and matched normal readers in an experimental whole report and a partial report of briefly presented letter arrays. Possible deviations in the parametric values of the dyslexic compared to the control group were taken as markers for the underlying deficit. The dyslexic group showed a striking reduction in perceptual processing speed (by 26% compared to controls) while their working memory storage capacity was in the normal range. In addition, a spatial deviation of attentional weighting compared to the control group was confirmed in dyslexic readers, which was larger in participants with a more severe dyslexic disorder. In general, the present study supports the relevance of perceptual processing speed in disorders of written language acquisition and demonstrates that the parametric assessment provides a suitable tool for specifying the underlying deficit within a unitary framework. Copyright © 2011 Elsevier Ltd. All rights reserved.
The Pursuit of a "Better" Explanation as an Organizing Framework for Science Teaching and Learning
ERIC Educational Resources Information Center
Papadouris, Nicos; Vokos, Stamatis; Constantinou, Constantinos P.
2018-01-01
This article seeks to make the case for the pursuit of a "better" explanation being a productive organizing framework for science teaching and learning. Underlying this position is the idea that this framework allows promoting, in a unified manner, facility with the scientific practice of constructing explanations, appreciation of its…
Space-Time Processing for Tactical Mobile Ad Hoc Networks
2008-08-01
vision for multiple concurrent communication settings, i.e., a many-to-many framework where multi-packet transmissions (MPTs) and multi-packet...modelling framework of capacity-delay tradeoffs We have introduced the first unified modeling framework for the computation of fundamental limits o We...dalities in wireless n twor i-packet modelling framework to account for the use of m lti-packet reception (MPR) f ad hoc networks with MPT under
Unified formalism for higher order non-autonomous dynamical systems
NASA Astrophysics Data System (ADS)
Prieto-Martínez, Pedro Daniel; Román-Roy, Narciso
2012-03-01
This work is devoted to giving a geometric framework for describing higher order non-autonomous mechanical systems. The starting point is to extend the Lagrangian-Hamiltonian unified formalism of Skinner and Rusk for these kinds of systems, generalizing previous developments for higher order autonomous mechanical systems and first-order non-autonomous mechanical systems. Then, we use this unified formulation to derive the standard Lagrangian and Hamiltonian formalisms, including the Legendre-Ostrogradsky map and the Euler-Lagrange and the Hamilton equations, both for regular and singular systems. As applications of our model, two examples of regular and singular physical systems are studied.
Colaborated Architechture Framework for Composition UML 2.0 in Zachman Framework
NASA Astrophysics Data System (ADS)
Hermawan; Hastarista, Fika
2016-01-01
Zachman Framework (ZF) is the framework of enterprise architechture that most widely adopted in the Enterprise Information System (EIS) development. In this study, has been developed Colaborated Architechture Framework (CAF) to collaborate ZF with Unified Modeling Language (UML) 2.0 modeling. The CAF provides the composition of ZF matrix that each cell is consist of the Model Driven architechture (MDA) from the various UML models and many Software Requirement Specification (SRS) documents. Implementation of this modeling is used to develops Enterprise Resource Planning (ERP). Because ERP have a coverage of applications in large numbers and complexly relations, it is necessary to use Agile Model Driven Design (AMDD) approach as an advanced method to transforms MDA into components of application modules with efficiently and accurately. Finally, through the using of the CAF, give good achievement in fullfilment the needs from all stakeholders that are involved in the overall process stage of Rational Unified Process (RUP), and also obtaining a high satisfaction to fullfiled the functionality features of the ERP software in PT. Iglas (Persero) Gresik.
Family Systems Theory: A Unifying Framework for Codependence.
ERIC Educational Resources Information Center
Prest, Layne A.; Protinsky, Howard
1993-01-01
Considers addictions and construct of codependence. Offers critical review and synthesis of codependency literature, along with an intergenerational family systems framework for conceptualizing the relationship of the dysfunctional family to the construct of codependence. Presents theoretical basis for systemic clinical work and research in this…
[Research on tumor information grid framework].
Zhang, Haowei; Qin, Zhu; Liu, Ying; Tan, Jianghao; Cao, Haitao; Chen, Youping; Zhang, Ke; Ding, Yuqing
2013-10-01
In order to realize tumor disease information sharing and unified management, we utilized grid technology to make the data and software resources which distributed in various medical institutions for effective integration so that we could make the heterogeneous resources consistent and interoperable in both semantics and syntax aspects. This article describes the tumor grid framework, the type of the service being packaged in Web Service Description Language (WSDL) and extensible markup language schemas definition (XSD), the client use the serialized document to operate the distributed resources. The service objects could be built by Unified Modeling Language (UML) as middle ware to create application programming interface. All of the grid resources are registered in the index and released in the form of Web Services based on Web Services Resource Framework (WSRF). Using the system we can build a multi-center, large sample and networking tumor disease resource sharing framework to improve the level of development in medical scientific research institutions and the patient's quality of life.
Kwok, T; Smith, K A
2000-09-01
The aim of this paper is to study both the theoretical and experimental properties of chaotic neural network (CNN) models for solving combinatorial optimization problems. Previously we have proposed a unifying framework which encompasses the three main model types, namely, Chen and Aihara's chaotic simulated annealing (CSA) with decaying self-coupling, Wang and Smith's CSA with decaying timestep, and the Hopfield network with chaotic noise. Each of these models can be represented as a special case under the framework for certain conditions. This paper combines the framework with experimental results to provide new insights into the effect of the chaotic neurodynamics of each model. By solving the N-queen problem of various sizes with computer simulations, the CNN models are compared in different parameter spaces, with optimization performance measured in terms of feasibility, efficiency, robustness and scalability. Furthermore, characteristic chaotic neurodynamics crucial to effective optimization are identified, together with a guide to choosing the corresponding model parameters.
Torfs, Elena; Martí, M Carmen; Locatelli, Florent; Balemans, Sophie; Bürger, Raimund; Diehl, Stefan; Laurent, Julien; Vanrolleghem, Peter A; François, Pierre; Nopens, Ingmar
2017-02-01
A new perspective on the modelling of settling behaviour in water resource recovery facilities is introduced. The ultimate goal is to describe in a unified way the processes taking place both in primary settling tanks (PSTs) and secondary settling tanks (SSTs) for a more detailed operation and control. First, experimental evidence is provided, pointing out distributed particle properties (such as size, shape, density, porosity, and flocculation state) as an important common source of distributed settling behaviour in different settling unit processes and throughout different settling regimes (discrete, hindered and compression settling). Subsequently, a unified model framework that considers several particle classes is proposed in order to describe distributions in settling behaviour as well as the effect of variations in particle properties on the settling process. The result is a set of partial differential equations (PDEs) that are valid from dilute concentrations, where they correspond to discrete settling, to concentrated suspensions, where they correspond to compression settling. Consequently, these PDEs model both PSTs and SSTs.
Local coding based matching kernel method for image classification.
Song, Yan; McLoughlin, Ian Vince; Dai, Li-Rong
2014-01-01
This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel based metrics are more effective, but at the cost of greater computational complexity and increased storage requirements. We show that a unified visual matching framework can be developed to encompass both BoV and kernel based metrics, in which local kernel plays an important role between feature pairs or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends to undermine the motivation behind Euclidean metrics. Motivated by recent advances in feature coding techniques, a novel efficient local coding based matching kernel (LCMK) method is proposed. This exploits the manifold structures in Hilbert space derived from local kernels. The proposed method combines advantages of both BoV and kernel based metrics, and achieves a linear computational complexity. This enables efficient and scalable visual matching to be performed on large scale image sets. To evaluate the effectiveness of the proposed LCMK method, we conduct extensive experiments with widely used benchmark datasets, including 15-Scenes, Caltech101/256, PASCAL VOC 2007 and 2011 datasets. Experimental results confirm the effectiveness of the relatively efficient LCMK method.
A Sensemaking Visualization Tool with Military Doctrinal Elements
2008-06-01
LeadUnderstand CDR / Staff ART / Science In short, we need to develop an integrated approach for the understanding (framing) and visualizing, describing...directing, assessing, and reframing of unified operations. Staff Running Estimates t ff i i Visualize CDR / Staff ART / Science •Planning guidance...Planning guidance •Cdr ’s Intent Describe CDR / Staff ART / Science •Plans & Orders •Preparation •Plans & Orders •Preparation •Execution WF
A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Wei; Liu, Cheng; Thomas, Neil
2015-01-01
Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. Formore » left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.« less
A quasi-likelihood approach to non-negative matrix factorization
Devarajan, Karthik; Cheung, Vincent C.K.
2017-01-01
A unified approach to non-negative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proven using the Expectation-Maximization algorithm. In addition, a measure to evaluate the goodness-of-fit of the resulting factorization is described. The proposed methods allow modeling of non-linear effects via appropriate link functions and are illustrated using an application in biomedical signal processing. PMID:27348511
Groundwater modelling in decision support: reflections on a unified conceptual framework
NASA Astrophysics Data System (ADS)
Doherty, John; Simmons, Craig T.
2013-11-01
Groundwater models are commonly used as basis for environmental decision-making. There has been discussion and debate in recent times regarding the issue of model simplicity and complexity. This paper contributes to this ongoing discourse. The selection of an appropriate level of model structural and parameterization complexity is not a simple matter. Although the metrics on which such selection should be based are simple, there are many competing, and often unquantifiable, considerations which must be taken into account as these metrics are applied. A unified conceptual framework is introduced and described which is intended to underpin groundwater modelling in decision support with a direct focus on matters regarding model simplicity and complexity.
Pattern-oriented modeling of agent-based complex systems: Lessons from ecology
Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.
2005-01-01
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology
NASA Astrophysics Data System (ADS)
Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.
2005-11-01
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
A Unified Model of Geostrophic Adjustment and Frontogenesis
NASA Astrophysics Data System (ADS)
Taylor, John; Shakespeare, Callum
2013-11-01
Fronts, or regions with strong horizontal density gradients, are ubiquitous and dynamically important features of the ocean and atmosphere. In the ocean, fronts are associated with enhanced air-sea fluxes, turbulence, and biological productivity, while atmospheric fronts are associated with some of the most extreme weather events. Here, we describe a new mathematical framework for describing the formation of fronts, or frontogenesis. This framework unifies two classical problems in geophysical fluid dynamics, geostrophic adjustment and strain-driven frontogenesis, and provides a number of important extensions beyond previous efforts. The model solutions closely match numerical simulations during the early stages of frontogenesis, and provide a means to describe the development of turbulence at mature fronts.
Integrating diverse databases into an unified analysis framework: a Galaxy approach
Blankenberg, Daniel; Coraor, Nathan; Von Kuster, Gregory; Taylor, James; Nekrutenko, Anton
2011-01-01
Recent technological advances have lead to the ability to generate large amounts of data for model and non-model organisms. Whereas, in the past, there have been a relatively small number of central repositories that serve genomic data, an increasing number of distinct specialized data repositories and resources have been established. Here, we describe a generic approach that provides for the integration of a diverse spectrum of data resources into a unified analysis framework, Galaxy (http://usegalaxy.org). This approach allows the simplified coupling of external data resources with the data analysis tools available to Galaxy users, while leveraging the native data mining facilities of the external data resources. Database URL: http://usegalaxy.org PMID:21531983
Perceiving the Present and a Systematization of Illusions
ERIC Educational Resources Information Center
Changizi, Mark A.; Hsieh, Andrew; Nijhawan, Romi; Kanai, Ryota; Shimojo, Shinsuke
2008-01-01
Over the history of the study of visual perception there has been great success at discovering countless visual illusions. There has been less success in organizing the overwhelming variety of illusions into empirical generalizations (much less explaining them all via a unifying theory). Here, this article shows that it is possible to…
Putting the School Interoperability Framework to the Test
ERIC Educational Resources Information Center
Mercurius, Neil; Burton, Glenn; Hopkins, Bill; Larsen, Hans
2004-01-01
The Jurupa Unified School District in Southern California recently partnered with Microsoft, Dell and the Zone Integration Group for the implementation of a School Interoperability Framework (SIF) database repository model throughout the district (Magner 2002). A two-week project--the Integrated District Education Applications System, better known…
Generalized Multilevel Structural Equation Modeling
ERIC Educational Resources Information Center
Rabe-Hesketh, Sophia; Skrondal, Anders; Pickles, Andrew
2004-01-01
A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models (GLLAMM), combine features of generalized linear mixed models (GLMM) and structural equation models (SEM) and consist of a response model and a structural model for the latent…
ERIC Educational Resources Information Center
O'Keeffe, Shawn Edward
2013-01-01
The author developed a unified nD framework and process ontology for Building Information Modeling (BIM). The research includes a framework developed for 6D BIM, nD BIM, and nD ontology that defines the domain and sub-domain constructs for future nD BIM dimensions. The nD ontology defines the relationships of kinds within any new proposed…
Parametric models to relate spike train and LFP dynamics with neural information processing.
Banerjee, Arpan; Dean, Heather L; Pesaran, Bijan
2012-01-01
Spike trains and local field potentials (LFPs) resulting from extracellular current flows provide a substrate for neural information processing. Understanding the neural code from simultaneous spike-field recordings and subsequent decoding of information processing events will have widespread applications. One way to demonstrate an understanding of the neural code, with particular advantages for the development of applications, is to formulate a parametric statistical model of neural activity and its covariates. Here, we propose a set of parametric spike-field models (unified models) that can be used with existing decoding algorithms to reveal the timing of task or stimulus specific processing. Our proposed unified modeling framework captures the effects of two important features of information processing: time-varying stimulus-driven inputs and ongoing background activity that occurs even in the absence of environmental inputs. We have applied this framework for decoding neural latencies in simulated and experimentally recorded spike-field sessions obtained from the lateral intraparietal area (LIP) of awake, behaving monkeys performing cued look-and-reach movements to spatial targets. Using both simulated and experimental data, we find that estimates of trial-by-trial parameters are not significantly affected by the presence of ongoing background activity. However, including background activity in the unified model improves goodness of fit for predicting individual spiking events. Uncovering the relationship between the model parameters and the timing of movements offers new ways to test hypotheses about the relationship between neural activity and behavior. We obtained significant spike-field onset time correlations from single trials using a previously published data set where significantly strong correlation was only obtained through trial averaging. We also found that unified models extracted a stronger relationship between neural response latency and trial-by-trial behavioral performance than existing models of neural information processing. Our results highlight the utility of the unified modeling framework for characterizing spike-LFP recordings obtained during behavioral performance.
A unifying framework for systems modeling, control systems design, and system operation
NASA Technical Reports Server (NTRS)
Dvorak, Daniel L.; Indictor, Mark B.; Ingham, Michel D.; Rasmussen, Robert D.; Stringfellow, Margaret V.
2005-01-01
Current engineering practice in the analysis and design of large-scale multi-disciplinary control systems is typified by some form of decomposition- whether functional or physical or discipline-based-that enables multiple teams to work in parallel and in relative isolation. Too often, the resulting system after integration is an awkward marriage of different control and data mechanisms with poor end-to-end accountability. System of systems engineering, which faces this problem on a large scale, cries out for a unifying framework to guide analysis, design, and operation. This paper describes such a framework based on a state-, model-, and goal-based architecture for semi-autonomous control systems that guides analysis and modeling, shapes control system software design, and directly specifies operational intent. This paper illustrates the key concepts in the context of a large-scale, concurrent, globally distributed system of systems: NASA's proposed Array-based Deep Space Network.
Toward a unified approach to dose-response modeling in ecotoxicology.
Ritz, Christian
2010-01-01
This study reviews dose-response models that are used in ecotoxicology. The focus lies on clarification of differences and similarities between models, and as a side effect, their different guises in ecotoxicology are unravelled. A look at frequently used dose-response models reveals major discrepancies, among other things in naming conventions. Therefore, there is a need for a unified view on dose-response modeling in order to improve the understanding of it and to facilitate communication and comparison of findings across studies, thus realizing its full potential. This study attempts to establish a general framework that encompasses most dose-response models that are of interest to ecotoxicologists in practice. The framework includes commonly used models such as the log-logistic and Weibull models, but also features entire suites of models as found in various guidance documents. An outline on how the proposed framework can be implemented in statistical software systems is also provided.
Probabilistic self-organizing maps for continuous data.
Lopez-Rubio, Ezequiel
2010-10-01
The original self-organizing feature map did not define any probability distribution on the input space. However, the advantages of introducing probabilistic methodologies into self-organizing map models were soon evident. This has led to a wide range of proposals which reflect the current emergence of probabilistic approaches to computational intelligence. The underlying estimation theories behind them derive from two main lines of thought: the expectation maximization methodology and stochastic approximation methods. Here, we present a comprehensive view of the state of the art, with a unifying perspective of the involved theoretical frameworks. In particular, we examine the most commonly used continuous probability distributions, self-organization mechanisms, and learning schemes. Special emphasis is given to the connections among them and their relative advantages depending on the characteristics of the problem at hand. Furthermore, we evaluate their performance in two typical applications of self-organizing maps: classification and visualization.
Theoretical Foundation of Copernicus: A Unified System for Trajectory Design and Optimization
NASA Technical Reports Server (NTRS)
Ocampo, Cesar; Senent, Juan S.; Williams, Jacob
2010-01-01
The fundamental methods are described for the general spacecraft trajectory design and optimization software system called Copernicus. The methods rely on a unified framework that is used to model, design, and optimize spacecraft trajectories that may operate in complex gravitational force fields, use multiple propulsion systems, and involve multiple spacecraft. The trajectory model, with its associated equations of motion and maneuver models, are discussed.
Binocular coordination in response to stereoscopic stimuli
NASA Astrophysics Data System (ADS)
Liversedge, Simon P.; Holliman, Nicolas S.; Blythe, Hazel I.
2009-02-01
Humans actively explore their visual environment by moving their eyes. Precise coordination of the eyes during visual scanning underlies the experience of a unified perceptual representation and is important for the perception of depth. We report data from three psychological experiments investigating human binocular coordination during visual processing of stereoscopic stimuli.In the first experiment participants were required to read sentences that contained a stereoscopically presented target word. Half of the word was presented exclusively to one eye and half exclusively to the other eye. Eye movements were recorded and showed that saccadic targeting was uninfluenced by the stereoscopic presentation, strongly suggesting that complementary retinal stimuli are perceived as a single, unified input prior to saccade initiation. In a second eye movement experiment we presented words stereoscopically to measure Panum's Fusional Area for linguistic stimuli. In the final experiment we compared binocular coordination during saccades between simple dot stimuli under 2D, stereoscopic 3D and real 3D viewing conditions. Results showed that depth appropriate vergence movements were made during saccades and fixations to real 3D stimuli, but only during fixations on stereoscopic 3D stimuli. 2D stimuli did not induce depth vergence movements. Together, these experiments indicate that stereoscopic visual stimuli are fused when they fall within Panum's Fusional Area, and that saccade metrics are computed on the basis of a unified percept. Also, there is sensitivity to non-foveal retinal disparity in real 3D stimuli, but not in stereoscopic 3D stimuli, and the system responsible for binocular coordination responds to this during saccades as well as fixations.
Visual representation of spatiotemporal structure
NASA Astrophysics Data System (ADS)
Schill, Kerstin; Zetzsche, Christoph; Brauer, Wilfried; Eisenkolb, A.; Musto, A.
1998-07-01
The processing and representation of motion information is addressed from an integrated perspective comprising low- level signal processing properties as well as higher-level cognitive aspects. For the low-level processing of motion information we argue that a fundamental requirement is the existence of a spatio-temporal memory. Its key feature, the provision of an orthogonal relation between external time and its internal representation, is achieved by a mapping of temporal structure into a locally distributed activity distribution accessible in parallel by higher-level processing stages. This leads to a reinterpretation of the classical concept of `iconic memory' and resolves inconsistencies on ultra-short-time processing and visual masking. The spatial-temporal memory is further investigated by experiments on the perception of spatio-temporal patterns. Results on the direction discrimination of motion paths provide evidence that information about direction and location are not processed and represented independent of each other. This suggests a unified representation on an early level, in the sense that motion information is internally available in form of a spatio-temporal compound. For the higher-level representation we have developed a formal framework for the qualitative description of courses of motion that may occur with moving objects.
A Unified Framework for Monetary Theory and Policy Analysis.
ERIC Educational Resources Information Center
Lagos, Ricardo; Wright, Randall
2005-01-01
Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…
Generalizability Theory as a Unifying Framework of Measurement Reliability in Adolescent Research
ERIC Educational Resources Information Center
Fan, Xitao; Sun, Shaojing
2014-01-01
In adolescence research, the treatment of measurement reliability is often fragmented, and it is not always clear how different reliability coefficients are related. We show that generalizability theory (G-theory) is a comprehensive framework of measurement reliability, encompassing all other reliability methods (e.g., Pearson "r,"…
Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A
2018-01-01
The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs-with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the "oracle" choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance.
A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets
ERIC Educational Resources Information Center
Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.
2013-01-01
This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…
RT-18: Value of Flexibility. Phase 1
2010-09-25
an analytical framework based on sound mathematical constructs. A review of the current state-of-the-art showed that there is little unifying theory...framework that is mathematically consistent, domain independent and applicable under varying information levels. This report presents our advances in...During this period, we also explored the development of an analytical framework based on sound mathematical constructs. A review of the current state
Framework Design of Unified Cross-Authentication Based on the Fourth Platform Integrated Payment
NASA Astrophysics Data System (ADS)
Yong, Xu; Yujin, He
The essay advances a unified authentication based on the fourth integrated payment platform. The research aims at improving the compatibility of the authentication in electronic business and providing a reference for the establishment of credit system by seeking a way to carry out a standard unified authentication on a integrated payment platform. The essay introduces the concept of the forth integrated payment platform and finally put forward the whole structure and different components. The main issue of the essay is about the design of the credit system of the fourth integrated payment platform and the PKI/CA structure design.
Unified Photo Enhancement by Discovering Aesthetic Communities From Flickr.
Hong, Richang; Zhang, Luming; Tao, Dacheng
2016-03-01
Photo enhancement refers to the process of increasing the aesthetic appeal of a photo, such as changing the photo aspect ratio and spatial recomposition. It is a widely used technique in the printing industry, graphic design, and cinematography. In this paper, we propose a unified and socially aware photo enhancement framework which can leverage the experience of photographers with various aesthetic topics (e.g., portrait and landscape). We focus on photos from the image hosting site Flickr, which has 87 million users and to which more than 3.5 million photos are uploaded daily. First, a tagwise regularized topic model is proposed to describe the aesthetic topic of each Flickr user, and coherent and interpretable topics are discovered by leveraging both the visual features and tags of photos. Next, a graph is constructed to describe the similarities in aesthetic topics between the users. Noticeably, densely connected users have similar aesthetic topics, which are categorized into different communities by a dense subgraph mining algorithm. Finally, a probabilistic model is exploited to enhance the aesthetic attractiveness of a test photo by leveraging the photographic experiences of Flickr users from the corresponding communities of that photo. Paired-comparison-based user studies show that our method performs competitively on photo retargeting and recomposition. Moreover, our approach accurately detects aesthetic communities in a photo set crawled from nearly 100000 Flickr users.
Art. Elementary Curriculum Guide 1985.
ERIC Educational Resources Information Center
Alberta Dept. of Education, Edmonton.
The elementary art program level 1 (grades 1 and 2), level 2 (grades 3 and 4), and level 3 (grades 5 and 6) is a unified, sequential course which focuses on 4 major concepts of visual learning. The concepts are: reflection--the response to visual forms in nature, designed objects and artworks; depiction--the development of imagery based on…
A unified framework for building high performance DVEs
NASA Astrophysics Data System (ADS)
Lei, Kaibin; Ma, Zhixia; Xiong, Hua
2011-10-01
A unified framework for integrating PC cluster based parallel rendering with distributed virtual environments (DVEs) is presented in this paper. While various scene graphs have been proposed in DVEs, it is difficult to enable collaboration of different scene graphs. This paper proposes a technique for non-distributed scene graphs with the capability of object and event distribution. With the increase of graphics data, DVEs require more powerful rendering ability. But general scene graphs are inefficient in parallel rendering. The paper also proposes a technique to connect a DVE and a PC cluster based parallel rendering environment. A distributed multi-player video game is developed to show the interaction of different scene graphs and the parallel rendering performance on a large tiled display wall.
Unified Behavior Framework for Discrete Event Simulation Systems
2015-03-26
I would like to thank Dr. Hodson for his guidance and direction throughout the AFIT program. I also would like to thank my thesis committee members...SPA Sense-Plan-Act SSL System Service Layer TCA Task Control Architecture TRP Teleo-Reactive Program UAV Unmanned Aerial Vehicle UBF Unified Behavior...a teleo-reactive architecture [11]. Teleo-Reactive Programs ( TRPs ) are composed of a list of rules, where each has a condition and an action. When the
Evolutionary game theory meets social science: is there a unifying rule for human cooperation?
Rosas, Alejandro
2010-05-21
Evolutionary game theory has shown that human cooperation thrives in different types of social interactions with a PD structure. Models treat the cooperative strategies within the different frameworks as discrete entities and sometimes even as contenders. Whereas strong reciprocity was acclaimed as superior to classic reciprocity for its ability to defeat defectors in public goods games, recent experiments and simulations show that costly punishment fails to promote cooperation in the IR and DR games, where classic reciprocity succeeds. My aim is to show that cooperative strategies across frameworks are capable of a unified treatment, for they are governed by a common underlying rule or norm. An analysis of the reputation and action rules that govern some representative cooperative strategies both in models and in economic experiments confirms that the different frameworks share a conditional action rule and several reputation rules. The common conditional rule contains an option between costly punishment and withholding benefits that provides alternative enforcement methods against defectors. Depending on the framework, individuals can switch to the appropriate strategy and method of enforcement. The stability of human cooperation looks more promising if one mechanism controls successful strategies across frameworks. Published by Elsevier Ltd.
General System Theory: Toward a Conceptual Framework for Science and Technology Education for All.
ERIC Educational Resources Information Center
Chen, David; Stroup, Walter
1993-01-01
Suggests using general system theory as a unifying theoretical framework for science and technology education for all. Five reasons are articulated: the multidisciplinary nature of systems theory, the ability to engage complexity, the capacity to describe system dynamics, the ability to represent the relationship between microlevel and…
Making Learning Personally Meaningful: A New Framework for Relevance Research
ERIC Educational Resources Information Center
Priniski, Stacy J.; Hecht, Cameron A.; Harackiewicz, Judith M.
2018-01-01
Personal relevance goes by many names in the motivation literature, stemming from a number of theoretical frameworks. Currently these lines of research are being conducted in parallel with little synthesis across them, perhaps because there is no unifying definition of the relevance construct within which this research can be situated. In this…
Unifying Different Theories of Learning: Theoretical Framework and Empirical Evidence
ERIC Educational Resources Information Center
Phan, Huy Phuong
2008-01-01
The main aim of this research study was to test out a conceptual model encompassing the theoretical frameworks of achievement goals, study processing strategies, effort, and reflective thinking practice. In particular, it was postulated that the causal influences of achievement goals on academic performance are direct and indirect through study…
ERIC Educational Resources Information Center
MacLean, Justine; Mulholland, Rosemary; Gray, Shirley; Horrell, Andrew
2015-01-01
Background: Curriculum for Excellence, a new national policy initiative in Scottish Schools, provides a unified curricular framework for children aged 3-18. Within this framework, Physical Education (PE) now forms part of a collective alongside physical activity and sport, subsumed by the newly created curriculum area of "Health and…
Using Fault Trees to Advance Understanding of Diagnostic Errors.
Rogith, Deevakar; Iyengar, M Sriram; Singh, Hardeep
2017-11-01
Diagnostic errors annually affect at least 5% of adults in the outpatient setting in the United States. Formal analytic techniques are only infrequently used to understand them, in part because of the complexity of diagnostic processes and clinical work flows involved. In this article, diagnostic errors were modeled using fault tree analysis (FTA), a form of root cause analysis that has been successfully used in other high-complexity, high-risk contexts. How factors contributing to diagnostic errors can be systematically modeled by FTA to inform error understanding and error prevention is demonstrated. A team of three experts reviewed 10 published cases of diagnostic error and constructed fault trees. The fault trees were modeled according to currently available conceptual frameworks characterizing diagnostic error. The 10 trees were then synthesized into a single fault tree to identify common contributing factors and pathways leading to diagnostic error. FTA is a visual, structured, deductive approach that depicts the temporal sequence of events and their interactions in a formal logical hierarchy. The visual FTA enables easier understanding of causative processes and cognitive and system factors, as well as rapid identification of common pathways and interactions in a unified fashion. In addition, it enables calculation of empirical estimates for causative pathways. Thus, fault trees might provide a useful framework for both quantitative and qualitative analysis of diagnostic errors. Future directions include establishing validity and reliability by modeling a wider range of error cases, conducting quantitative evaluations, and undertaking deeper exploration of other FTA capabilities. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.
Brainerd, C J; Reyna, V F; Howe, M L
2009-10-01
One of the most extensively investigated topics in the adult memory literature, dual memory processes, has had virtually no impact on the study of early memory development. The authors remove the key obstacles to such research by formulating a trichotomous theory of recall that combines the traditional dual processes of recollection and familiarity with a reconstruction process. The theory is then embedded in a hidden Markov model that measures all 3 processes with low-burden tasks that are appropriate for even young children. These techniques are applied to a large corpus of developmental studies of recall, yielding stable findings about the emergence of dual memory processes between childhood and young adulthood and generating tests of many theoretical predictions. The techniques are extended to the study of healthy aging and to the memory sequelae of common forms of neurocognitive impairment, resulting in a theoretical framework that is unified over 4 major domains of memory research: early development, mainstream adult research, aging, and neurocognitive impairment. The techniques are also extended to recognition, creating a unified dual process framework for recall and recognition.
Pelowski, Matthew; Markey, Patrick S.; Lauring, Jon O.; Leder, Helmut
2016-01-01
The last decade has witnessed a renaissance of empirical and psychological approaches to art study, especially regarding cognitive models of art processing experience. This new emphasis on modeling has often become the basis for our theoretical understanding of human interaction with art. Models also often define areas of focus and hypotheses for new empirical research, and are increasingly important for connecting psychological theory to discussions of the brain. However, models are often made by different researchers, with quite different emphases or visual styles. Inputs and psychological outcomes may be differently considered, or can be under-reported with regards to key functional components. Thus, we may lose the major theoretical improvements and ability for comparison that can be had with models. To begin addressing this, this paper presents a theoretical assessment, comparison, and new articulation of a selection of key contemporary cognitive or information-processing-based approaches detailing the mechanisms underlying the viewing of art. We review six major models in contemporary psychological aesthetics. We in turn present redesigns of these models using a unified visual form, in some cases making additions or creating new models where none had previously existed. We also frame these approaches in respect to their targeted outputs (e.g., emotion, appraisal, physiological reaction) and their strengths within a more general framework of early, intermediate, and later processing stages. This is used as a basis for general comparison and discussion of implications and future directions for modeling, and for theoretically understanding our engagement with visual art. PMID:27199697
Helical Axis Data Visualization and Analysis of the Knee Joint Articulation.
Millán Vaquero, Ricardo Manuel; Vais, Alexander; Dean Lynch, Sean; Rzepecki, Jan; Friese, Karl-Ingo; Hurschler, Christof; Wolter, Franz-Erich
2016-09-01
We present processing methods and visualization techniques for accurately characterizing and interpreting kinematical data of flexion-extension motion of the knee joint based on helical axes. We make use of the Lie group of rigid body motions and particularly its Lie algebra for a natural representation of motion sequences. This allows to analyze and compute the finite helical axis (FHA) and instantaneous helical axis (IHA) in a unified way without redundant degrees of freedom or singularities. A polynomial fitting based on Legendre polynomials within the Lie algebra is applied to provide a smooth description of a given discrete knee motion sequence which is essential for obtaining stable instantaneous helical axes for further analysis. Moreover, this allows for an efficient overall similarity comparison across several motion sequences in order to differentiate among several cases. Our approach combines a specifically designed patient-specific three-dimensional visualization basing on the processed helical axes information and incorporating computed tomography (CT) scans for an intuitive interpretation of the axes and their geometrical relation with respect to the knee joint anatomy. In addition, in the context of the study of diseases affecting the musculoskeletal articulation, we propose to integrate the above tools into a multiscale framework for exploring related data sets distributed across multiple spatial scales. We demonstrate the utility of our methods, exemplarily processing a collection of motion sequences acquired from experimental data involving several surgery techniques. Our approach enables an accurate analysis, visualization and comparison of knee joint articulation, contributing to the evaluation and diagnosis in medical applications.
Pelowski, Matthew; Markey, Patrick S; Lauring, Jon O; Leder, Helmut
2016-01-01
The last decade has witnessed a renaissance of empirical and psychological approaches to art study, especially regarding cognitive models of art processing experience. This new emphasis on modeling has often become the basis for our theoretical understanding of human interaction with art. Models also often define areas of focus and hypotheses for new empirical research, and are increasingly important for connecting psychological theory to discussions of the brain. However, models are often made by different researchers, with quite different emphases or visual styles. Inputs and psychological outcomes may be differently considered, or can be under-reported with regards to key functional components. Thus, we may lose the major theoretical improvements and ability for comparison that can be had with models. To begin addressing this, this paper presents a theoretical assessment, comparison, and new articulation of a selection of key contemporary cognitive or information-processing-based approaches detailing the mechanisms underlying the viewing of art. We review six major models in contemporary psychological aesthetics. We in turn present redesigns of these models using a unified visual form, in some cases making additions or creating new models where none had previously existed. We also frame these approaches in respect to their targeted outputs (e.g., emotion, appraisal, physiological reaction) and their strengths within a more general framework of early, intermediate, and later processing stages. This is used as a basis for general comparison and discussion of implications and future directions for modeling, and for theoretically understanding our engagement with visual art.
NASA Astrophysics Data System (ADS)
Kuvich, Gary
2003-08-01
Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. The ability of human brain to emulate knowledge structures in the form of networks-symbolic models is found. And that means an important shift of paradigm in our knowledge about brain from neural networks to "cortical software". Symbols, predicates and grammars naturally emerge in such active multilevel hierarchical networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type decision structure created via multilevel hierarchical compression of visual information. Mid-level vision processes like clustering, perceptual grouping, separation of figure from ground, are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models works similar to frames and agents, combines learning, classification, analogy together with higher-level model-based reasoning into a single framework. Such models do not require supercomputers. Based on such principles, and using methods of Computational intelligence, an Image Understanding system can convert images into the network-symbolic knowledge models, and effectively resolve uncertainty and ambiguity, providing unifying representation for perception and cognition. That allows creating new intelligent computer vision systems for robotic and defense industries.
Tomalia, Donald A; Khanna, Shiv N
2016-02-24
Development of a central paradigm is undoubtedly the single most influential force responsible for advancing Dalton's 19th century atomic/molecular chemistry concepts to the current maturity enjoyed by traditional chemistry. A similar central dogma for guiding and unifying nanoscience has been missing. This review traces the origins, evolution, and current status of such a critical nanoperiodic concept/framework for defining and unifying nanoscience. Based on parallel efforts and a mutual consensus now shared by both chemists and physicists, a nanoperiodic/systematic framework concept has emerged. This concept is based on the well-documented existence of discrete, nanoscale collections of traditional inorganic/organic atoms referred to as hard and soft superatoms (i.e., nanoelement categories). These nanometric entities are widely recognized to exhibit nanoscale atom mimicry features reminiscent of traditional picoscale atoms. All unique superatom/nanoelement physicochemical features are derived from quantized structural control defined by six critical nanoscale design parameters (CNDPs), namely, size, shape, surface chemistry, flexibility/rigidity, architecture, and elemental composition. These CNDPs determine all intrinsic superatom properties, their combining behavior to form stoichiometric nanocompounds/assemblies as well as to exhibit nanoperiodic properties leading to new nanoperiodic rules and predictive Mendeleev-like nanoperiodic tables, and they portend possible extension of these principles to larger quantized building blocks including meta-atoms.
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view. PMID:23515240
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties observed in biological systems at different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be enough to confer intrinsic robustness in order to tolerate intrinsic parameter fluctuations, genetic robustness for buffering genetic variations, and environmental robustness for resisting environmental disturbances. With this, the phenotypic stability of biological network can be maintained, thus guaranteeing phenotype robustness. This paper presents a survey on biological systems and then develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation in systems and evolutionary biology. Further, from the unifying mathematical framework, it was discovered that the phenotype robustness criterion for biological networks at different levels relies upon intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness. When this is true, the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in systems and evolutionary biology can also be investigated through their corresponding phenotype robustness criterion from the systematic point of view.
A new view of Baryon symmetric cosmology based on grand unified theories
NASA Technical Reports Server (NTRS)
Stecker, F. W.
1981-01-01
Within the framework of grand unified theories, it is shown how spontaneous CP violation leads to a domain structure in the universe with the domains evolving into separate regions of matter and antimatter excesses. Subsequent to exponential horizon growth, this can result in a universe of matter galaxies and antimatter galaxies. Various astrophysical data appear to favor this form of big bang cosmology. Future direct tests for cosmologically significant antimatter are discussed.
From everyday emotions to aesthetic emotions: towards a unified theory of musical emotions.
Juslin, Patrik N
2013-09-01
The sound of music may arouse profound emotions in listeners. But such experiences seem to involve a 'paradox', namely that music--an abstract form of art, which appears removed from our concerns in everyday life--can arouse emotions - biologically evolved reactions related to human survival. How are these (seemingly) non-commensurable phenomena linked together? Key is to understand the processes through which sounds are imbued with meaning. It can be argued that the survival of our ancient ancestors depended on their ability to detect patterns in sounds, derive meaning from them, and adjust their behavior accordingly. Such an ecological perspective on sound and emotion forms the basis of a recent multi-level framework that aims to explain emotional responses to music in terms of a large set of psychological mechanisms. The goal of this review is to offer an updated and expanded version of the framework that can explain both 'everyday emotions' and 'aesthetic emotions'. The revised framework--referred to as BRECVEMA--includes eight mechanisms: Brain Stem Reflex, Rhythmic Entrainment, Evaluative Conditioning, Contagion, Visual Imagery, Episodic Memory, Musical Expectancy, and Aesthetic Judgment. In this review, it is argued that all of the above mechanisms may be directed at information that occurs in a 'musical event' (i.e., a specific constellation of music, listener, and context). Of particular significance is the addition of a mechanism corresponding to aesthetic judgments of the music, to better account for typical 'appreciation emotions' such as admiration and awe. Relationships between aesthetic judgments and other mechanisms are reviewed based on the revised framework. It is suggested that the framework may contribute to a long-needed reconciliation between previous approaches that have conceptualized music listeners' responses in terms of either 'everyday emotions' or 'aesthetic emotions'. © 2013 Elsevier B.V. All rights reserved.
From everyday emotions to aesthetic emotions: Towards a unified theory of musical emotions
NASA Astrophysics Data System (ADS)
Juslin, Patrik N.
2013-09-01
The sound of music may arouse profound emotions in listeners. But such experiences seem to involve a ‘paradox’, namely that music - an abstract form of art, which appears removed from our concerns in everyday life - can arouse emotions - biologically evolved reactions related to human survival. How are these (seemingly) non-commensurable phenomena linked together? Key is to understand the processes through which sounds are imbued with meaning. It can be argued that the survival of our ancient ancestors depended on their ability to detect patterns in sounds, derive meaning from them, and adjust their behavior accordingly. Such an ecological perspective on sound and emotion forms the basis of a recent multi-level framework that aims to explain emotional responses to music in terms of a large set of psychological mechanisms. The goal of this review is to offer an updated and expanded version of the framework that can explain both ‘everyday emotions’ and ‘aesthetic emotions’. The revised framework - referred to as BRECVEMA - includes eight mechanisms: Brain Stem Reflex, Rhythmic Entrainment, Evaluative Conditioning, Contagion, Visual Imagery, Episodic Memory, Musical Expectancy, and Aesthetic Judgment. In this review, it is argued that all of the above mechanisms may be directed at information that occurs in a ‘musical event’ (i.e., a specific constellation of music, listener, and context). Of particular significance is the addition of a mechanism corresponding to aesthetic judgments of the music, to better account for typical ‘appreciation emotions’ such as admiration and awe. Relationships between aesthetic judgments and other mechanisms are reviewed based on the revised framework. It is suggested that the framework may contribute to a long-needed reconciliation between previous approaches that have conceptualized music listeners' responses in terms of either ‘everyday emotions’ or ‘aesthetic emotions’.
Celedonio Aguirre-Bravo; Carlos Rodriguez Franco
1999-01-01
The general objective of this Symposium was to build on the best science and technology available to assure that the data and information produced in future inventory and monitoring programs are comparable, quality assured, available, and adequate for their intended purposes, thereby providing a reliable framework for characterization, assessment, and management of...
ERIC Educational Resources Information Center
Molina, Otilia Alejandro; Ratté, Sylvie
2017-01-01
This research introduces a method to construct a unified representation of teachers and students perspectives based on the actionable knowledge discovery (AKD) and delivery framework. The representation is constructed using two models: one obtained from student evaluations and the other obtained from teachers' reflections about their teaching…
Metzger, Marc J.; Bunce, Robert G.H.; Jongman, Rob H.G.; Sayre, Roger G.; Trabucco, Antonio; Zomer, Robert
2013-01-01
Main conclusions: The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (http://www.geoportal.org).
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
Teaching Introductory Business Statistics Using the DCOVA Framework
ERIC Educational Resources Information Center
Levine, David M.; Stephan, David F.
2011-01-01
Introductory business statistics students often receive little guidance on how to apply the methods they learn to further business objectives they may one day face. And those students may fail to see the continuity among the topics taught in an introductory course if they learn those methods outside a context that provides a unifying framework.…
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
Evaluating Health Information Systems Using Ontologies
Anderberg, Peter; Larsson, Tobias C; Fricker, Samuel A; Berglund, Johan
2016-01-01
Background There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems. Objectives The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems—whether similar or heterogeneous—by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework. Methods On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries. Results The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project. Conclusions The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems. PMID:27311735
Evaluating Health Information Systems Using Ontologies.
Eivazzadeh, Shahryar; Anderberg, Peter; Larsson, Tobias C; Fricker, Samuel A; Berglund, Johan
2016-06-16
There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems. The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems-whether similar or heterogeneous-by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework. On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries. The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project. The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems.
Wolff, J Gerard
2014-01-01
The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.
Beyond Containment and Deterrence: A Security Framework for Europe in the 21st Century
1990-04-02
decades of the 21st Century in Europe, and examines DDO FJoA 1473 E. T1O. Of INOV 65 IS OBSOLETE Uaf eSECRIT CUnclassified SECURITY CLASSIFICATION’ OF THIS... Poland , and parts of France and Russia, but it did not truely unify Germany. Bismarck unified only parts of Germany which he could constrain under...Europe, Central Europe, the Balkans, and the Soviet Union. Central Europe includes Vest Germany, East Germany, Austria, Czechoslavakia, Poland , and
Towards a Unified Description of the Electroweak Nuclear Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Benhar, Omar; Lovato, Alessandro
2015-06-01
We briefly review the growing efforts to set up a unified framework for the description of neutrino interactions with atomic nuclei and nuclear matter, applicable in the broad kinematical region corresponding to neutrino energies ranging between few MeV and few GeV. The emerging picture suggests that the formalism of nuclear many-body theory (NMBT) can be exploited to obtain the neutrino-nucleus cross-sections needed for both the interpretation of oscillation signals and simulations of neutrino transport in compact stars
A theoretical formulation of wave-vortex interactions
NASA Technical Reports Server (NTRS)
Wu, J. Z.; Wu, J. M.
1989-01-01
A unified theoretical formulation for wave-vortex interaction, designated the '(omega, Pi) framework,' is presented. Based on the orthogonal decomposition of fluid dynamic interactions, the formulation can be used to study a variety of problems, including the interaction of a longitudinal (acoustic) wave and/or transverse (vortical) wave with a main vortex flow. Moreover, the formulation permits a unified treatment of wave-vortex interaction at various approximate levels, where the normal 'piston' process and tangential 'rubbing' process can be approximated dfferently.
Hu, Shiang; Yao, Dezhong; Valdes-Sosa, Pedro A.
2018-01-01
The choice of reference for the electroencephalogram (EEG) is a long-lasting unsolved issue resulting in inconsistent usages and endless debates. Currently, both the average reference (AR) and the reference electrode standardization technique (REST) are two primary, apparently irreconcilable contenders. We propose a theoretical framework to resolve this reference issue by formulating both (a) estimation of potentials at infinity, and (b) determination of the reference, as a unified Bayesian linear inverse problem, which can be solved by maximum a posterior estimation. We find that AR and REST are very particular cases of this unified framework: AR results from biophysically non-informative prior; while REST utilizes the prior based on the EEG generative model. To allow for simultaneous denoising and reference estimation, we develop the regularized versions of AR and REST, named rAR and rREST, respectively. Both depend on a regularization parameter that is the noise to signal variance ratio. Traditional and new estimators are evaluated with this framework, by both simulations and analysis of real resting EEGs. Toward this end, we leverage the MRI and EEG data from 89 subjects which participated in the Cuban Human Brain Mapping Project. Generated artificial EEGs—with a known ground truth, show that relative error in estimating the EEG potentials at infinity is lowest for rREST. It also reveals that realistic volume conductor models improve the performances of REST and rREST. Importantly, for practical applications, it is shown that an average lead field gives the results comparable to the individual lead field. Finally, it is shown that the selection of the regularization parameter with Generalized Cross-Validation (GCV) is close to the “oracle” choice based on the ground truth. When evaluated with the real 89 resting state EEGs, rREST consistently yields the lowest GCV. This study provides a novel perspective to the EEG reference problem by means of a unified inverse solution framework. It may allow additional principled theoretical formulations and numerical evaluation of performance. PMID:29780302
In quest of a systematic framework for unifying and defining nanoscience
2009-01-01
This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience. Electronic supplementary material The online version of this article (doi:10.1007/s11051-009-9632-z) contains supplementary material, which is available to authorized users. PMID:21170133
NASA Astrophysics Data System (ADS)
Beretta, Gian Paolo
2014-10-01
By suitable reformulations, we cast the mathematical frameworks of several well-known different approaches to the description of nonequilibrium dynamics into a unified formulation valid in all these contexts, which extends to such frameworks the concept of steepest entropy ascent (SEA) dynamics introduced by the present author in previous works on quantum thermodynamics. Actually, the present formulation constitutes a generalization also for the quantum thermodynamics framework. The analysis emphasizes that in the SEA modeling principle a key role is played by the geometrical metric with respect to which to measure the length of a trajectory in state space. In the near-thermodynamic-equilibrium limit, the metric tensor is directly related to the Onsager's generalized resistivity tensor. Therefore, through the identification of a suitable metric field which generalizes the Onsager generalized resistance to the arbitrarily far-nonequilibrium domain, most of the existing theories of nonequilibrium thermodynamics can be cast in such a way that the state exhibits the spontaneous tendency to evolve in state space along the path of SEA compatible with the conservation constraints and the boundary conditions. The resulting unified family of SEA dynamical models is intrinsically and strongly consistent with the second law of thermodynamics. The non-negativity of the entropy production is a general and readily proved feature of SEA dynamics. In several of the different approaches to nonequilibrium description we consider here, the SEA concept has not been investigated before. We believe it defines the precise meaning and the domain of general validity of the so-called maximum entropy production principle. Therefore, it is hoped that the present unifying approach may prove useful in providing a fresh basis for effective, thermodynamically consistent, numerical models and theoretical treatments of irreversible conservative relaxation towards equilibrium from far nonequilibrium states. The mathematical frameworks we consider are the following: (A) statistical or information-theoretic models of relaxation; (B) small-scale and rarefied gas dynamics (i.e., kinetic models for the Boltzmann equation); (C) rational extended thermodynamics, macroscopic nonequilibrium thermodynamics, and chemical kinetics; (D) mesoscopic nonequilibrium thermodynamics, continuum mechanics with fluctuations; and (E) quantum statistical mechanics, quantum thermodynamics, mesoscopic nonequilibrium quantum thermodynamics, and intrinsic quantum thermodynamics.
Development and application of unified algorithms for problems in computational science
NASA Technical Reports Server (NTRS)
Shankar, Vijaya; Chakravarthy, Sukumar
1987-01-01
A framework is presented for developing computationally unified numerical algorithms for solving nonlinear equations that arise in modeling various problems in mathematical physics. The concept of computational unification is an attempt to encompass efficient solution procedures for computing various nonlinear phenomena that may occur in a given problem. For example, in Computational Fluid Dynamics (CFD), a unified algorithm will be one that allows for solutions to subsonic (elliptic), transonic (mixed elliptic-hyperbolic), and supersonic (hyperbolic) flows for both steady and unsteady problems. The objectives are: development of superior unified algorithms emphasizing accuracy and efficiency aspects; development of codes based on selected algorithms leading to validation; application of mature codes to realistic problems; and extension/application of CFD-based algorithms to problems in other areas of mathematical physics. The ultimate objective is to achieve integration of multidisciplinary technologies to enhance synergism in the design process through computational simulation. Specific unified algorithms for a hierarchy of gas dynamics equations and their applications to two other areas: electromagnetic scattering, and laser-materials interaction accounting for melting.
Backward Registration Based Aspect Ratio Similarity (ARS) for Image Retargeting Quality Assessment.
Zhang, Yabin; Fang, Yuming; Lin, Weisi; Zhang, Xinfeng; Li, Leida
2016-06-28
During the past few years, there have been various kinds of content-aware image retargeting operators proposed for image resizing. However, the lack of effective objective retargeting quality assessment metrics limits the further development of image retargeting techniques. Different from traditional Image Quality Assessment (IQA) metrics, the quality degradation during image retargeting is caused by artificial retargeting modifications, and the difficulty for Image Retargeting Quality Assessment (IRQA) lies in the alternation of the image resolution and content, which makes it impossible to directly evaluate the quality degradation like traditional IQA. In this paper, we interpret the image retargeting in a unified framework of resampling grid generation and forward resampling. We show that the geometric change estimation is an efficient way to clarify the relationship between the images. We formulate the geometric change estimation as a Backward Registration problem with Markov Random Field (MRF) and provide an effective solution. The geometric change aims to provide the evidence about how the original image is resized into the target image. Under the guidance of the geometric change, we develop a novel Aspect Ratio Similarity metric (ARS) to evaluate the visual quality of retargeted images by exploiting the local block changes with a visual importance pooling strategy. Experimental results on the publicly available MIT RetargetMe and CUHK datasets demonstrate that the proposed ARS can predict more accurate visual quality of retargeted images compared with state-of-the-art IRQA metrics.
An integrative, experience-based theory of attentional control.
Wilder, Matthew H; Mozer, Michael C; Wickens, Christopher D
2011-02-09
Although diverse, theories of visual attention generally share the notion that attention is controlled by some combination of three distinct strategies: (1) exogenous cuing from locally contrasting primitive visual features, such as abrupt onsets or color singletons (e.g., L. Itti, C. Koch, & E. Neiber, 1998), (2) endogenous gain modulation of exogenous activations, used to guide attention to task-relevant features (e.g., V. Navalpakkam & L. Itti, 2007; J. Wolfe, 1994, 2007), and (3) endogenous prediction of likely locations of interest, based on task and scene gist (e.g., A. Torralba, A. Oliva, M. Castelhano, & J. Henderson, 2006). However, little work has been done to synthesize these disparate theories. In this work, we propose a unifying conceptualization in which attention is controlled along two dimensions: the degree of task focus and the contextual scale of operation. Previously proposed strategies-and their combinations-can be viewed as instances of this one mechanism. Thus, this theory serves not as a replacement for existing models but as a means of bringing them into a coherent framework. We present an implementation of this theory and demonstrate its applicability to a wide range of attentional phenomena. The model accounts for key results in visual search with synthetic images and makes reasonable predictions for human eye movements in search tasks involving real-world images. In addition, the theory offers an unusual perspective on attention that places a fundamental emphasis on the role of experience and task-related knowledge.
Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun
2017-01-01
Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. PMID:27733503
NASA Astrophysics Data System (ADS)
Mirkia, Hasti; Sangari, Arash; Nelson, Mark; Assadi, Amir H.
2013-03-01
Architecture brings together diverse elements to enhance the observer's measure of esthetics and the convenience of functionality. Architects often conceptualize synthesis of design elements to invoke the observer's sense of harmony and positive affect. How does an observer's brain respond to harmony of design in interior spaces? One implicit consideration by architects is the role of guided visual attention by observers while navigating indoors. Prior visual experience of natural scenes provides the perceptual basis for Gestalt of design elements. In contrast, Gestalt of organization in design varies according to the architect's decision. We outline a quantitative theory to measure the success in utilizing the observer's psychological factors to achieve the desired positive affect. We outline a unified framework for perception of geometry and motion in interior spaces, which integrates affective and cognitive aspects of human vision in the context of anthropocentric interior design. The affective criteria are derived from contemporary theories of interior design. Our contribution is to demonstrate that the neural computations in an observer's eye movement could be used to elucidate harmony in perception of form, space and motion, thus a measure of goodness of interior design. Through mathematical modeling, we argue the plausibility of the relevant hypotheses.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eccleston, C.H.
1997-09-05
The National Environmental Policy Act (NEPA) of 1969 was established by Congress more than a quarter of a century ago, yet there is a surprising lack of specific tools, techniques, and methodologies for effectively implementing these regulatory requirements. Lack of professionally accepted techniques is a principal factor responsible for many inefficiencies. Often, decision makers do not fully appreciate or capitalize on the true potential which NEPA provides as a platform for planning future actions. New approaches and modem management tools must be adopted to fully achieve NEPA`s mandate. A new strategy, referred to as Total Federal Planning, is proposed formore » unifying large-scale federal planning efforts under a single, systematic, structured, and holistic process. Under this approach, the NEPA planning process provides a unifying framework for integrating all early environmental and nonenvironmental decision-making factors into a single comprehensive planning process. To promote effectiveness and efficiency, modem tools and principles from the disciplines of Value Engineering, Systems Engineering, and Total Quality Management are incorporated. Properly integrated and implemented, these planning tools provide the rigorous, structured, and disciplined framework essential in achieving effective planning. Ultimately, the goal of a Total Federal Planning strategy is to construct a unified and interdisciplinary framework that substantially improves decision-making, while reducing the time, cost, redundancy, and effort necessary to comply with environmental and other planning requirements. At a time when Congress is striving to re-engineer the governmental framework, apparatus, and process, a Total Federal Planning philosophy offers a systematic approach for uniting the disjointed and often convoluted planning process currently used by most federal agencies. Potentially this approach has widespread implications in the way federal planning is approached.« less
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
ERIC Educational Resources Information Center
National Center for Education Statistics, 2011
2011-01-01
Guided by a new framework, the National Assessment of Educational Progress (NAEP) science assessment was updated in 2009 to keep the content current with key developments in science, curriculum standards, assessments, and research. The 2009 framework organizes science content into three broad content areas. Physical science includes concepts…
A unifying framework for quantifying the nature of animal interactions.
Potts, Jonathan R; Mokross, Karl; Lewis, Mark A
2014-07-06
Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their environment. Despite both types of interaction fundamentally influencing animal behaviour, there has hitherto been no unifying framework for the models proposed in both areas. Here, we construct a general method for inferring population-level spatial patterns from underlying individual movement and interaction processes, a key ingredient in building a statistical mechanics for ecological systems. We show that resource selection functions, as well as several examples of collective motion models, arise as special cases of our framework, thus bringing together resource selection analysis and collective animal behaviour into a single theory. In particular, we focus on combining the various mechanistic models of territorial interactions in the literature with step selection functions, by incorporating interactions into the step selection framework and demonstrating how to derive territorial patterns from the resulting models. We demonstrate the efficacy of our model by application to a population of insectivore birds in the Amazon rainforest. © 2014 The Author(s) Published by the Royal Society. All rights reserved.
Application of Frameworks in the Analysis and (Re)design of Interactive Visual Learning Tools
ERIC Educational Resources Information Center
Liang, Hai-Ning; Sedig, Kamran
2009-01-01
Interactive visual learning tools (IVLTs) are software environments that encode and display information visually and allow learners to interact with the visual information. This article examines the application and utility of frameworks in the analysis and design of IVLTs at the micro level. Frameworks play an important role in any design. They…
40 CFR 300.105 - General organization concepts.
Code of Federal Regulations, 2010 CFR
2010-07-01
... capabilities. (b) Three fundamental kinds of activities are performed pursuant to the NCP: (1) Preparedness....205(c). (d) The basic framework for the response management structure is a system (e.g., a unified...
Measuring pictorial balance perception at first glance using Japanese calligraphy
Gershoni, Sharon; Hochstein, Shaul
2011-01-01
According to art theory, pictorial balance acts to unify picture elements into a cohesive composition. For asymmetrical compositions, balancing elements is thought to be similar to balancing mechanical weights in a framework of symmetry axes. Assessment of preference for balance (APB), based on the symmetry-axes framework suggested in Arnheim R, 1974 Art and Visual Perception: A Psychology of the Creative Eye (Berkeley, CA: University of California Press), successfully matched subject balance ratings of images of geometrical shapes over unlimited viewing time. We now examine pictorial balance perception of Japanese calligraphy during first fixation, isolated from later cognitive processes, comparing APB measures with results from balance-rating and comparison tasks. Results show high between-task correlation, but low correlation with APB. We repeated the rating task, expanding the image set to include five rotations of each image, comparing balance perception of artist and novice participant groups. Rotation has no effect on APB balance computation but dramatically affects balance rating, especially for art experts. We analyze the variety of rotation effects and suggest that, rather than depending on element size and position relative to symmetry axes, first fixation balance processing derives from global processes such as grouping of lines and shapes, object recognition, preference for horizontal and vertical elements, closure, and completion, enhanced by vertical symmetry. PMID:23145242
A unified and efficient framework for court-net sports video analysis using 3D camera modeling
NASA Astrophysics Data System (ADS)
Han, Jungong; de With, Peter H. N.
2007-01-01
The extensive amount of video data stored on available media (hard and optical disks) necessitates video content analysis, which is a cornerstone for different user-friendly applications, such as, smart video retrieval and intelligent video summarization. This paper aims at finding a unified and efficient framework for court-net sports video analysis. We concentrate on techniques that are generally applicable for more than one sports type to come to a unified approach. To this end, our framework employs the concept of multi-level analysis, where a novel 3-D camera modeling is utilized to bridge the gap between the object-level and the scene-level analysis. The new 3-D camera modeling is based on collecting features points from two planes, which are perpendicular to each other, so that a true 3-D reference is obtained. Another important contribution is a new tracking algorithm for the objects (i.e. players). The algorithm can track up to four players simultaneously. The complete system contributes to summarization by various forms of information, of which the most important are the moving trajectory and real-speed of each player, as well as 3-D height information of objects and the semantic event segments in a game. We illustrate the performance of the proposed system by evaluating it for a variety of court-net sports videos containing badminton, tennis and volleyball, and we show that the feature detection performance is above 92% and events detection about 90%.
Generic-distributed framework for cloud services marketplace based on unified ontology.
Hasan, Samer; Valli Kumari, V
2017-11-01
Cloud computing is a pattern for delivering ubiquitous and on demand computing resources based on pay-as-you-use financial model. Typically, cloud providers advertise cloud service descriptions in various formats on the Internet. On the other hand, cloud consumers use available search engines (Google and Yahoo) to explore cloud service descriptions and find the adequate service. Unfortunately, general purpose search engines are not designed to provide a small and complete set of results, which makes the process a big challenge. This paper presents a generic-distrusted framework for cloud services marketplace to automate cloud services discovery and selection process, and remove the barriers between service providers and consumers. Additionally, this work implements two instances of generic framework by adopting two different matching algorithms; namely dominant and recessive attributes algorithm borrowed from gene science and semantic similarity algorithm based on unified cloud service ontology. Finally, this paper presents unified cloud services ontology and models the real-life cloud services according to the proposed ontology. To the best of the authors' knowledge, this is the first attempt to build a cloud services marketplace where cloud providers and cloud consumers can trend cloud services as utilities. In comparison with existing work, semantic approach reduced the execution time by 20% and maintained the same values for all other parameters. On the other hand, dominant and recessive attributes approach reduced the execution time by 57% but showed lower value for recall.
NASA Astrophysics Data System (ADS)
Peña, Adrian F.; Devine, Jack; Doronin, Alexander; Meglinski, Igor
2014-03-01
We report the use of conventional Optical Coherence Tomography (OCT) for visualization of propagation of low frequency electric field in soft biological tissues ex vivo. To increase the overall quality of the experimental images an adaptive Wiener filtering technique has been employed. Fourier domain correlation has been subsequently applied to enhance spatial resolution of images of biological tissues influenced by low frequency electric field. Image processing has been performed on Graphics Processing Units (GPUs) utilizing Compute Unified Device Architecture (CUDA) framework in the frequencydomain. The results show that variation in voltage and frequency of the applied electric field relates exponentially to the magnitude of its influence on biological tissue. The magnitude of influence is about twice more for fresh tissue samples in comparison to non-fresh ones. The obtained results suggest that OCT can be used for observation and quantitative evaluation of the electro-kinetic changes in biological tissues under different physiological conditions, functional electrical stimulation, and potentially can be used non-invasively for food quality control.
A Subdivision-Based Representation for Vector Image Editing.
Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou
2012-11-01
Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.
Cytoscape: a software environment for integrated models of biomolecular interaction networks.
Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey
2003-11-01
Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
The experience of agency: an interplay between prediction and postdiction
Synofzik, Matthis; Vosgerau, Gottfried; Voss, Martin
2013-01-01
The experience of agency, i.e., the registration that I am the initiator of my actions, is a basic and constant underpinning of our interaction with the world. Whereas several accounts have underlined predictive processes as the central mechanism (e.g., the comparator model by C. Frith), others emphasized postdictive inferences (e.g., post-hoc inference account by D. Wegner). Based on increasing evidence that both predictive and postdictive processes contribute to the experience of agency, we here present a unifying but at the same time parsimonious approach that reconciles these accounts: predictive and postdictive processes are both integrated by the brain according to the principles of optimal cue integration. According to this framework, predictive and postdictive processes each serve as authorship cues that are continuously integrated and weighted depending on their availability and reliability in a given situation. Both sensorimotor and cognitive signals can serve as predictive cues (e.g., internal predictions based on an efferency copy of the motor command or cognitive anticipations based on priming). Similarly, other sensorimotor and cognitive cues can each serve as post-hoc cues (e.g., visual feedback of the action or the affective valence of the action outcome). Integration and weighting of these cues might not only differ between contexts and individuals, but also between different subject and disease groups. For example, schizophrenia patients with delusions of influence seem to rely less on (probably imprecise) predictive motor signals of the action and more on post-hoc action cues like e.g., visual feedback and, possibly, the affective valence of the action outcome. Thus, the framework of optimal cue integration offers a promising approach that directly stimulates a wide range of experimentally testable hypotheses on agency processing in different subject groups. PMID:23508565
Master Middle Ware: A Tool to Integrate Water Resources and Fish Population Dynamics Models
NASA Astrophysics Data System (ADS)
Yi, S.; Sandoval Solis, S.; Thompson, L. C.; Kilduff, D. P.
2017-12-01
Linking models that investigate separate components of ecosystem processes has the potential to unify messages regarding management decisions by evaluating potential trade-offs in a cohesive framework. This project aimed to improve the ability of riparian resource managers to forecast future water availability conditions and resultant fish habitat suitability, in order to better inform their management decisions. To accomplish this goal, we developed a middleware tool that is capable of linking and overseeing the operations of two existing models, a water resource planning tool Water Evaluation and Planning (WEAP) model and a habitat-based fish population dynamics model (WEAPhish). First, we designed the Master Middle Ware (MMW) software in Visual Basic for Application® in one Excel® file that provided a familiar framework for both data input and output Second, MMW was used to link and jointly operate WEAP and WEAPhish, using Visual Basic Application (VBA) macros to implement system level calls to run the models. To demonstrate the utility of this approach, hydrological, biological, and middleware model components were developed for the Butte Creek basin. This tributary of the Sacramento River, California is managed for both hydropower and the persistence of a threatened population of spring-run Chinook salmon (Oncorhynchus tschawytscha). While we have demonstrated the use of MMW for a particular watershed and fish population, MMW can be customized for use with different rivers and fish populations, assuming basic data requirements are met. This model integration improves on ad hoc linkages for managing data transfer between software programs by providing a consistent, user-friendly, and familiar interface across different model implementations. Furthermore, the data-viewing capabilities of MMW facilitate the rapid interpretation of model results by hydrologists, fisheries biologists, and resource managers, in order to accelerate learning and management decision making.
A Framework for the Design of Effective Graphics for Scientific Visualization
NASA Technical Reports Server (NTRS)
Miceli, Kristina D.
1992-01-01
This proposal presents a visualization framework, based on a data model, that supports the production of effective graphics for scientific visualization. Visual representations are effective only if they augment comprehension of the increasing amounts of data being generated by modern computer simulations. These representations are created by taking into account the goals and capabilities of the scientist, the type of data to be displayed, and software and hardware considerations. This framework is embodied in an assistant-based visualization system to guide the scientist in the visualization process. This will improve the quality of the visualizations and decrease the time the scientist is required to spend in generating the visualizations. I intend to prove that such a framework will create a more productive environment for tile analysis and interpretation of large, complex data sets.
New developments in UTMOST : application to electronic stability control.
DOT National Transportation Integrated Search
2009-10-01
The Unified Tool for Mapping Opportunities for Safety Technology (UTMOST) : is a model of crash data that incorporates the complex relationships among different : vehicle and driver variables. It is designed to visualize the effect of multiple safety...
LIFE CYCLE ENGINEERING GUIDELINES
This document provides guidelines for the implementation of LCE concepts, information, and techniques in engineering products, systems, processes, and facilities. To make this document as practical and useable as possible, a unifying LCE framework is presented. Subsequent topics ...
Value of Flexibility - Phase 1
2010-09-25
weaknesses of each approach. During this period, we also explored the development of an analytical framework based on sound mathematical constructs... mathematical constructs. A review of the current state-of-the-art showed that there is little unifying theory or guidance on best approaches to...research activities is in developing a coherent value based definition of flexibility that is based on an analytical framework that is mathematically
Food-web based unified model of macro- and microevolution.
Chowdhury, Debashish; Stauffer, Dietrich
2003-10-01
We incorporate the generic hierarchical architecture of foodwebs into a "unified" model that describes both micro- and macroevolutions within a single theoretical framework. This model describes the microevolution in detail by accounting for the birth, ageing, and natural death of individual organisms as well as prey-predator interactions on a hierarchical dynamic food web. It also provides a natural description of random mutations and speciation (origination) of species as well as their extinctions. The distribution of lifetimes of species follows an approximate power law only over a limited regime.
Unified approach to redshift in cosmological/black hole spacetimes and synchronous frame
NASA Astrophysics Data System (ADS)
Toporensky, A. V.; Zaslavskii, O. B.; Popov, S. B.
2018-01-01
Usually, interpretation of redshift in static spacetimes (for example, near black holes) is opposed to that in cosmology. In this methodological note, we show that both explanations are unified in a natural picture. This is achieved if, considering the static spacetime, one (i) makes a transition to a synchronous frame, and (ii) returns to the original frame by means of local Lorentz boost. To reach our goal, we consider a rather general class of spherically symmetric spacetimes. In doing so, we construct frames that generalize the well-known Lemaitre and Painlevé-Gullstand ones and elucidate the relation between them. This helps us to understand, in a unifying approach, how gravitation reveals itself in different branches of general relativity. This framework can be useful for general relativity university courses.
Impact of Beads and Drops on a Repellent Solid Surface: A Unified Description
NASA Astrophysics Data System (ADS)
Arora, S.; Fromental, J.-M.; Mora, S.; Phou, Ty; Ramos, L.; Ligoure, C.
2018-04-01
We investigate freely expanding sheets formed by ultrasoft gel beads, and liquid and viscoelastic drops, produced by the impact of the bead or drop on a silicon wafer covered with a thin layer of liquid nitrogen that suppresses viscous dissipation thanks to an inverse Leidenfrost effect. Our experiments show a unified behavior for the impact dynamics that holds for solids, liquids, and viscoelastic fluids and that we rationalize by properly taking into account elastocapillary effects. In this framework, the classical impact dynamics of solids and liquids, as far as viscous dissipation is negligible, appears as the asymptotic limits of a universal theoretical description. A novel material-dependent characteristic velocity that includes both capillary and bulk elasticity emerges from this unified description of the physics of impact.
SCIFIO: an extensible framework to support scientific image formats.
Hiner, Mark C; Rueden, Curtis T; Eliceiri, Kevin W
2016-12-07
No gold standard exists in the world of scientific image acquisition; a proliferation of instruments each with its own proprietary data format has made out-of-the-box sharing of that data nearly impossible. In the field of light microscopy, the Bio-Formats library was designed to translate such proprietary data formats to a common, open-source schema, enabling sharing and reproduction of scientific results. While Bio-Formats has proved successful for microscopy images, the greater scientific community was lacking a domain-independent framework for format translation. SCIFIO (SCientific Image Format Input and Output) is presented as a freely available, open-source library unifying the mechanisms of reading and writing image data. The core of SCIFIO is its modular definition of formats, the design of which clearly outlines the components of image I/O to encourage extensibility, facilitated by the dynamic discovery of the SciJava plugin framework. SCIFIO is structured to support coexistence of multiple domain-specific open exchange formats, such as Bio-Formats' OME-TIFF, within a unified environment. SCIFIO is a freely available software library developed to standardize the process of reading and writing scientific image formats.
Zenni, Rafael Dudeque; Dickie, Ian A; Wingfield, Michael J; Hirsch, Heidi; Crous, Casparus J; Meyerson, Laura A; Burgess, Treena I; Zimmermann, Thalita G; Klock, Metha M; Siemann, Evan; Erfmeier, Alexandra; Aragon, Roxana; Montti, Lia; Le Roux, Johannes J
2016-12-30
Evolutionary processes greatly impact the outcomes of biological invasions. An extensive body of research suggests that invasive populations often undergo phenotypic and ecological divergence from their native sources. Evolution also operates at different and distinct stages during the invasion process. Thus, it is important to incorporate evolutionary change into frameworks of biological invasions because it allows us to conceptualize how these processes may facilitate or hinder invasion success. Here, we review such processes, with an emphasis on tree invasions, and place them in the context of the unified framework for biological invasions. The processes and mechanisms described are pre-introduction evolutionary history, sampling effect, founder effect, genotype-by-environment interactions, admixture, hybridization, polyploidization, rapid evolution, epigenetics, and second-genomes. For the last, we propose that co-evolved symbionts, both beneficial and harmful, which are closely physiologically associated with invasive species, contain critical genetic traits that affect the evolutionary dynamics of biological invasions. By understanding the mechanisms underlying invasion success, researchers will be better equipped to predict, understand, and manage biological invasions. Published by Oxford University Press on behalf of the Annals of Botany Company.
Dickie, Ian A.; Wingfield, Michael J.; Hirsch, Heidi; Crous, Casparus J.; Meyerson, Laura A.; Burgess, Treena I.; Zimmermann, Thalita G.; Klock, Metha M.; Siemann, Evan; Erfmeier, Alexandra; Aragon, Roxana; Montti, Lia; Le Roux, Johannes J.
2017-01-01
Abstract Evolutionary processes greatly impact the outcomes of biological invasions. An extensive body of research suggests that invasive populations often undergo phenotypic and ecological divergence from their native sources. Evolution also operates at different and distinct stages during the invasion process. Thus, it is important to incorporate evolutionary change into frameworks of biological invasions because it allows us to conceptualize how these processes may facilitate or hinder invasion success. Here, we review such processes, with an emphasis on tree invasions, and place them in the context of the unified framework for biological invasions. The processes and mechanisms described are pre-introduction evolutionary history, sampling effect, founder effect, genotype-by-environment interactions, admixture, hybridization, polyploidization, rapid evolution, epigenetics and second-genomes. For the last, we propose that co-evolved symbionts, both beneficial and harmful, which are closely physiologically associated with invasive species, contain critical genetic traits that affect the evolutionary dynamics of biological invasions. By understanding the mechanisms underlying invasion success, researchers will be better equipped to predict, understand and manage biological invasions. PMID:28039118
NASA Astrophysics Data System (ADS)
Pathirana, A.; Radhakrishnan, M.; Zevenbergen, C.; Quan, N. H.
2016-12-01
The need to address the shortcomings of urban systems - adaptation deficit - and shortcomings in response to climate change - `adaptation gap' - are both major challenges in maintaining the livability and sustainability of cities. However, the adaptation actions defined in terms of type I (addressing adaptation deficits) and type II (addressing adaptation gaps), often compete and conflict each other in the secondary cities of the global south. Extending the concept of the environmental Kuznets curve, this paper argues that a unified framework that calls for synergistic action on type I and type II adaptation is essential in order for these cities to maintain their livability, sustainability and resilience facing extreme rates of urbanization and rapid onset of climate change. The proposed framework has been demonstrated in Can Tho, Vietnam, where there are significant adaptation deficits due to rapid urbanisation and adaptation gaps due to climate change and socio-economic changes. The analysis in Can Tho reveals the lack of integration between type I and type II measures that could be overcome by closer integration between various stakeholders in terms of planning, prioritising and implementing the adaptation measures.
Unified framework for automated iris segmentation using distantly acquired face images.
Tan, Chun-Wei; Kumar, Ajay
2012-09-01
Remote human identification using iris biometrics has high civilian and surveillance applications and its success requires the development of robust segmentation algorithm to automatically extract the iris region. This paper presents a new iris segmentation framework which can robustly segment the iris images acquired using near infrared or visible illumination. The proposed approach exploits multiple higher order local pixel dependencies to robustly classify the eye region pixels into iris or noniris regions. Face and eye detection modules have been incorporated in the unified framework to automatically provide the localized eye region from facial image for iris segmentation. We develop robust postprocessing operations algorithm to effectively mitigate the noisy pixels caused by the misclassification. Experimental results presented in this paper suggest significant improvement in the average segmentation errors over the previously proposed approaches, i.e., 47.5%, 34.1%, and 32.6% on UBIRIS.v2, FRGC, and CASIA.v4 at-a-distance databases, respectively. The usefulness of the proposed approach is also ascertained from recognition experiments on three different publicly available databases.
Trajectory optimization for lunar soft landing with complex constraints
NASA Astrophysics Data System (ADS)
Chu, Huiping; Ma, Lin; Wang, Kexin; Shao, Zhijiang; Song, Zhengyu
2017-11-01
A unified trajectory optimization framework with initialization strategies is proposed in this paper for lunar soft landing for various missions with specific requirements. Two main missions of interest are Apollo-like Landing from low lunar orbit and Vertical Takeoff Vertical Landing (a promising mobility method) on the lunar surface. The trajectory optimization is characterized by difficulties arising from discontinuous thrust, multi-phase connections, jump of attitude angle, and obstacles avoidance. Here R-function is applied to deal with the discontinuities of thrust, checkpoint constraints are introduced to connect multiple landing phases, attitude angular rate is designed to get rid of radical changes, and safeguards are imposed to avoid collision with obstacles. The resulting dynamic problems are generally with complex constraints. The unified framework based on Gauss Pseudospectral Method (GPM) and Nonlinear Programming (NLP) solver are designed to solve the problems efficiently. Advanced initialization strategies are developed to enhance both the convergence and computation efficiency. Numerical results demonstrate the adaptability of the framework for various landing missions, and the performance of successful solution of difficult dynamic problems.
A Unified Framework for Periodic, On-Demand, and User-Specified Software Information
NASA Technical Reports Server (NTRS)
Kolano, Paul Z.
2004-01-01
Although grid computing can increase the number of resources available to a user; not all resources on the grid may have a software environment suitable for running a given application. To provide users with the necessary assistance for selecting resources with compatible software environments and/or for automatically establishing such environments, it is necessary to have an accurate source of information about the software installed across the grid. This paper presents a new OGSI-compliant software information service that has been implemented as part of NASA's Information Power Grid project. This service is built on top of a general framework for reconciling information from periodic, on-demand, and user-specified sources. Information is retrieved using standard XPath queries over a single unified namespace independent of the information's source. Two consumers of the provided software information, the IPG Resource Broker and the IPG Neutralization Service, are briefly described.
Semantically enabled image similarity search
NASA Astrophysics Data System (ADS)
Casterline, May V.; Emerick, Timothy; Sadeghi, Kolia; Gosse, C. A.; Bartlett, Brent; Casey, Jason
2015-05-01
Georeferenced data of various modalities are increasingly available for intelligence and commercial use, however effectively exploiting these sources demands a unified data space capable of capturing the unique contribution of each input. This work presents a suite of software tools for representing geospatial vector data and overhead imagery in a shared high-dimension vector or embedding" space that supports fused learning and similarity search across dissimilar modalities. While the approach is suitable for fusing arbitrary input types, including free text, the present work exploits the obvious but computationally difficult relationship between GIS and overhead imagery. GIS is comprised of temporally-smoothed but information-limited content of a GIS, while overhead imagery provides an information-rich but temporally-limited perspective. This processing framework includes some important extensions of concepts in literature but, more critically, presents a means to accomplish them as a unified framework at scale on commodity cloud architectures.
Motor symptoms in Parkinson's disease: A unified framework.
Moustafa, Ahmed A; Chakravarthy, Srinivasa; Phillips, Joseph R; Gupta, Ankur; Keri, Szabolcs; Polner, Bertalan; Frank, Michael J; Jahanshahi, Marjan
2016-09-01
Parkinson's disease (PD) is characterized by a range of motor symptoms. Besides the cardinal symptoms (akinesia and bradykinesia, tremor and rigidity), PD patients show additional motor deficits, including: gait disturbance, impaired handwriting, grip force and speech deficits, among others. Some of these motor symptoms (e.g., deficits of gait, speech, and handwriting) have similar clinical profiles, neural substrates, and respond similarly to dopaminergic medication and deep brain stimulation (DBS). Here, we provide an extensive review of the clinical characteristics and neural substrates of each of these motor symptoms, to highlight precisely how PD and its medical and surgical treatments impact motor symptoms. In conclusion, we offer a unified framework for understanding the range of motor symptoms in PD. We argue that various motor symptoms in PD reflect dysfunction of neural structures responsible for action selection, motor sequencing, and coordination and execution of movement. Copyright © 2016 Elsevier Ltd. All rights reserved.
Liu, Dan; Liu, Xuejun; Wu, Yiguang
2018-04-24
This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.
Robust nonlinear control of vectored thrust aircraft
NASA Technical Reports Server (NTRS)
Doyle, John C.; Murray, Richard; Morris, John
1993-01-01
An interdisciplinary program in robust control for nonlinear systems with applications to a variety of engineering problems is outlined. Major emphasis will be placed on flight control, with both experimental and analytical studies. This program builds on recent new results in control theory for stability, stabilization, robust stability, robust performance, synthesis, and model reduction in a unified framework using Linear Fractional Transformations (LFT's), Linear Matrix Inequalities (LMI's), and the structured singular value micron. Most of these new advances have been accomplished by the Caltech controls group independently or in collaboration with researchers in other institutions. These recent results offer a new and remarkably unified framework for all aspects of robust control, but what is particularly important for this program is that they also have important implications for system identification and control of nonlinear systems. This combines well with Caltech's expertise in nonlinear control theory, both in geometric methods and methods for systems with constraints and saturations.
Discrete shearlet transform: faithful digitization concept and its applications
NASA Astrophysics Data System (ADS)
Lim, Wang-Q.
2011-09-01
Over the past years, various representation systems which sparsely approximate functions governed by anisotropic features such as edges in images have been proposed. Alongside the theoretical development of these systems, algorithmic realizations of the associated transforms were provided. However, one of the most common short-comings of these frameworks is the lack of providing a unified treatment of the continuum and digital world, i.e., allowing a digital theory to be a natural digitization of the continuum theory. Shearlets were introduced as means to sparsely encode anisotropic singularities of multivariate data while providing a unified treatment of the continuous and digital realm. In this paper, we introduce a discrete framework which allows a faithful digitization of the continuum domain shearlet transform based on compactly supported shearlets. Finally, we show numerical experiments demonstrating the potential of the discrete shearlet transform in several image processing applications.
Some characteristics of supernetworks based on unified hybrid network theory framework
NASA Astrophysics Data System (ADS)
Liu, Qiang; Fang, Jin-Qing; Li, Yong
Comparing with single complex networks, supernetworks are more close to the real world in some ways, and have become the newest research hot spot in the network science recently. Some progresses have been made in the research of supernetworks, but the theoretical research method and complex network characteristics of supernetwork models are still needed to further explore. In this paper, we propose three kinds of supernetwork models with three layers based on the unified hybrid network theory framework (UHNTF), and introduce preferential and random linking, respectively, between the upper and lower layers. Then we compared the topological characteristics of the single networks with the supernetwork models. In order to analyze the influence of the interlayer edges on network characteristics, the cross-degree is defined as a new important parameter. Then some interesting new phenomena are found, the results imply this supernetwork model has reference value and application potential.
Snoopy--a unifying Petri net framework to investigate biomolecular networks.
Rohr, Christian; Marwan, Wolfgang; Heiner, Monika
2010-04-01
To investigate biomolecular networks, Snoopy provides a unifying Petri net framework comprising a family of related Petri net classes. Models can be hierarchically structured, allowing for the mastering of larger networks. To move easily between the qualitative, stochastic and continuous modelling paradigms, models can be converted into each other. We get models sharing structure, but specialized by their kinetic information. The analysis and iterative reverse engineering of biomolecular networks is supported by the simultaneous use of several Petri net classes, while the graphical user interface adapts dynamically to the active one. Built-in animation and simulation are complemented by exports to various analysis tools. Snoopy facilitates the addition of new Petri net classes thanks to its generic design. Our tool with Petri net samples is available free of charge for non-commercial use at http://www-dssz.informatik.tu-cottbus.de/snoopy.html; supported operating systems: Mac OS X, Windows and Linux (selected distributions).
A unified selection signal for attention and reward in primary visual cortex.
Stănişor, Liviu; van der Togt, Chris; Pennartz, Cyriel M A; Roelfsema, Pieter R
2013-05-28
Stimuli associated with high rewards evoke stronger neuronal activity than stimuli associated with lower rewards in many brain regions. It is not well understood how these reward effects influence activity in sensory cortices that represent low-level stimulus features. Here, we investigated the effects of reward information in the primary visual cortex (area V1) of monkeys. We found that the reward value of a stimulus relative to the value of other stimuli is a good predictor of V1 activity. Relative value biases the competition between stimuli, just as has been shown for selective attention. The neuronal latency of this reward value effect in V1 was similar to the latency of attentional influences. Moreover, V1 neurons with a strong value effect also exhibited a strong attention effect, which implies that relative value and top-down attention engage overlapping, if not identical, neuronal selection mechanisms. Our findings demonstrate that the effects of reward value reach down to the earliest sensory processing levels of the cerebral cortex and imply that theories about the effects of reward coding and top-down attention on visual representations should be unified.
Unified framework for information integration based on information geometry
Oizumi, Masafumi; Amari, Shun-ichi
2016-01-01
Assessment of causal influences is a ubiquitous and important subject across diverse research fields. Drawn from consciousness studies, integrated information is a measure that defines integration as the degree of causal influences among elements. Whereas pairwise causal influences between elements can be quantified with existing methods, quantifying multiple influences among many elements poses two major mathematical difficulties. First, overestimation occurs due to interdependence among influences if each influence is separately quantified in a part-based manner and then simply summed over. Second, it is difficult to isolate causal influences while avoiding noncausal confounding influences. To resolve these difficulties, we propose a theoretical framework based on information geometry for the quantification of multiple causal influences with a holistic approach. We derive a measure of integrated information, which is geometrically interpreted as the divergence between the actual probability distribution of a system and an approximated probability distribution where causal influences among elements are statistically disconnected. This framework provides intuitive geometric interpretations harmonizing various information theoretic measures in a unified manner, including mutual information, transfer entropy, stochastic interaction, and integrated information, each of which is characterized by how causal influences are disconnected. In addition to the mathematical assessment of consciousness, our framework should help to analyze causal relationships in complex systems in a complete and hierarchical manner. PMID:27930289
Ghosh, Avijit; Scott, Dennis O; Maurer, Tristan S
2014-02-14
In this work, we provide a unified theoretical framework describing how drug molecules can permeate across membranes in neutral and ionized forms for unstirred in vitro systems. The analysis provides a self-consistent basis for the origin of the unstirred water layer (UWL) within the Nernst-Planck framework in the fully unstirred limit and further provides an accounting mechanism based simply on the bulk aqueous solvent diffusion constant of the drug molecule. Our framework makes no new assumptions about the underlying physics of molecular permeation. We hold simply that Nernst-Planck is a reasonable approximation at low concentrations and all physical systems must conserve mass. The applicability of the derived framework has been examined both with respect to the effect of stirring and externally applied voltages to measured permeability. The analysis contains data for 9 compounds extracted from the literature representing a range of permeabilities and aqueous diffusion coefficients. Applicability with respect to ionized permeation is examined using literature data for the permanently charged cation, crystal violet, providing a basis for the underlying mechanism for ionized drug permeation for this molecule as being due to mobile counter-current flow. Copyright © 2013 Elsevier B.V. All rights reserved.
A Unified Framework for Street-View Panorama Stitching
Li, Li; Yao, Jian; Xie, Renping; Xia, Menghan; Zhang, Wei
2016-01-01
In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas. PMID:28025481
Expanding Understanding of Emergent Literacy: Empirical Support for a New Framework
ERIC Educational Resources Information Center
Erickson, Karen A.; Hatton, Deborah
2007-01-01
Emergent literacy in young children with visual impairments is examined using a conceptual framework proposed by Senechal, LeFevre, Smith-Chant, and Colton (2001). The utility of this framework for young children with visual impairments is illustrated using data from a field study of preschool classes for children with visual impairments.…
A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models.
Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S; Wu, Xiaowei; Müller, Rolf
2018-01-01
Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design.
A Unified Analysis of Structured Sonar-terrain Data using Bayesian Functional Mixed Models
Zhu, Hongxiao; Caspers, Philip; Morris, Jeffrey S.; Wu, Xiaowei; Müller, Rolf
2017-01-01
Sonar emits pulses of sound and uses the reflected echoes to gain information about target objects. It offers a low cost, complementary sensing modality for small robotic platforms. While existing analytical approaches often assume independence across echoes, real sonar data can have more complicated structures due to device setup or experimental design. In this paper, we consider sonar echo data collected from multiple terrain substrates with a dual-channel sonar head. Our goals are to identify the differential sonar responses to terrains and study the effectiveness of this dual-channel design in discriminating targets. We describe a unified analytical framework that achieves these goals rigorously, simultaneously, and automatically. The analysis was done by treating the echo envelope signals as functional responses and the terrain/channel information as covariates in a functional regression setting. We adopt functional mixed models that facilitate the estimation of terrain and channel effects while capturing the complex hierarchical structure in data. This unified analytical framework incorporates both Gaussian models and robust models. We fit the models using a full Bayesian approach, which enables us to perform multiple inferential tasks under the same modeling framework, including selecting models, estimating the effects of interest, identifying significant local regions, discriminating terrain types, and describing the discriminatory power of local regions. Our analysis of the sonar-terrain data identifies time regions that reflect differential sonar responses to terrains. The discriminant analysis suggests that a multi- or dual-channel design achieves target identification performance comparable with or better than a single-channel design. PMID:29749977
Unifying framework for multimodal brain MRI segmentation based on Hidden Markov Chains.
Bricq, S; Collet, Ch; Armspach, J P
2008-12-01
In the frame of 3D medical imaging, accurate segmentation of multimodal brain MR images is of interest for many brain disorders. However, due to several factors such as noise, imaging artifacts, intrinsic tissue variation and partial volume effects, tissue classification remains a challenging task. In this paper, we present a unifying framework for unsupervised segmentation of multimodal brain MR images including partial volume effect, bias field correction, and information given by a probabilistic atlas. Here-proposed method takes into account neighborhood information using a Hidden Markov Chain (HMC) model. Due to the limited resolution of imaging devices, voxels may be composed of a mixture of different tissue types, this partial volume effect is included to achieve an accurate segmentation of brain tissues. Instead of assigning each voxel to a single tissue class (i.e., hard classification), we compute the relative amount of each pure tissue class in each voxel (mixture estimation). Further, a bias field estimation step is added to the proposed algorithm to correct intensity inhomogeneities. Furthermore, atlas priors were incorporated using probabilistic brain atlas containing prior expectations about the spatial localization of different tissue classes. This atlas is considered as a complementary sensor and the proposed method is extended to multimodal brain MRI without any user-tunable parameter (unsupervised algorithm). To validate this new unifying framework, we present experimental results on both synthetic and real brain images, for which the ground truth is available. Comparison with other often used techniques demonstrates the accuracy and the robustness of this new Markovian segmentation scheme.
An object-oriented framework for medical image registration, fusion, and visualization.
Zhu, Yang-Ming; Cochoff, Steven M
2006-06-01
An object-oriented framework for image registration, fusion, and visualization was developed based on the classic model-view-controller paradigm. The framework employs many design patterns to facilitate legacy code reuse, manage software complexity, and enhance the maintainability and portability of the framework. Three sample applications built a-top of this framework are illustrated to show the effectiveness of this framework: the first one is for volume image grouping and re-sampling, the second one is for 2D registration and fusion, and the last one is for visualization of single images as well as registered volume images.
Brain-Mind Operational Architectonics Imaging: Technical and Methodological Aspects
Fingelkurts, Andrew A; Fingelkurts, Alexander A
2008-01-01
This review paper deals with methodological and technical foundations of the Operational Architectonics framework of brain and mind functioning. This theory provides a framework for mapping and understanding important aspects of the brain mechanisms that constitute perception, cognition, and eventually consciousness. The methods utilized within Operational Architectonics framework allow analyzing with an incredible detail the operational behavior of local neuronal assemblies and their joint activity in the form of unified and metastable operational modules, which constitute the whole hierarchy of brain operations, operations of cognition and phenomenal consciousness. PMID:19526071
A Unified Nonlinear Adaptive Approach for Detection and Isolation of Engine Faults
NASA Technical Reports Server (NTRS)
Tang, Liang; DeCastro, Jonathan A.; Zhang, Xiaodong; Farfan-Ramos, Luis; Simon, Donald L.
2010-01-01
A challenging problem in aircraft engine health management (EHM) system development is to detect and isolate faults in system components (i.e., compressor, turbine), actuators, and sensors. Existing nonlinear EHM methods often deal with component faults, actuator faults, and sensor faults separately, which may potentially lead to incorrect diagnostic decisions and unnecessary maintenance. Therefore, it would be ideal to address sensor faults, actuator faults, and component faults under one unified framework. This paper presents a systematic and unified nonlinear adaptive framework for detecting and isolating sensor faults, actuator faults, and component faults for aircraft engines. The fault detection and isolation (FDI) architecture consists of a parallel bank of nonlinear adaptive estimators. Adaptive thresholds are appropriately designed such that, in the presence of a particular fault, all components of the residual generated by the adaptive estimator corresponding to the actual fault type remain below their thresholds. If the faults are sufficiently different, then at least one component of the residual generated by each remaining adaptive estimator should exceed its threshold. Therefore, based on the specific response of the residuals, sensor faults, actuator faults, and component faults can be isolated. The effectiveness of the approach was evaluated using the NASA C-MAPSS turbofan engine model, and simulation results are presented.
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.
Reframing Information Literacy as a Metaliteracy
ERIC Educational Resources Information Center
Mackey, Thomas P.; Jacobson, Trudi E.
2011-01-01
Social media environments and online communities are innovative collaborative technologies that challenge traditional definitions of information literacy. Metaliteracy is an overarching and self-referential framework that integrates emerging technologies and unifies multiple literacy types. This redefinition of information literacy expands the…
Modeling the Development of Audiovisual Cue Integration in Speech Perception
Getz, Laura M.; Nordeen, Elke R.; Vrabic, Sarah C.; Toscano, Joseph C.
2017-01-01
Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues. PMID:28335558
Modeling the Development of Audiovisual Cue Integration in Speech Perception.
Getz, Laura M; Nordeen, Elke R; Vrabic, Sarah C; Toscano, Joseph C
2017-03-21
Adult speech perception is generally enhanced when information is provided from multiple modalities. In contrast, infants do not appear to benefit from combining auditory and visual speech information early in development. This is true despite the fact that both modalities are important to speech comprehension even at early stages of language acquisition. How then do listeners learn how to process auditory and visual information as part of a unified signal? In the auditory domain, statistical learning processes provide an excellent mechanism for acquiring phonological categories. Is this also true for the more complex problem of acquiring audiovisual correspondences, which require the learner to integrate information from multiple modalities? In this paper, we present simulations using Gaussian mixture models (GMMs) that learn cue weights and combine cues on the basis of their distributional statistics. First, we simulate the developmental process of acquiring phonological categories from auditory and visual cues, asking whether simple statistical learning approaches are sufficient for learning multi-modal representations. Second, we use this time course information to explain audiovisual speech perception in adult perceivers, including cases where auditory and visual input are mismatched. Overall, we find that domain-general statistical learning techniques allow us to model the developmental trajectory of audiovisual cue integration in speech, and in turn, allow us to better understand the mechanisms that give rise to unified percepts based on multiple cues.
Parallel Processing Strategies of the Primate Visual System
Nassi, Jonathan J.; Callaway, Edward M.
2009-01-01
Preface Incoming sensory information is sent to the brain along modality-specific channels corresponding to the five senses. Each of these channels further parses the incoming signals into parallel streams to provide a compact, efficient input to the brain. Ultimately, these parallel input signals must be elaborated upon and integrated within the cortex to provide a unified and coherent percept. Recent studies in the primate visual cortex have greatly contributed to our understanding of how this goal is accomplished. Multiple strategies including retinal tiling, hierarchical and parallel processing and modularity, defined spatially and by cell type-specific connectivity, are all used by the visual system to recover the rich detail of our visual surroundings. PMID:19352403
A UML profile for framework modeling.
Xu, Xiao-liang; Wang, Le-yu; Zhou, Hong
2004-01-01
The current standard Unified Modeling Language(UML) could not model framework flexibility and extendability adequately due to lack of appropriate constructs to distinguish framework hot-spots from kernel elements. A new UML profile that may customize UML for framework modeling was presented using the extension mechanisms of UML, providing a group of UML extensions to meet the needs of framework modeling. In this profile, the extended class diagrams and sequence diagrams were defined to straightforwardly identify the hot-spots and describe their instantiation restrictions. A transformation model based on design patterns was also put forward, such that the profile based framework design diagrams could be automatically mapped to the corresponding implementation diagrams. It was proved that the presented profile makes framework modeling more straightforwardly and therefore easier to understand and instantiate.
NASA Technical Reports Server (NTRS)
Erickson, Gary E.
2010-01-01
Laser vapor screen (LVS) flow visualization and pressure sensitive paint (PSP) techniques were applied in a unified approach to wind tunnel testing of slender wing and missile configurations dominated by vortex flows and shock waves at subsonic, transonic, and supersonic speeds. The off-surface cross-flow patterns using the LVS technique were combined with global PSP surface static pressure mappings to characterize the leading-edge vortices and shock waves that coexist and interact at high angles of attack. The synthesis of LVS and PSP techniques was also effective in identifying the significant effects of passive surface porosity and the presence of vertical tail surfaces on the flow topologies. An overview is given of LVS and PSP applications in selected experiments on small-scale models of generic slender wing and missile configurations in the NASA Langley Research Center (NASA LaRC) Unitary Plan Wind Tunnel (UPWT) and 8-Foot Transonic Pressure Tunnel (8-Foot TPT).
NASA Technical Reports Server (NTRS)
Erickson, Gary E.
2008-01-01
Laser vapor screen (LVS) flow visualization and pressure sensitive paint (PSP) techniques were applied in a unified approach to wind tunnel testing of slender wing and missile configurations dominated by vortex flows and shock waves at subsonic, transonic, and supersonic speeds. The off-surface cross-flow patterns using the LVS technique were combined with global PSP surface static pressure mappings to characterize the leading-edge vortices and shock waves that coexist and interact at high angles of attack (alpha). The synthesis of LVS and PSP techniques was also effective in identifying the significant effects of passive surface porosity and the presence of vertical tail surfaces on the flow topologies. An overview is given of LVS and PSP applications in selected experiments on small-scale models of generic slender wing and missile configurations in the NASA Langley Research Center (NASA LaRC) Unitary Plan Wind Tunnel (UPWT) and 8-Foot Transonic Pressure Tunnel (8-Foot TPT).
Sörqvist, Patrik; Stenfelt, Stefan; Rönnberg, Jerker
2012-11-01
Two fundamental research questions have driven attention research in the past: One concerns whether selection of relevant information among competing, irrelevant, information takes place at an early or at a late processing stage; the other concerns whether the capacity of attention is limited by a central, domain-general pool of resources or by independent, modality-specific pools. In this article, we contribute to these debates by showing that the auditory-evoked brainstem response (an early stage of auditory processing) to task-irrelevant sound decreases as a function of central working memory load (manipulated with a visual-verbal version of the n-back task). Furthermore, individual differences in central/domain-general working memory capacity modulated the magnitude of the auditory-evoked brainstem response, but only in the high working memory load condition. The results support a unified view of attention whereby the capacity of a late/central mechanism (working memory) modulates early precortical sensory processing.
A unified science of concussion
Maruta, Jun; Lee, Stephanie W; Jacobs, Emily F; Ghajar, Jamshid
2010-01-01
The etiology, imaging, and behavioral assessment of mild traumatic brain injury (mTBI) are daunting fields, given the lack of a cohesive neurobiological explanation for the observed cognitive deficits seen following mTBI. Although subjective patient self-report is the leading method of diagnosing mTBI, current scientific evidence suggests that quantitative measures of predictive timing, such as visual tracking, could be a useful adjunct to guide the assessment of attention and to screen for advanced brain imaging. Magnetic resonance diffusion tensor imaging (DTI) has demonstrated that mTBI is associated with widespread microstructural changes that include those in the frontal white matter tracts. Deficits observed during predictive visual tracking correlate with DTI findings that show lesions localized in neural pathways subserving the cognitive functions often disrupted in mTBI. Unifying the anatomical and behavioral approaches, the emerging evidence supports an explanation for mTBI that the observed cognitive impairments are a result of predictive timing deficits caused by shearing injuries in the frontal white matter tracts. PMID:20955326
Self-Efficacy: Toward a Unifying Theory of Behavioral Change
ERIC Educational Resources Information Center
Bandura, Albert
1977-01-01
This research presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of "self-efficacy". (Editor/RK)
COMPLEMENTARITY OF ECOLOGICAL GOAL FUNCTIONS
This paper summarizes, in the framework of network environ analysis, a set of analyses of energy-matter flow and storage in steady state systems. The network perspective is used to codify and unify ten ecological orientors or external principles: maximum power (Lotka), maximum st...
DataSpread: Unifying Databases and Spreadsheets.
Bendre, Mangesh; Sun, Bofan; Zhang, Ding; Zhou, Xinyan; Chang, Kevin ChenChuan; Parameswaran, Aditya
2015-08-01
Spreadsheet software is often the tool of choice for ad-hoc tabular data management, processing, and visualization, especially on tiny data sets. On the other hand, relational database systems offer significant power, expressivity, and efficiency over spreadsheet software for data management, while lacking in the ease of use and ad-hoc analysis capabilities. We demonstrate DataSpread, a data exploration tool that holistically unifies databases and spreadsheets. It continues to offer a Microsoft Excel-based spreadsheet front-end, while in parallel managing all the data in a back-end database, specifically, PostgreSQL. DataSpread retains all the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the advantages of traditional relational databases, such as scalability and the ability to use arbitrary SQL to import, filter, or join external or internal tables and have the results appear in the spreadsheet. DataSpread needs to reason about and reconcile differences in the notions of schema, addressing of cells and tuples, and the current "pane" (which exists in spreadsheets but not in traditional databases), and support data modifications at both the front-end and the back-end. Our demonstration will center on our first and early prototype of the DataSpread, and will give the attendees a sense for the enormous data exploration capabilities offered by unifying spreadsheets and databases.
DataSpread: Unifying Databases and Spreadsheets
Bendre, Mangesh; Sun, Bofan; Zhang, Ding; Zhou, Xinyan; Chang, Kevin ChenChuan; Parameswaran, Aditya
2015-01-01
Spreadsheet software is often the tool of choice for ad-hoc tabular data management, processing, and visualization, especially on tiny data sets. On the other hand, relational database systems offer significant power, expressivity, and efficiency over spreadsheet software for data management, while lacking in the ease of use and ad-hoc analysis capabilities. We demonstrate DataSpread, a data exploration tool that holistically unifies databases and spreadsheets. It continues to offer a Microsoft Excel-based spreadsheet front-end, while in parallel managing all the data in a back-end database, specifically, PostgreSQL. DataSpread retains all the advantages of spreadsheets, including ease of use, ad-hoc analysis and visualization capabilities, and a schema-free nature, while also adding the advantages of traditional relational databases, such as scalability and the ability to use arbitrary SQL to import, filter, or join external or internal tables and have the results appear in the spreadsheet. DataSpread needs to reason about and reconcile differences in the notions of schema, addressing of cells and tuples, and the current “pane” (which exists in spreadsheets but not in traditional databases), and support data modifications at both the front-end and the back-end. Our demonstration will center on our first and early prototype of the DataSpread, and will give the attendees a sense for the enormous data exploration capabilities offered by unifying spreadsheets and databases. PMID:26900487
Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun
2017-01-04
Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.
Compressive Sampling based Image Coding for Resource-deficient Visual Communication.
Liu, Xianming; Zhai, Deming; Zhou, Jiantao; Zhang, Xinfeng; Zhao, Debin; Gao, Wen
2016-04-14
In this paper, a new compressive sampling based image coding scheme is developed to achieve competitive coding efficiency at lower encoder computational complexity, while supporting error resilience. This technique is particularly suitable for visual communication with resource-deficient devices. At the encoder, compact image representation is produced, which is a polyphase down-sampled version of the input image; but the conventional low-pass filter prior to down-sampling is replaced by a local random binary convolution kernel. The pixels of the resulting down-sampled pre-filtered image are local random measurements and placed in the original spatial configuration. The advantages of local random measurements are two folds: 1) preserve high-frequency image features that are otherwise discarded by low-pass filtering; 2) remain a conventional image and can therefore be coded by any standardized codec to remove statistical redundancy of larger scales. Moreover, measurements generated by different kernels can be considered as multiple descriptions of the original image and therefore the proposed scheme has the advantage of multiple description coding. At the decoder, a unified sparsity-based soft-decoding technique is developed to recover the original image from received measurements in a framework of compressive sensing. Experimental results demonstrate that the proposed scheme is competitive compared with existing methods, with a unique strength of recovering fine details and sharp edges at low bit-rates.
Simione, Luca; Raffone, Antonino; Wolters, Gezinus; Salmas, Paola; Nakatani, Chie; Belardinelli, Marta Olivetti; van Leeuwen, Cees
2012-10-01
Two separate lines of study have clarified the role of selectivity in conscious access to visual information. Both involve presenting multiple targets and distracters: one simultaneously in a spatially distributed fashion, the other sequentially at a single location. To understand their findings in a unified framework, we propose a neurodynamic model for Visual Selection and Awareness (ViSA). ViSA supports the view that neural representations for conscious access and visuo-spatial working memory are globally distributed and are based on recurrent interactions between perceptual and access control processors. Its flexible global workspace mechanisms enable a unitary account of a broad range of effects: It accounts for the limited storage capacity of visuo-spatial working memory, attentional cueing, and efficient selection with multi-object displays, as well as for the attentional blink and associated sparing and masking effects. In particular, the speed of consolidation for storage in visuo-spatial working memory in ViSA is not fixed but depends adaptively on the input and recurrent signaling. Slowing down of consolidation due to weak bottom-up and recurrent input as a result of brief presentation and masking leads to the attentional blink. Thus, ViSA goes beyond earlier 2-stage and neuronal global workspace accounts of conscious processing limitations. PsycINFO Database Record (c) 2012 APA, all rights reserved.
Hybrid region merging method for segmentation of high-resolution remote sensing images
NASA Astrophysics Data System (ADS)
Zhang, Xueliang; Xiao, Pengfeng; Feng, Xuezhi; Wang, Jiangeng; Wang, Zuo
2014-12-01
Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images. HRM integrates the advantages of global-oriented and local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect the local context, as compared with the global-oriented method. A set of high-resolution remote sensing images is used to test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single regions better than MRS, and the supervised and unsupervised evaluation results further prove the superiority of HRM.
Chimaera simulation of complex states of flowing matter
2016-01-01
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro–meso–micro levels through suitable ‘mutations’ of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows. This article is part of the themed issue ‘Multiscale modelling at the physics–chemistry–biology interface’. PMID:27698031
Ethier, J-F; Curcin, V; Barton, A; McGilchrist, M M; Bastiaens, H; Andreasson, A; Rossiter, J; Zhao, L; Arvanitis, T N; Taweel, A; Delaney, B C; Burgun, A
2015-01-01
This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Primary care data is the single richest source of routine health care data. However its use, both in research and clinical work, often requires data from multiple clinical sites, clinical trials databases and registries. Data integration and interoperability are therefore of utmost importance. TRANSFoRm's general approach relies on a unified interoperability framework, described in a previous paper. We developed a core ontology for an interoperability framework based on data mediation. This article presents how such an ontology, the Clinical Data Integration Model (CDIM), can be designed to support, in conjunction with appropriate terminologies, biomedical data federation within TRANSFoRm, an EU FP7 project that aims to develop the digital infrastructure for a learning healthcare system in European Primary Care. TRANSFoRm utilizes a unified structural / terminological interoperability framework, based on the local-as-view mediation paradigm. Such an approach mandates the global information model to describe the domain of interest independently of the data sources to be explored. Following a requirement analysis process, no ontology focusing on primary care research was identified and, thus we designed a realist ontology based on Basic Formal Ontology to support our framework in collaboration with various terminologies used in primary care. The resulting ontology has 549 classes and 82 object properties and is used to support data integration for TRANSFoRm's use cases. Concepts identified by researchers were successfully expressed in queries using CDIM and pertinent terminologies. As an example, we illustrate how, in TRANSFoRm, the Query Formulation Workbench can capture eligibility criteria in a computable representation, which is based on CDIM. A unified mediation approach to semantic interoperability provides a flexible and extensible framework for all types of interaction between health record systems and research systems. CDIM, as core ontology of such an approach, enables simplicity and consistency of design across the heterogeneous software landscape and can support the specific needs of EHR-driven phenotyping research using primary care data.
Pinto, Rogério M; da Silva, Sueli Bulhões; Soriano, Rafaela
2012-03-01
Community health workers (CHWs) play a pivotal role in primary care, serving as liaisons between community members and medical providers. However, the growing reliance of health care systems worldwide on CHWs has outpaced research explaining their praxis - how they combine indigenous and technical knowledge, overcome challenges and impact patient outcomes. This paper thus articulates the CHW Praxis and Patient Health Behavior Framework. Such a framework is needed to advance research on CHW impact on patient outcomes and to advance CHW training. The project that originated this framework followed community-based participatory research principles. A team of U.S.-Brazil research partners, including CHWs, worked together from conceptualization of the study to dissemination of its findings. The framework is built on an integrated conceptual foundation including learning/teaching and individual behavior theories. The empirical base of the framework comprises in-depth interviews with 30 CHWs in Brazil's Unified Health System, Mesquita, Rio de Janeiro. Data collection for the project which originated this report occurred in 2008-10. Semi-structured questions examined how CHWs used their knowledge/skills; addressed personal and environmental challenges; and how they promoted patient health behaviors. This study advances an explanation of how CHWs use self-identified strategies--i.e., empathic communication and perseverance--to help patients engage in health behaviors. Grounded in our proposed framework, survey measures can be developed and used in predictive models testing the effects of CHW praxis on health behaviors. Training for CHWs can explicitly integrate indigenous and technical knowledge in order for CHWs to overcome contextual challenges and enhance service delivery. Copyright © 2012 Elsevier Ltd. All rights reserved.
Pinto, Rogério M.; da Silva, Sueli Bulhões; Soriano, Rafaela
2012-01-01
Community Health Workers (CHWs) play a pivotal role in primary care, serving as liaisons between community members and medical providers. However, the growing reliance of health care systems worldwide on CHWs has outpaced research explaining their praxis – how they combine indigenous and technical knowledge, overcome challenges and impact patient outcomes. This paper thus articulates the CHW Praxis and Patient Health Behavior Framework. Such a framework is needed to advance research on CHW impact on patient outcomes and to advance CHW training. The project that originated this framework followed Community-Based Participatory Research principles. A team of U.S.-Brazil research partners, including CHWs, worked together from conceptualization of the study to dissemination of its findings. The framework is built on an integrated conceptual foundation including learning/teaching and individual behavior theories. The empirical base of the framework comprises in-depth interviews with 30 CHWs in Brazil's Unified Health System, Mesquita, Rio de Janeiro. Data collection for the project which originated this report occurred in 2008–10. Semi-structured questions examined how CHWs used their knowledge/skills; addressed personal and environmental challenges; and how they promoted patient health behaviors. This study advances an explanation of how CHWs use self-identified strategies – i.e., empathic communication and perseverance – to help patients engage in health behaviors. Grounded in our proposed framework, survey measures can be developed and used in predictive models testing the effects of CHW praxis on health behaviors. Training for CHWs can explicitly integrate indigenous and technical knowledge in order for CHWs to overcome contextual challenges and enhance service delivery. PMID:22305469
SSBRP Communication & Data System Development using the Unified Modeling Language (UML)
NASA Technical Reports Server (NTRS)
Windrem, May; Picinich, Lou; Givens, John J. (Technical Monitor)
1998-01-01
The Unified Modeling Language (UML) is the standard method for specifying, visualizing, and documenting the artifacts of an object-oriented system under development. UML is the unification of the object-oriented methods developed by Grady Booch and James Rumbaugh, and of the Use Case Model developed by Ivar Jacobson. This paper discusses the application of UML by the Communications and Data Systems (CDS) team to model the ground control and command of the Space Station Biological Research Project (SSBRP) User Operations Facility (UOF). UML is used to define the context of the system, the logical static structure, the life history of objects, and the interactions among objects.
Testing a Conceptual Change Model Framework for Visual Data
ERIC Educational Resources Information Center
Finson, Kevin D.; Pedersen, Jon E.
2015-01-01
An emergent data analysis technique was employed to test the veracity of a conceptual framework constructed around visual data use and instruction in science classrooms. The framework incorporated all five key components Vosniadou (2007a, 2007b) described as existing in a learner's schema: framework theory, presuppositions, conceptual domains,…
A framework to monitor activities of satellite data processing in real-time
NASA Astrophysics Data System (ADS)
Nguyen, M. D.; Kryukov, A. P.
2018-01-01
Space Monitoring Data Center (SMDC) of SINP MSU is one of the several centers in the world that collects data on the radiational conditions in near-Earth orbit from various Russian (Lomonosov, Electro-L1, Electro-L2, Meteor-M1, Meteor-M2, etc.) and foreign (GOES 13, GOES 15, ACE, SDO, etc.) satellites. The primary purposes of SMDC are: aggregating heterogeneous data from different sources; providing a unified interface for data retrieval, visualization, analysis, as well as development and testing new space weather models; and controlling the correctness and completeness of data. Space weather models rely on data provided by SMDC to produce forecasts. Therefore, monitoring the whole data processing cycle is crucial for further success in the modeling of physical processes in near-Earth orbit based on the collected data. To solve the problem described above, we have developed a framework called Live Monitor at SMDC. Live Monitor allows watching all stages and program components involved in each data processing cycle. All activities of each stage are logged by Live Monitor and shown in real-time on a web interface. When an error occurs, a notification message will be sent to satellite operators via email and the Telegram messenger service so that they could take measures in time. The Live Monitor’s API can be used to create a customized monitoring service with minimum coding.
NASA Astrophysics Data System (ADS)
Curtis, Christopher; Lenzo, Matthew; McClure, Matthew; Preiss, Bruce
2010-04-01
In order to anticipate the constantly changing landscape of global warfare, the United States Air Force must acquire new capabilities in the field of Intelligence, Surveillance, and Reconnaissance (ISR). To meet this challenge, the Air Force Research Laboratory (AFRL) is developing a unifying construct of "Layered Sensing" which will provide military decision-makers at all levels with the timely, actionable, and trusted information necessary for complete battlespace awareness. Layered Sensing is characterized by the appropriate combination of sensors and platforms (including those for persistent sensing), infrastructure, and exploitation capabilities to enable this synergistic awareness. To achieve the Layered Sensing vision, AFRL is pursuing a Modeling & Simulation (M&S) strategy through the Layered Sensing Operations Center (LSOC). An experimental ISR system-of-systems test-bed, the LSOC integrates DoD standard simulation tools with commercial, off-the-shelf video game technology for rapid scenario development and visualization. These tools will help facilitate sensor management performance characterization, system development, and operator behavioral analysis. Flexible and cost-effective, the LSOC will implement a non-proprietary, open-architecture framework with well-defined interfaces. This framework will incentivize the transition of current ISR performance models to service-oriented software design for maximum re-use and consistency. This paper will present the LSOC's development and implementation thus far as well as a summary of lessons learned and future plans for the LSOC.
Charras, Guillaume T; Mitchison, Timothy J; Mahadevan, L
2009-09-15
Water is the dominant ingredient of cells and its dynamics are crucial to life. We and others have suggested a physical picture of the cell as a soft, fluid-infiltrated sponge, surrounded by a water-permeable barrier. To understand water movements in an animal cell, we imposed an external, inhomogeneous osmotic stress on cultured cancer cells. This forced water through the membrane on one side, and out on the other. Inside the cell, it created a gradient in hydration, that we visualized by tracking cellular responses using natural organelles and artificially introduced quantum dots. The dynamics of these markers at short times were the same for normal and metabolically poisoned cells, indicating that the cellular responses are primarily physical rather than chemical. Our finding of an internal gradient in hydration is inconsistent with a continuum model for cytoplasm, but consistent with the sponge model, and implies that the effective pore size of the sponge is small enough to retard water flow significantly on time scales ( approximately 10-100 seconds) relevant to cell physiology. We interpret these data in terms of a theoretical framework that combines mechanics and hydraulics in a multiphase poroelastic description of the cytoplasm and explains the experimentally observed dynamics quantitatively in terms of a few coarse-grained parameters that are based on microscopically measurable structural, hydraulic and mechanical properties. Our fluid-filled sponge model could provide a unified framework to understand a number of disparate observations in cell morphology and motility.
Clark, Jeremy; Cooper, Colin S; Mills, Robert; Rayward-Smith, Victor J; de la Iglesia, Beatriz
2015-01-01
Background Routinely collected data in hospitals is complex, typically heterogeneous, and scattered across multiple Hospital Information Systems (HIS). This big data, created as a byproduct of health care activities, has the potential to provide a better understanding of diseases, unearth hidden patterns, and improve services and cost. The extent and uses of such data rely on its quality, which is not consistently checked, nor fully understood. Nevertheless, using routine data for the construction of data-driven clinical pathways, describing processes and trends, is a key topic receiving increasing attention in the literature. Traditional algorithms do not cope well with unstructured processes or data, and do not produce clinically meaningful visualizations. Supporting systems that provide additional information, context, and quality assurance inspection are needed. Objective The objective of the study is to explore how routine hospital data can be used to develop data-driven pathways that describe the journeys that patients take through care, and their potential uses in biomedical research; it proposes a framework for the construction, quality assessment, and visualization of patient pathways for clinical studies and decision support using a case study on prostate cancer. Methods Data pertaining to prostate cancer patients were extracted from a large UK hospital from eight different HIS, validated, and complemented with information from the local cancer registry. Data-driven pathways were built for each of the 1904 patients and an expert knowledge base, containing rules on the prostate cancer biomarker, was used to assess the completeness and utility of the pathways for a specific clinical study. Software components were built to provide meaningful visualizations for the constructed pathways. Results The proposed framework and pathway formalism enable the summarization, visualization, and querying of complex patient-centric clinical information, as well as the computation of quality indicators and dimensions. A novel graphical representation of the pathways allows the synthesis of such information. Conclusions Clinical pathways built from routinely collected hospital data can unearth information about patients and diseases that may otherwise be unavailable or overlooked in hospitals. Data-driven clinical pathways allow for heterogeneous data (ie, semistructured and unstructured data) to be collated over a unified data model and for data quality dimensions to be assessed. This work has enabled further research on prostate cancer and its biomarkers, and on the development and application of methods to mine, compare, analyze, and visualize pathways constructed from routine data. This is an important development for the reuse of big data in hospitals. PMID:26162314
DOE Office of Scientific and Technical Information (OSTI.GOV)
Machnes, S.; Institute for Theoretical Physics, University of Ulm, D-89069 Ulm; Sander, U.
2011-08-15
For paving the way to novel applications in quantum simulation, computation, and technology, increasingly large quantum systems have to be steered with high precision. It is a typical task amenable to numerical optimal control to turn the time course of pulses, i.e., piecewise constant control amplitudes, iteratively into an optimized shape. Here, we present a comparative study of optimal-control algorithms for a wide range of finite-dimensional applications. We focus on the most commonly used algorithms: GRAPE methods which update all controls concurrently, and Krotov-type methods which do so sequentially. Guidelines for their use are given and open research questions aremore » pointed out. Moreover, we introduce a unifying algorithmic framework, DYNAMO (dynamic optimization platform), designed to provide the quantum-technology community with a convenient matlab-based tool set for optimal control. In addition, it gives researchers in optimal-control techniques a framework for benchmarking and comparing newly proposed algorithms with the state of the art. It allows a mix-and-match approach with various types of gradients, update and step-size methods as well as subspace choices. Open-source code including examples is made available at http://qlib.info.« less
Papadimitriou, Konstantinos I.; Liu, Shih-Chii; Indiveri, Giacomo; Drakakis, Emmanuel M.
2014-01-01
The field of neuromorphic silicon synapse circuits is revisited and a parsimonious mathematical framework able to describe the dynamics of this class of log-domain circuits in the aggregate and in a systematic manner is proposed. Starting from the Bernoulli Cell Formalism (BCF), originally formulated for the modular synthesis and analysis of externally linear, time-invariant logarithmic filters, and by means of the identification of new types of Bernoulli Cell (BC) operators presented here, a generalized formalism (GBCF) is established. The expanded formalism covers two new possible and practical combinations of a MOS transistor (MOST) and a linear capacitor. The corresponding mathematical relations codifying each case are presented and discussed through the tutorial treatment of three well-known transistor-level examples of log-domain neuromorphic silicon synapses. The proposed mathematical tool unifies past analysis approaches of the same circuits under a common theoretical framework. The speed advantage of the proposed mathematical framework as an analysis tool is also demonstrated by a compelling comparative circuit analysis example of high order, where the GBCF and another well-known log-domain circuit analysis method are used for the determination of the input-output transfer function of the high (4th) order topology. PMID:25653579
NASA Technical Reports Server (NTRS)
2005-01-01
A number of titanium matrix composite (TMC) systems are currently being investigated for high-temperature air frame and propulsion system applications. As a result, numerous computational methodologies for predicting both deformation and life for this class of materials are under development. An integral part of these methodologies is an accurate and computationally efficient constitutive model for the metallic matrix constituent. Furthermore, because these systems are designed to operate at elevated temperatures, the required constitutive models must account for both time-dependent and time-independent deformations. To accomplish this, the NASA Lewis Research Center is employing a recently developed, complete, potential-based framework. This framework, which utilizes internal state variables, was put forth for the derivation of reversible and irreversible constitutive equations. The framework, and consequently the resulting constitutive model, is termed complete because the existence of the total (integrated) form of the Gibbs complementary free energy and complementary dissipation potentials are assumed a priori. The specific forms selected here for both the Gibbs and complementary dissipation potentials result in a fully associative, multiaxial, nonisothermal, unified viscoplastic model with nonlinear kinematic hardening. This model constitutes one of many models in the Generalized Viscoplasticity with Potential Structure (GVIPS) class of inelastic constitutive equations.
Papadimitriou, Konstantinos I; Liu, Shih-Chii; Indiveri, Giacomo; Drakakis, Emmanuel M
2014-01-01
The field of neuromorphic silicon synapse circuits is revisited and a parsimonious mathematical framework able to describe the dynamics of this class of log-domain circuits in the aggregate and in a systematic manner is proposed. Starting from the Bernoulli Cell Formalism (BCF), originally formulated for the modular synthesis and analysis of externally linear, time-invariant logarithmic filters, and by means of the identification of new types of Bernoulli Cell (BC) operators presented here, a generalized formalism (GBCF) is established. The expanded formalism covers two new possible and practical combinations of a MOS transistor (MOST) and a linear capacitor. The corresponding mathematical relations codifying each case are presented and discussed through the tutorial treatment of three well-known transistor-level examples of log-domain neuromorphic silicon synapses. The proposed mathematical tool unifies past analysis approaches of the same circuits under a common theoretical framework. The speed advantage of the proposed mathematical framework as an analysis tool is also demonstrated by a compelling comparative circuit analysis example of high order, where the GBCF and another well-known log-domain circuit analysis method are used for the determination of the input-output transfer function of the high (4(th)) order topology.
Classical Markov Chains: A Unifying Framework for Understanding Avian Reproductive Success
Traditional methods for monitoring and analysis of avian nesting success have several important shortcomings, including 1) inability to handle multiple classes of nest failure, and 2) inability to provide estimates of annual reproductive success (because birds can, and typically ...
Do changes in connectivity explain desertification?
USDA-ARS?s Scientific Manuscript database
Desertification, broad-scale land degradation in drylands, is a major environmental hazard facing inhabitants of the world’s deserts as well as an important component of global change. There is no unifying framework that simply and effectively explains different forms of desertification. Here we arg...
MultiSeq: unifying sequence and structure data for evolutionary analysis
Roberts, Elijah; Eargle, John; Wright, Dan; Luthey-Schulten, Zaida
2006-01-01
Background Since the publication of the first draft of the human genome in 2000, bioinformatic data have been accumulating at an overwhelming pace. Currently, more than 3 million sequences and 35 thousand structures of proteins and nucleic acids are available in public databases. Finding correlations in and between these data to answer critical research questions is extremely challenging. This problem needs to be approached from several directions: information science to organize and search the data; information visualization to assist in recognizing correlations; mathematics to formulate statistical inferences; and biology to analyze chemical and physical properties in terms of sequence and structure changes. Results Here we present MultiSeq, a unified bioinformatics analysis environment that allows one to organize, display, align and analyze both sequence and structure data for proteins and nucleic acids. While special emphasis is placed on analyzing the data within the framework of evolutionary biology, the environment is also flexible enough to accommodate other usage patterns. The evolutionary approach is supported by the use of predefined metadata, adherence to standard ontological mappings, and the ability for the user to adjust these classifications using an electronic notebook. MultiSeq contains a new algorithm to generate complete evolutionary profiles that represent the topology of the molecular phylogenetic tree of a homologous group of distantly related proteins. The method, based on the multidimensional QR factorization of multiple sequence and structure alignments, removes redundancy from the alignments and orders the protein sequences by increasing linear dependence, resulting in the identification of a minimal basis set of sequences that spans the evolutionary space of the homologous group of proteins. Conclusion MultiSeq is a major extension of the Multiple Alignment tool that is provided as part of VMD, a structural visualization program for analyzing molecular dynamics simulations. Both are freely distributed by the NIH Resource for Macromolecular Modeling and Bioinformatics and MultiSeq is included with VMD starting with version 1.8.5. The MultiSeq website has details on how to download and use the software: PMID:16914055
Cho, Kwang-Hyun; Choo, Sang-Mok; Wellstead, Peter; Wolkenhauer, Olaf
2005-08-15
We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.
Real-time tracking of visually attended objects in virtual environments and its application to LOD.
Lee, Sungkil; Kim, Gerard Jounghyun; Choi, Seungmoon
2009-01-01
This paper presents a real-time framework for computationally tracking objects visually attended by the user while navigating in interactive virtual environments. In addition to the conventional bottom-up (stimulus-driven) saliency map, the proposed framework uses top-down (goal-directed) contexts inferred from the user's spatial and temporal behaviors, and identifies the most plausibly attended objects among candidates in the object saliency map. The computational framework was implemented using GPU, exhibiting high computational performance adequate for interactive virtual environments. A user experiment was also conducted to evaluate the prediction accuracy of the tracking framework by comparing objects regarded as visually attended by the framework to actual human gaze collected with an eye tracker. The results indicated that the accuracy was in the level well supported by the theory of human cognition for visually identifying single and multiple attentive targets, especially owing to the addition of top-down contextual information. Finally, we demonstrate how the visual attention tracking framework can be applied to managing the level of details in virtual environments, without any hardware for head or eye tracking.
The Cooperate Assistive Teamwork Environment for Software Description Languages.
Groenda, Henning; Seifermann, Stephan; Müller, Karin; Jaworek, Gerhard
2015-01-01
Versatile description languages such as the Unified Modeling Language (UML) are commonly used in software engineering across different application domains in theory and practice. They often use graphical notations and leverage visual memory for expressing complex relations. Those notations are hard to access for people with visual impairment and impede their smooth inclusion in an engineering team. Existing approaches provide textual notations but require manual synchronization between the notations. This paper presents requirements for an accessible and language-aware team work environment as well as our plan for the assistive implementation of Cooperate. An industrial software engineering team consisting of people with and without visual impairment will evaluate the implementation.
Wolfrum, Ed (ORCID:0000000273618931); Knoshug, Eric (ORCID:000000025709914X); Laurens, Lieve (ORCID:0000000349303267); Harmon, Valerie; Dempster, Thomas (ORCID:000000029550488X); McGowan, John (ORCID:0000000266920518); Rosov, Theresa; Cardello, David; Arrowsmith, Sarah; Kempkes, Sarah; Bautista, Maria; Lundquist, Tryg; Crowe, Brandon; Murawsky, Garrett; Nicolai, Eric; Rowe, Egan; Knurek, Emily; Javar, Reyna; Saracco Alvarez, Marcela; Schlosser, Steve; Riddle, Mary; Withstandley, Chris; Chen, Yongsheng; Van Ginkel, Steven; Igou, Thomas; Xu, Chunyan; Hu, Zixuan
2017-10-20
ATP3 Unified Field Study Data The Algae Testbed Public-Private Partnership (ATP3) was established with the goal of investigating open pond algae cultivation across different geographic, climatic, seasonal, and operational conditions while setting the benchmark for quality data collection, analysis, and dissemination. Identical algae cultivation systems and data analysis methodologies were established at testbed sites across the continental United States and Hawaii. Within this framework, the Unified Field Studies (UFS) were designed to characterize the cultivation of different algal strains during all 4 seasons across this testbed network. The dataset presented here is the complete, curated, climatic, cultivation, harvest, and biomass composition data for each season at each site. These data enable others to do in-depth cultivation, harvest, techno-economic, life cycle, resource, and predictive growth modeling analysis, as well as develop crop protection strategies for the nascent algae industry. NREL Sub award Number: DE-AC36-08-GO28308
A Unified Methodology for Computing Accurate Quaternion Color Moments and Moment Invariants.
Karakasis, Evangelos G; Papakostas, George A; Koulouriotis, Dimitrios E; Tourassis, Vassilios D
2014-02-01
In this paper, a general framework for computing accurate quaternion color moments and their corresponding invariants is proposed. The proposed unified scheme arose by studying the characteristics of different orthogonal polynomials. These polynomials are used as kernels in order to form moments, the invariants of which can easily be derived. The resulted scheme permits the usage of any polynomial-like kernel in a unified and consistent way. The resulted moments and moment invariants demonstrate robustness to noisy conditions and high discriminative power. Additionally, in the case of continuous moments, accurate computations take place to avoid approximation errors. Based on this general methodology, the quaternion Tchebichef, Krawtchouk, Dual Hahn, Legendre, orthogonal Fourier-Mellin, pseudo Zernike and Zernike color moments, and their corresponding invariants are introduced. A selected paradigm presents the reconstruction capability of each moment family, whereas proper classification scenarios evaluate the performance of color moment invariants.
NASA Astrophysics Data System (ADS)
Codello, Alessandro; Jain, Rajeev Kumar
2018-05-01
We present a unified evolution of the universe from very early times until the present epoch by including both the leading local correction R^2 and the leading non-local term R1/\\square ^2R to the classical gravitational action. We find that the inflationary phase driven by R^2 term gracefully exits in a transitory regime characterized by coherent oscillations of the Hubble parameter. The universe then naturally enters into a radiation dominated epoch followed by a matter dominated era. At sufficiently late times after radiation-matter equality, the non-local term starts to dominate inducing an accelerated expansion of the universe at the present epoch. We further exhibit the fact that both the leading local and non-local terms can be obtained within the covariant effective field theory of gravity. This scenario thus provides a unified picture of inflation and dark energy in a single framework by means of a purely gravitational action without the usual need of a scalar field.
Multilayer network of language: A unified framework for structural analysis of linguistic subsystems
NASA Astrophysics Data System (ADS)
Martinčić-Ipšić, Sanda; Margan, Domagoj; Meštrović, Ana
2016-09-01
Recently, the focus of complex networks' research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena - multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax and co-occurrence) and a subword-level (syllables and graphemes) network layers, from four variations of original text (in the modeled language). The analysis and comparison of layers at the word and subword-levels are employed in order to determine the mechanism of the structural influences between linguistic units and subsystems. The obtained results suggest that there are substantial differences between the networks' structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword-level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems simultaneously and hence to provide a more unified view on language.
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example. PMID:23515190
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
Robust stabilization and environmental disturbance attenuation are ubiquitous systematic properties that are observed in biological systems at many different levels. The underlying principles for robust stabilization and environmental disturbance attenuation are universal to both complex biological systems and sophisticated engineering systems. In many biological networks, network robustness should be large enough to confer: intrinsic robustness for tolerating intrinsic parameter fluctuations; genetic robustness for buffering genetic variations; and environmental robustness for resisting environmental disturbances. Network robustness is needed so phenotype stability of biological network can be maintained, guaranteeing phenotype robustness. Synthetic biology is foreseen to have important applications in biotechnology and medicine; it is expected to contribute significantly to a better understanding of functioning of complex biological systems. This paper presents a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance attenuation for synthetic gene networks in synthetic biology. Further, from the unifying mathematical framework, we found that the phenotype robustness criterion for synthetic gene networks is the following: if intrinsic robustness + genetic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations, genetic variations, and environmental disturbances. Therefore, the trade-offs between intrinsic robustness, genetic robustness, environmental robustness, and network robustness in synthetic biology can also be investigated through corresponding phenotype robustness criteria from the systematic point of view. Finally, a robust synthetic design that involves network evolution algorithms with desired behavior under intrinsic parameter fluctuations, genetic variations, and environmental disturbances, is also proposed, together with a simulation example.
Spatial and temporal coherence in perceptual binding
Blake, Randolph; Yang, Yuede
1997-01-01
Component visual features of objects are registered by distributed patterns of activity among neurons comprising multiple pathways and visual areas. How these distributed patterns of activity give rise to unified representations of objects remains unresolved, although one recent, controversial view posits temporal coherence of neural activity as a binding agent. Motivated by the possible role of temporal coherence in feature binding, we devised a novel psychophysical task that requires the detection of temporal coherence among features comprising complex visual images. Results show that human observers can more easily detect synchronized patterns of temporal contrast modulation within hybrid visual images composed of two components when those components are drawn from the same original picture. Evidently, time-varying changes within spatially coherent features produce more salient neural signals. PMID:9192701
NASA Technical Reports Server (NTRS)
1978-01-01
A unified framework for comparing intercity passenger and freight transportation systems is presented. Composite measures for cost, service/demand, energy, and environmental impact were determined. A set of 14 basic measures were articulated to form the foundation for computing the composite measures. A parameter dependency diagram, constructed to explicitly interrelate the composite and basic measures is discussed. Ground rules and methodology for developing the values of the basic measures are provided and the use of the framework with existing cost and service data is illustrated for various freight systems.
NASA Astrophysics Data System (ADS)
Perfors, Amy
2014-09-01
There is much to approve of in this provocative and interesting paper. I strongly agree in many parts, especially the point that dichotomies like nature/nurture are actively detrimental to the field. I also appreciate the idea that cognitive scientists should take the "biological wetware" of the cell (rather than the network) more seriously.
Chimaera simulation of complex states of flowing matter.
Succi, S
2016-11-13
We discuss a unified mesoscale framework (chimaera) for the simulation of complex states of flowing matter across scales of motion. The chimaera framework can deal with each of the three macro-meso-micro levels through suitable 'mutations' of the basic mesoscale formulation. The idea is illustrated through selected simulations of complex micro- and nanoscale flows.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).
A unified framework for gesture recognition and spatiotemporal gesture segmentation.
Alon, Jonathan; Athitsos, Vassilis; Yuan, Quan; Sclaroff, Stan
2009-09-01
Within the context of hand gesture recognition, spatiotemporal gesture segmentation is the task of determining, in a video sequence, where the gesturing hand is located and when the gesture starts and ends. Existing gesture recognition methods typically assume either known spatial segmentation or known temporal segmentation, or both. This paper introduces a unified framework for simultaneously performing spatial segmentation, temporal segmentation, and recognition. In the proposed framework, information flows both bottom-up and top-down. A gesture can be recognized even when the hand location is highly ambiguous and when information about when the gesture begins and ends is unavailable. Thus, the method can be applied to continuous image streams where gestures are performed in front of moving, cluttered backgrounds. The proposed method consists of three novel contributions: a spatiotemporal matching algorithm that can accommodate multiple candidate hand detections in every frame, a classifier-based pruning framework that enables accurate and early rejection of poor matches to gesture models, and a subgesture reasoning algorithm that learns which gesture models can falsely match parts of other longer gestures. The performance of the approach is evaluated on two challenging applications: recognition of hand-signed digits gestured by users wearing short-sleeved shirts, in front of a cluttered background, and retrieval of occurrences of signs of interest in a video database containing continuous, unsegmented signing in American Sign Language (ASL).
14 CFR 1221.108 - Establishment of the NASA Unified Visual Communications System.
Code of Federal Regulations, 2013 CFR
2013-01-01
... forward-looking image through the use of effective design for improved communications. The system provides a professional and cohesive NASA identity by imparting continuity of graphics design in all layout... developed under the Federal Design Improvement Program initiated by the President in May 1972. This system...
14 CFR 1221.108 - Establishment of the NASA Unified Visual Communications System.
Code of Federal Regulations, 2011 CFR
2011-01-01
... forward-looking image through the use of effective design for improved communications. The system provides a professional and cohesive NASA identity by imparting continuity of graphics design in all layout... developed under the Federal Design Improvement Program initiated by the President in May 1972. This system...
14 CFR § 1221.105 - Establishment of NASA Program Identifiers.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Establishment of NASA Program Identifiers... THE NASA SEAL AND OTHER DEVICES, AND THE CONGRESSIONAL SPACE MEDAL OF HONOR NASA Seal, NASA Insignia, NASA Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications...
Efficient threshold for volumetric segmentation
NASA Astrophysics Data System (ADS)
Burdescu, Dumitru D.; Brezovan, Marius; Stanescu, Liana; Stoica Spahiu, Cosmin; Ebanca, Daniel
2015-07-01
Image segmentation plays a crucial role in effective understanding of digital images. However, the research on the existence of general purpose segmentation algorithm that suits for variety of applications is still very much active. Among the many approaches in performing image segmentation, graph based approach is gaining popularity primarily due to its ability in reflecting global image properties. Volumetric image segmentation can simply result an image partition composed by relevant regions, but the most fundamental challenge in segmentation algorithm is to precisely define the volumetric extent of some object, which may be represented by the union of multiple regions. The aim in this paper is to present a new method to detect visual objects from color volumetric images and efficient threshold. We present a unified framework for volumetric image segmentation and contour extraction that uses a virtual tree-hexagonal structure defined on the set of the image voxels. The advantage of using a virtual tree-hexagonal network superposed over the initial image voxels is that it reduces the execution time and the memory space used, without losing the initial resolution of the image.
Robustness surfaces of complex networks
NASA Astrophysics Data System (ADS)
Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis
2014-09-01
Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.
Censor, N
2013-10-10
In both perceptual and motor learning, numerous studies have shown specificity of learning to the trained eye or hand and to the physical features of the task. However, generalization of learning is possible in both perceptual and motor domains. Here, I review evidence for perceptual and motor learning generalization, suggesting that generalization patterns are affected by the way in which the original memory is encoded and consolidated. Generalization may be facilitated during fast learning, with possible engagement of higher-order brain areas recurrently interacting with the primary visual or motor cortices encoding the stimuli or movements' memories. Such generalization may be supported by sleep, involving functional interactions between low and higher-order brain areas. Repeated exposure to the task may alter generalization patterns of learning and overall offline learning. Development of unifying frameworks across learning modalities and better understanding of the conditions under which learning can generalize may enable to gain insight regarding the neural mechanisms underlying procedural learning and have useful clinical implications. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.
Robustness surfaces of complex networks.
Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis
2014-09-02
Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared.
Data Centric Development Methodology
ERIC Educational Resources Information Center
Khoury, Fadi E.
2012-01-01
Data centric applications, an important effort of software development in large organizations, have been mostly adopting a software methodology, such as a waterfall or Rational Unified Process, as the framework for its development. These methodologies could work on structural, procedural, or object oriented based applications, but fails to capture…
The semiotics of medical image Segmentation.
Baxter, John S H; Gibson, Eli; Eagleson, Roy; Peters, Terry M
2018-02-01
As the interaction between clinicians and computational processes increases in complexity, more nuanced mechanisms are required to describe how their communication is mediated. Medical image segmentation in particular affords a large number of distinct loci for interaction which can act on a deep, knowledge-driven level which complicates the naive interpretation of the computer as a symbol processing machine. Using the perspective of the computer as dialogue partner, we can motivate the semiotic understanding of medical image segmentation. Taking advantage of Peircean semiotic traditions and new philosophical inquiry into the structure and quality of metaphors, we can construct a unified framework for the interpretation of medical image segmentation as a sign exchange in which each sign acts as an interface metaphor. This allows for a notion of finite semiosis, described through a schematic medium, that can rigorously describe how clinicians and computers interpret the signs mediating their interaction. Altogether, this framework provides a unified approach to the understanding and development of medical image segmentation interfaces. Copyright © 2017 Elsevier B.V. All rights reserved.
Complex networks as a unified framework for descriptive analysis and predictive modeling in climate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R
The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less
The thermodynamics of dense granular flow and jamming
NASA Astrophysics Data System (ADS)
Lu, Shih Yu
The scope of the thesis is to propose, based on experimental evidence and theoretical validation, a quantifiable connection between systems that exhibit the jamming phenomenon. When jammed, some materials that flow are able to resist deformation so that they appear solid-like on the laboratory scale. But unlike ordinary fusion, which has a critically defined criterion in pressure and temperature, jamming occurs under a wide range of conditions. These condition have been rigorously investigated but at the moment, no self-consistent framework can apply to grains, foam and colloids that may have suddenly ceased to flow. To quantify the jamming behavior, a constitutive model of dense granular flows is deduced from shear-flow experiments. The empirical equations are then generalized, via a thermodynamic approach, into an equation-of-state for jamming. Notably, the unifying theory also predicts the experimental data on the behavior of molecular glassy liquids. This analogy paves a crucial road map for a unifying theoretical framework in condensed matter, for example, ranging from sand to fire retardants to toothpaste.
Li, Bing; Yuan, Chunfeng; Xiong, Weihua; Hu, Weiming; Peng, Houwen; Ding, Xinmiao; Maybank, Steve
2017-12-01
In multi-instance learning (MIL), the relations among instances in a bag convey important contextual information in many applications. Previous studies on MIL either ignore such relations or simply model them with a fixed graph structure so that the overall performance inevitably degrades in complex environments. To address this problem, this paper proposes a novel multi-view multi-instance learning algorithm (MIL) that combines multiple context structures in a bag into a unified framework. The novel aspects are: (i) we propose a sparse -graph model that can generate different graphs with different parameters to represent various context relations in a bag, (ii) we propose a multi-view joint sparse representation that integrates these graphs into a unified framework for bag classification, and (iii) we propose a multi-view dictionary learning algorithm to obtain a multi-view graph dictionary that considers cues from all views simultaneously to improve the discrimination of the MIL. Experiments and analyses in many practical applications prove the effectiveness of the M IL.
Chen, Bor-Sen; Lin, Ying-Po
2013-01-01
In ecological networks, network robustness should be large enough to confer intrinsic robustness for tolerating intrinsic parameter fluctuations, as well as environmental robustness for resisting environmental disturbances, so that the phenotype stability of ecological networks can be maintained, thus guaranteeing phenotype robustness. However, it is difficult to analyze the network robustness of ecological systems because they are complex nonlinear partial differential stochastic systems. This paper develops a unifying mathematical framework for investigating the principles of both robust stabilization and environmental disturbance sensitivity in ecological networks. We found that the phenotype robustness criterion for ecological networks is that if intrinsic robustness + environmental robustness ≦ network robustness, then the phenotype robustness can be maintained in spite of intrinsic parameter fluctuations and environmental disturbances. These results in robust ecological networks are similar to that in robust gene regulatory networks and evolutionary networks even they have different spatial-time scales. PMID:23515112
Unified Computational Methods for Regression Analysis of Zero-Inflated and Bound-Inflated Data
Yang, Yan; Simpson, Douglas
2010-01-01
Bounded data with excess observations at the boundary are common in many areas of application. Various individual cases of inflated mixture models have been studied in the literature for bound-inflated data, yet the computational methods have been developed separately for each type of model. In this article we use a common framework for computing these models, and expand the range of models for both discrete and semi-continuous data with point inflation at the lower boundary. The quasi-Newton and EM algorithms are adapted and compared for estimation of model parameters. The numerical Hessian and generalized Louis method are investigated as means for computing standard errors after optimization. Correlated data are included in this framework via generalized estimating equations. The estimation of parameters and effectiveness of standard errors are demonstrated through simulation and in the analysis of data from an ultrasound bioeffect study. The unified approach enables reliable computation for a wide class of inflated mixture models and comparison of competing models. PMID:20228950
Domain Anomaly Detection in Machine Perception: A System Architecture and Taxonomy.
Kittler, Josef; Christmas, William; de Campos, Teófilo; Windridge, David; Yan, Fei; Illingworth, John; Osman, Magda
2014-05-01
We address the problem of anomaly detection in machine perception. The concept of domain anomaly is introduced as distinct from the conventional notion of anomaly used in the literature. We propose a unified framework for anomaly detection which exposes the multifaceted nature of anomalies and suggest effective mechanisms for identifying and distinguishing each facet as instruments for domain anomaly detection. The framework draws on the Bayesian probabilistic reasoning apparatus which clearly defines concepts such as outlier, noise, distribution drift, novelty detection (object, object primitive), rare events, and unexpected events. Based on these concepts we provide a taxonomy of domain anomaly events. One of the mechanisms helping to pinpoint the nature of anomaly is based on detecting incongruence between contextual and noncontextual sensor(y) data interpretation. The proposed methodology has wide applicability. It underpins in a unified way the anomaly detection applications found in the literature. To illustrate some of its distinguishing features, in here the domain anomaly detection methodology is applied to the problem of anomaly detection for a video annotation system.
US Army Research Laboratory Visualization Framework Architecture Document
2018-01-11
this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. Citation of...release; distribution is unlimited. 14. ABSTRACT Visualization of network science experimentation results is generally achieved using stovepipe...report documents the ARL Visualization Framework system design and specific details of its implementation. 15. SUBJECT TERMS visualization
Wang, Guoli; Ebrahimi, Nader
2014-01-01
Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H, such that V ∼ W H. It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H. In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data. PMID:25821345
A unifying retinex model based on non-local differential operators
NASA Astrophysics Data System (ADS)
Zosso, Dominique; Tran, Giang; Osher, Stanley
2013-02-01
In this paper, we present a unifying framework for retinex that is able to reproduce many of the existing retinex implementations within a single model. The fundamental assumption, as shared with many retinex models, is that the observed image is a multiplication between the illumination and the true underlying reflectance of the object. Starting from Morel's 2010 PDE model for retinex, where illumination is supposed to vary smoothly and where the reflectance is thus recovered from a hard-thresholded Laplacian of the observed image in a Poisson equation, we define our retinex model in similar but more general two steps. First, look for a filtered gradient that is the solution of an optimization problem consisting of two terms: The first term is a sparsity prior of the reflectance, such as the TV or H1 norm, while the second term is a quadratic fidelity prior of the reflectance gradient with respect to the observed image gradients. In a second step, since this filtered gradient almost certainly is not a consistent image gradient, we then look for a reflectance whose actual gradient comes close. Beyond unifying existing models, we are able to derive entirely novel retinex formulations by using more interesting non-local versions for the sparsity and fidelity prior. Hence we define within a single framework new retinex instances particularly suited for texture-preserving shadow removal, cartoon-texture decomposition, color and hyperspectral image enhancement.
Fallah, Parisa Nicole; Bernstein, Mark
2017-09-07
Access to adequate surgical care is limited globally, particularly in low- and middle-income countries (LMICs). To address this issue, surgeons are becoming increasingly involved in international surgical teaching collaborations (ISTCs), which include educational partnerships between surgical teams in high-income countries and those in LMICs. The purpose of this study is to determine a framework for unifying, systematizing, and improving the quality of ISTCs so that they can better address the global surgical need. A convenience sample of 68 surgeons, anesthesiologists, physicians, residents, nurses, academics, and administrators from the U.S., Canada, and Norway was used for the study. Participants all had some involvement in ISTCs and came from multiple specialties and institutions. Qualitative methodology was used, and participants were interviewed using a pre-determined set of open-ended questions. Data was gathered over two months either in-person, over the phone, or on Skype. Data was evaluated using thematic content analysis. To organize and systematize ISTCs, participants reported a need for a centralized/systematized process with designated leaders, a universal data bank of current efforts/progress, communication amongst involved parties, full-time administrative staff, dedicated funds, a scholarly approach, increased use of technology, and more research on needs and outcomes. By taking steps towards unifying and systematizing ISTCs, the quality of ISTCs can be improved. This could lead to an advancement in efforts to increase access to surgical care worldwide.
Devarajan, Karthik; Wang, Guoli; Ebrahimi, Nader
2015-04-01
Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H , such that V ∼ W H . It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H . In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data.
Hilltop supernatural inflation and SUSY unified models
NASA Astrophysics Data System (ADS)
Kohri, Kazunori; Lim, C. S.; Lin, Chia-Min; Mimura, Yukihiro
2014-01-01
In this paper, we consider high scale (100TeV) supersymmetry (SUSY) breaking and realize the idea of hilltop supernatural inflation in concrete particle physics models based on flipped-SU(5)and Pati-Salam models in the framework of supersymmetric grand unified theories (SUSY GUTs). The inflaton can be a flat direction including right-handed sneutrino and the waterfall field is a GUT Higgs. The spectral index is ns = 0.96 which fits very well with recent data by PLANCK satellite. There is no both thermal and non-thermal gravitino problems. Non-thermal leptogenesis can be resulted from the decay of right-handed sneutrino which plays (part of) the role of inflaton.
Emotion and the prefrontal cortex: An integrative review.
Dixon, Matthew L; Thiruchselvam, Ravi; Todd, Rebecca; Christoff, Kalina
2017-10-01
The prefrontal cortex (PFC) plays a critical role in the generation and regulation of emotion. However, we lack an integrative framework for understanding how different emotion-related functions are organized across the entire expanse of the PFC, as prior reviews have generally focused on specific emotional processes (e.g., decision making) or specific anatomical regions (e.g., orbitofrontal cortex). Additionally, psychological theories and neuroscientific investigations have proceeded largely independently because of the lack of a common framework. Here, we provide a comprehensive review of functional neuroimaging, electrophysiological, lesion, and structural connectivity studies on the emotion-related functions of 8 subregions spanning the entire PFC. We introduce the appraisal-by-content model, which provides a new framework for integrating the diverse range of empirical findings. Within this framework, appraisal serves as a unifying principle for understanding the PFC's role in emotion, while relative content-specialization serves as a differentiating principle for understanding the role of each subregion. A synthesis of data from affective, social, and cognitive neuroscience studies suggests that different PFC subregions are preferentially involved in assigning value to specific types of inputs: exteroceptive sensations, episodic memories and imagined future events, viscero-sensory signals, viscero-motor signals, actions, others' mental states (e.g., intentions), self-related information, and ongoing emotions. We discuss the implications of this integrative framework for understanding emotion regulation, value-based decision making, emotional salience, and refining theoretical models of emotion. This framework provides a unified understanding of how emotional processes are organized across PFC subregions and generates new hypotheses about the mechanisms underlying adaptive and maladaptive emotional functioning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Interprofessional Care and Collaborative Practice.
ERIC Educational Resources Information Center
Casto, R. Michael; And Others
This book provides materials for those learning about the dynamics, techniques, and potential of interprofessional collaboration in health care and human services professions. Eight case studies thread their way through most chapters to unify and illustrate the text. Part 1 addresses the theoretical framework that forms the basis for…
Mean Comparison: Manifest Variable versus Latent Variable
ERIC Educational Resources Information Center
Yuan, Ke-Hai; Bentler, Peter M.
2006-01-01
An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…
Unified Framework for Deriving Simultaneous Equation Algorithms for Water Distribution Networks
The known formulations for steady state hydraulics within looped water distribution networks are re-derived in terms of linear and non-linear transformations of the original set of partly linear and partly non-linear equations that express conservation of mass and energy. All of ...
Reconciling Time, Space and Function: A New Dorsal-Ventral Stream Model of Sentence Comprehension
ERIC Educational Resources Information Center
Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias
2013-01-01
We present a new dorsal-ventral stream framework for language comprehension which unifies basic neurobiological assumptions (Rauschecker & Scott, 2009) with a cross-linguistic neurocognitive sentence comprehension model (eADM; Bornkessel & Schlesewsky, 2006). The dissociation between (time-dependent) syntactic structure-building and…
Bring NASA Scientific Data into GIS
NASA Astrophysics Data System (ADS)
Xu, H.
2016-12-01
NASA's Earth Observation System (EOS) and many other missions produce data of huge volume and near real time which drives the research and understanding of climate change. Geographic Information System (GIS) is a technology used for the management, visualization and analysis of spatial data. Since it's inception in the 1960s, GIS has been applied to many fields at the city, state, national, and world scales. People continue to use it today to analyze and visualize trends, patterns, and relationships from the massive datasets of scientific data. There is great interest in both the scientific and GIS communities in improving technologies that can bring scientific data into a GIS environment, where scientific research and analysis can be shared through the GIS platform to the public. Most NASA scientific data are delivered in the Hierarchical Data Format (HDF), a format is both flexible and powerful. However, this flexibility results in challenges when trying to develop supported GIS software - data stored with HDF formats lack a unified standard and convention among these products. The presentation introduces an information model that enables ArcGIS software to ingest NASA scientific data and create a multidimensional raster - univariate and multivariate hypercubes - for scientific visualization and analysis. We will present the framework how ArcGIS leverages the open source GDAL (Geospatial Data Abstract Library) to support its raster data access, discuss how we overcame the GDAL drivers limitations in handing scientific products that are stored with HDF4 and HDF5 formats and how we improve the way in modeling the multidimensionality with GDAL. In additional, we will talk about the direction of ArcGIS handling NASA products and demonstrate how the multidimensional information model can help scientists work with various data products such as MODIS, MOPPIT, SMAP as well as many data products in a GIS environment.
Visualization of Coastal Data Through KML
NASA Astrophysics Data System (ADS)
Damsma, T.; Baart, F.; de Boer, G.; van Koningsveld, M.; Bruens, A.
2009-12-01
As a country that lies mostly below sea level, the Netherlands has a history of coastal engineering, and is world renowned for its leading role in Integrated Coastal Zone Management (ICZM). Within the framework of Building with Nature (a Dutch ICZM research program) an OPeNDAP server is used to host several datasets of the Dutch coast. Among these sets are bathymetric data, cross-shore profiles, water level time series of which some date back to the eighteenth century. The challenge with hosting this amount of data is more in dissemination and accessibility rather than a technical one (tracing, accessing, gathering, unifying and storing). With so many data in different sets, how can one easily know when and where data is available, and of what quality it is? Recent work using Google Earth as a visual front-end for this database has proven very encouraging. Taking full advantage of the four dimensional (3D+time) visualization capabilities allows researchers, consultants and the general public to view, access and interact with the data. Within MATLAB a set of generic tools are developed for easy creation of among others:
OVERGRID: A Unified Overset Grid Generation Graphical Interface
NASA Technical Reports Server (NTRS)
Chan, William M.; Akien, Edwin W. (Technical Monitor)
1999-01-01
This paper presents a unified graphical interface and gridding strategy for performing overset grid generation. The interface called OVERGRID has been specifically designed to follow an efficient overset gridding strategy, and contains general grid manipulation capabilities as well as modules that are specifically suited for overset grids. General grid utilities include functions for grid redistribution, smoothing, concatenation, extraction, extrapolation, projection, and many others. Modules specially tailored for overset grids include a seam curve extractor, hyperbolic and algebraic surface grid generators, a hyperbolic volume grid generator, and a Cartesian box grid generator, Grid visualization is achieved using OpenGL while widgets are constructed with Tcl/Tk. The software is portable between various platforms from UNIX workstations to personal computers.
NASA Astrophysics Data System (ADS)
Honing, Henkjan; Zuidema, Willem
2014-09-01
The future of cognitive science will be about bridging neuroscience and behavioral studies, with essential roles played by comparative biology, formal modeling, and the theory of computation. Nowhere will this integration be more strongly needed than in understanding the biological basis of language and music. We thus strongly sympathize with the general framework that Fitch [1] proposes, and welcome the remarkably broad and readable review he presents to support it.
RosettaRemodel: A Generalized Framework for Flexible Backbone Protein Design
Huang, Po-Ssu; Ban, Yih-En Andrew; Richter, Florian; Andre, Ingemar; Vernon, Robert; Schief, William R.; Baker, David
2011-01-01
We describe RosettaRemodel, a generalized framework for flexible protein design that provides a versatile and convenient interface to the Rosetta modeling suite. RosettaRemodel employs a unified interface, called a blueprint, which allows detailed control over many aspects of flexible backbone protein design calculations. RosettaRemodel allows the construction and elaboration of customized protocols for a wide range of design problems ranging from loop insertion and deletion, disulfide engineering, domain assembly, loop remodeling, motif grafting, symmetrical units, to de novo structure modeling. PMID:21909381
Pricing foreign equity option with stochastic volatility
NASA Astrophysics Data System (ADS)
Sun, Qi; Xu, Weidong
2015-11-01
In this paper we propose a general foreign equity option pricing framework that unifies the vast foreign equity option pricing literature and incorporates the stochastic volatility into foreign equity option pricing. Under our framework, the time-changed Lévy processes are used to model the underlying assets price of foreign equity option and the closed form pricing formula is obtained through the use of characteristic function methodology. Numerical tests indicate that stochastic volatility has a dramatic effect on the foreign equity option prices.
NASA Astrophysics Data System (ADS)
Laban, Shaban; El-Desouky, Aly
2014-05-01
To achieve a rapid, simple and reliable parallel processing of different types of tasks and big data processing on any compute cluster, a lightweight messaging-based distributed applications processing and workflow execution framework model is proposed. The framework is based on Apache ActiveMQ and Simple (or Streaming) Text Oriented Message Protocol (STOMP). ActiveMQ , a popular and powerful open source persistence messaging and integration patterns server with scheduler capabilities, acts as a message broker in the framework. STOMP provides an interoperable wire format that allows framework programs to talk and interact between each other and ActiveMQ easily. In order to efficiently use the message broker a unified message and topic naming pattern is utilized to achieve the required operation. Only three Python programs and simple library, used to unify and simplify the implementation of activeMQ and STOMP protocol, are needed to use the framework. A watchdog program is used to monitor, remove, add, start and stop any machine and/or its different tasks when necessary. For every machine a dedicated one and only one zoo keeper program is used to start different functions or tasks, stompShell program, needed for executing the user required workflow. The stompShell instances are used to execute any workflow jobs based on received message. A well-defined, simple and flexible message structure, based on JavaScript Object Notation (JSON), is used to build any complex workflow systems. Also, JSON format is used in configuration, communication between machines and programs. The framework is platform independent. Although, the framework is built using Python the actual workflow programs or jobs can be implemented by any programming language. The generic framework can be used in small national data centres for processing seismological and radionuclide data received from the International Data Centre (IDC) of the Preparatory Commission for the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Also, it is possible to extend the use of the framework in monitoring the IDC pipeline. The detailed design, implementation,conclusion and future work of the proposed framework will be presented.
Understanding visualization: a formal approach using category theory and semiotics.
Vickers, Paul; Faith, Joe; Rossiter, Nick
2013-06-01
This paper combines the vocabulary of semiotics and category theory to provide a formal analysis of visualization. It shows how familiar processes of visualization fit the semiotic frameworks of both Saussure and Peirce, and extends these structures using the tools of category theory to provide a general framework for understanding visualization in practice, including: Relationships between systems, data collected from those systems, renderings of those data in the form of representations, the reading of those representations to create visualizations, and the use of those visualizations to create knowledge and understanding of the system under inspection. The resulting framework is validated by demonstrating how familiar information visualization concepts (such as literalness, sensitivity, redundancy, ambiguity, generalizability, and chart junk) arise naturally from it and can be defined formally and precisely. This paper generalizes previous work on the formal characterization of visualization by, inter alia, Ziemkiewicz and Kosara and allows us to formally distinguish properties of the visualization process that previous work does not.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pachuilo, Andrew R; Ragan, Eric; Goodall, John R
Visualization tools can take advantage of multiple coordinated views to support analysis of large, multidimensional data sets. Effective design of such views and layouts can be challenging, but understanding users analysis strategies can inform design improvements. We outline an approach for intelligent design configuration of visualization tools with multiple coordinated views, and we discuss a proposed software framework to support the approach. The proposed software framework could capture and learn from user interaction data to automate new compositions of views and widgets. Such a framework could reduce the time needed for meta analysis of the visualization use and lead tomore » more effective visualization design.« less
NASA Astrophysics Data System (ADS)
Kuvychko, Igor
2001-10-01
Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.
RANZCR Body Systems Framework of diagnostic imaging examination descriptors.
Pitman, Alexander G; Penlington, Lisa; Doromal, Darren; Slater, Gregory; Vukolova, Natalia
2014-08-01
A unified and logical system of descriptors for diagnostic imaging examinations and procedures is a desirable resource for radiology in Australia and New Zealand and is needed to support core activities of RANZCR. Existing descriptor systems available in Australia and New Zealand (including the Medicare DIST and the ACC Schedule) have significant limitations and are inappropriate for broader clinical application. An anatomically based grid was constructed, with anatomical structures arranged in rows and diagnostic imaging modalities arranged in columns (including nuclear medicine and positron emission tomography). The grid was segregated into five body systems. The cells at the intersection of an anatomical structure row and an imaging modality column were populated with short, formulaic descriptors of the applicable diagnostic imaging examinations. Clinically illogical or physically impossible combinations were 'greyed out'. Where the same examination applied to different anatomical structures, the descriptor was kept identical for the purposes of streamlining. The resulting Body Systems Framework of diagnostic imaging examination descriptors lists all the reasonably common diagnostic imaging examinations currently performed in Australia and New Zealand using a unified grid structure allowing navigation by both referrers and radiologists. The Framework has been placed on the RANZCR website and is available for access free of charge by registered users. The Body Systems Framework of diagnostic imaging examination descriptors is a system of descriptors based on relationships between anatomical structures and imaging modalities. The Framework is now available as a resource and reference point for the radiology profession and to support core College activities. © 2014 The Royal Australian and New Zealand College of Radiologists.
Read, Mark; Andrews, Paul S; Timmis, Jon; Kumar, Vipin
2014-10-06
We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology.
Read, Mark; Andrews, Paul S.; Timmis, Jon; Kumar, Vipin
2014-01-01
We present a framework to assist the diagrammatic modelling of complex biological systems using the unified modelling language (UML). The framework comprises three levels of modelling, ranging in scope from the dynamics of individual model entities to system-level emergent properties. By way of an immunological case study of the mouse disease experimental autoimmune encephalomyelitis, we show how the framework can be used to produce models that capture and communicate the biological system, detailing how biological entities, interactions and behaviours lead to higher-level emergent properties observed in the real world. We demonstrate how the UML can be successfully applied within our framework, and provide a critique of UML's ability to capture concepts fundamental to immunology and biology more generally. We show how specialized, well-explained diagrams with less formal semantics can be used where no suitable UML formalism exists. We highlight UML's lack of expressive ability concerning cyclic feedbacks in cellular networks, and the compounding concurrency arising from huge numbers of stochastic, interacting agents. To compensate for this, we propose several additional relationships for expressing these concepts in UML's activity diagram. We also demonstrate the ambiguous nature of class diagrams when applied to complex biology, and question their utility in modelling such dynamic systems. Models created through our framework are non-executable, and expressly free of simulation implementation concerns. They are a valuable complement and precursor to simulation specifications and implementations, focusing purely on thoroughly exploring the biology, recording hypotheses and assumptions, and serve as a communication medium detailing exactly how a simulation relates to the real biology. PMID:25142524
Buetow, S; Adair, V; Coster, G; Hight, M; Gribben, B; Mitchell, E
2002-12-01
Different sets of literature suggest how aspects of practice time management can limit access to general practitioner (GP) care. Researchers have not organised this knowledge into a unified framework that can enhance understanding of barriers to, and opportunities for, improved access. To suggest a framework conceptualising how differences in professional and cultural understanding of practice time management in Auckland, New Zealand, influence access to GP care for children with chronic asthma. A qualitative study involving selective sampling, semi-structured interviews on barriers to access, and a general inductive approach. Twenty-nine key informants and ten mothers of children with chronic, moderate to severe asthma and poor access to GP care in Auckland. Development of a framework from themes describing barriers associated with, and needs for, practice time management. The themes were independently identified by two authors from transcribed interviews and confirmed through informant checking. Themes from key informant and patient interviews were triangulated with each other and with published literature. The framework distinguishes 'practice-centred time' from 'patient-centred time.' A predominance of 'practice-centred time' and an unmet opportunity for 'patient-centred time' are suggested by the persistence of five barriers to accessing GP care: limited hours of opening; traditional appointment systems; practice intolerance of missed appointments; long waiting times in the practice; and inadequate consultation lengths. None of the barriers is specific to asthmatic children. A unified framework was suggested for understanding how the organisation of practice work time can influence access to GP care by groups including asthmatic children.
Modeling Geyser Eruptions in the Classroom
ERIC Educational Resources Information Center
Mattox, Stephen; Webster, Christine
2005-01-01
Watching Old Faithful transform from a smoldering mound to an explosive 50-meter high geyser is enough to generate awe in any observer. Behind this stunning, visual geologic display is a triad of heat, water, and plumbing that rarely unify on our planet. But geologists are not the only scientists drawn to geysers. Biologists have recently…
Status 1968; Report of the Special Education Branch, Los Angeles Unified School District.
ERIC Educational Resources Information Center
Los Angeles Unified School District, CA.
Included in the report on special education services of Los Angeles schools are chapters on an overview of the special education branch programs; the educationally handicapped, aphasic, and trainable mentally retarded; development centers for handicapped minors; the aurally and visually handicapped; the orthopedically handicapped or other health…
14 CFR § 1221.112 - Use of the NASA Program Identifiers.
Code of Federal Regulations, 2014 CFR
2014-01-01
... 14 Aeronautics and Space 5 2014-01-01 2014-01-01 false Use of the NASA Program Identifiers. Â... NASA SEAL AND OTHER DEVICES, AND THE CONGRESSIONAL SPACE MEDAL OF HONOR NASA Seal, NASA Insignia, NASA Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System...
2012-11-27
with powerful analysis tools and an informatics approach leveraging best-of-breed NoSQL databases, in order to store, search and retrieve relevant...dictionaries, and JavaScript also has good support. The MongoDB project[15] was chosen as a scalable NoSQL data store for the cheminfor- matics components
14 CFR § 1221.114 - Approval of new or change proposals.
Code of Federal Regulations, 2014 CFR
2014-01-01
... Logotype, NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System... modification to the design of the NASA Insignia may also be submitted to the Commission of Fine Arts for its... received from the Commission of Fine Arts, the NASA Insignia and the use of such NASA Insignia must be...
Tuan Pham; Julia Jones; Ronald Metoyer; Frederick Colwell
2014-01-01
The study of the diversity of multivariate objects shares common characteristics and goals across disciplines, including ecology and organizational management. Nevertheless, subject-matter experts have adopted somewhat separate diversity concepts and analysis techniques, limiting the potential for sharing and comparing across disciplines. Moreover, while large and...
Automatic extraction and visualization of object-oriented software design metrics
NASA Astrophysics Data System (ADS)
Lakshminarayana, Anuradha; Newman, Timothy S.; Li, Wei; Talburt, John
2000-02-01
Software visualization is a graphical representation of software characteristics and behavior. Certain modes of software visualization can be useful in isolating problems and identifying unanticipated behavior. In this paper we present a new approach to aid understanding of object- oriented software through 3D visualization of software metrics that can be extracted from the design phase of software development. The focus of the paper is a metric extraction method and a new collection of glyphs for multi- dimensional metric visualization. Our approach utilize the extensibility interface of a popular CASE tool to access and automatically extract the metrics from Unified Modeling Language class diagrams. Following the extraction of the design metrics, 3D visualization of these metrics are generated for each class in the design, utilizing intuitively meaningful 3D glyphs that are representative of the ensemble of metrics. Extraction and visualization of design metrics can aid software developers in the early study and understanding of design complexity.
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
Towards diverse visual suggestions on Flickr
NASA Astrophysics Data System (ADS)
Feki, Ghada; Ben Ammar, Anis; Ben Amar, Chokri
2017-03-01
With the great popularity of the photo sharing site Flickr, the research community is involved to produce innovative applications in order to enhance different Flickr services. In this paper, we present a new process for diverse visual suggestions generation on Flickr. We unify the social aspect of Flickr and the richness of Wikipedia to produce an important number of meanings illustrated by the diverse visual suggestions which can integrate the diversity aspect into the Flickr search. We conduct an experimental study to illustrate the effect of the fusion of the Wikipedia and Flickr knowledge on the diversity rate among the Flickr search and reveal the evolution of the diversity aspect through the returned images among the different results of search engines.
Visualization Techniques in Space and Atmospheric Sciences
NASA Technical Reports Server (NTRS)
Szuszczewicz, E. P. (Editor); Bredekamp, Joseph H. (Editor)
1995-01-01
Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.
NASA Astrophysics Data System (ADS)
Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara
2013-04-01
Analysis of growing volume of related to climate change data from sensors and model outputs requires collaborative multidisciplinary efforts of researchers. To do it timely and in reliable way one needs in modern information-computational infrastructure supporting integrated studies in the field of environmental sciences. Recently developed experimental software and hardware platform Climate (http://climate.scert.ru/) provides required environment for regional climate change related investigations. The platform combines modern web 2.0 approach, GIS-functionality and capabilities to run climate and meteorological models, process large geophysical datasets and support relevant analysis. It also supports joint software development by distributed research groups, and organization of thematic education for students and post-graduate students. In particular, platform software developed includes dedicated modules for numerical processing of regional and global modeling results for consequent analysis and visualization. Also run of integrated into the platform WRF and «Planet Simulator» models, modeling results data preprocessing and visualization is provided. All functions of the platform are accessible by a user through a web-portal using common graphical web-browser in the form of an interactive graphical user interface which provides, particularly, capabilities of selection of geographical region of interest (pan and zoom), data layers manipulation (order, enable/disable, features extraction) and visualization of results. Platform developed provides users with capabilities of heterogeneous geophysical data analysis, including high-resolution data, and discovering of tendencies in climatic and ecosystem changes in the framework of different multidisciplinary researches. Using it even unskilled user without specific knowledge can perform reliable computational processing and visualization of large meteorological, climatic and satellite monitoring datasets through unified graphical web-interface. Partial support of RF Ministry of Education and Science grant 8345, SB RAS Program VIII.80.2 and Projects 69, 131, 140 and APN CBA2012-16NSY project is acknowledged.
NASA Astrophysics Data System (ADS)
Zhou, S.; Tao, W. K.; Li, X.; Matsui, T.; Sun, X. H.; Yang, X.
2015-12-01
A cloud-resolving model (CRM) is an atmospheric numerical model that can numerically resolve clouds and cloud systems at 0.25~5km horizontal grid spacings. The main advantage of the CRM is that it can allow explicit interactive processes between microphysics, radiation, turbulence, surface, and aerosols without subgrid cloud fraction, overlapping and convective parameterization. Because of their fine resolution and complex physical processes, it is challenging for the CRM community to i) visualize/inter-compare CRM simulations, ii) diagnose key processes for cloud-precipitation formation and intensity, and iii) evaluate against NASA's field campaign data and L1/L2 satellite data products due to large data volume (~10TB) and complexity of CRM's physical processes. We have been building the Super Cloud Library (SCL) upon a Hadoop framework, capable of CRM database management, distribution, visualization, subsetting, and evaluation in a scalable way. The current SCL capability includes (1) A SCL data model enables various CRM simulation outputs in NetCDF, including the NASA-Unified Weather Research and Forecasting (NU-WRF) and Goddard Cumulus Ensemble (GCE) model, to be accessed and processed by Hadoop, (2) A parallel NetCDF-to-CSV converter supports NU-WRF and GCE model outputs, (3) A technique visualizes Hadoop-resident data with IDL, (4) A technique subsets Hadoop-resident data, compliant to the SCL data model, with HIVE or Impala via HUE's Web interface, (5) A prototype enables a Hadoop MapReduce application to dynamically access and process data residing in a parallel file system, PVFS2 or CephFS, where high performance computing (HPC) simulation outputs such as NU-WRF's and GCE's are located. We are testing Apache Spark to speed up SCL data processing and analysis.With the SCL capabilities, SCL users can conduct large-domain on-demand tasks without downloading voluminous CRM datasets and various observations from NASA Field Campaigns and Satellite data to a local computer, and inter-compare CRM output and data with GCE and NU-WRF.
2016-09-01
is a Windows Presentation Foundation (WPF) control developed using the .NET framework in Microsoft Visual Studio. As a WPF control, it can be used in...any WPF application as a graphical visual element. The purpose of the control is to visually display time-related events as vertical lines on a...available on the control. 15. SUBJECT TERMS Windows Presentation Foundation, WPF, control, C#, .NET framework, Microsoft Visual Studio 16. SECURITY
Teacher Preparation for Vocational Education and Training in Germany: A Potential Model for Canada?
ERIC Educational Resources Information Center
Barabasch, Antje; Watt-Malcolm, Bonnie
2013-01-01
Germany's vocational education and training (VET) and corresponding teacher-education programmes are known worldwide for their integrated framework. Government legislation unifies companies, unions and vocational schools, and specifies the education and training required for students as well as vocational teachers. Changing from the Diplom…
The Unified Plant Growth Model (UPGM): software framework overview and model application
USDA-ARS?s Scientific Manuscript database
Since the Environmental Policy Integrated Climate (EPIC) model was developed in 1989, the EPIC plant growth component has been incorporated into other erosion and crop management models (e.g., WEPS, WEPP, SWAT, ALMANAC, and APEX) and modified to meet model developer research objectives. This has re...
The Importance of Culture for Developmental Science
ERIC Educational Resources Information Center
Keller, Heidi
2012-01-01
In this essay, it is argued that a general understanding of human development needs a unified framework based on evolutionary theorizing and cross-cultural and cultural anthropological approaches. An eco-social model of development has been proposed that defines cultural milieus as adaptations to specific socio-demographic contexts. Ontogenetic…
2009-08-19
SSDS Ship Self Defense System TSTS Total Ship Training System UDDI Universal Description, Discovery, and Integration UML Unified Modeling...34ContractorOrganization" type="ContractorOrganizationType"> <xs:annotation> <xs:documentation>Identifies a contractor organization resposible for the
ERIC Educational Resources Information Center
Hwang, Heungsun; Montreal, Hec; Dillon, William R.; Takane, Yoshio
2006-01-01
An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…
USDA-ARS?s Scientific Manuscript database
Biological diversity is a key concept in the life sciences and plays a fundamental role in many ecological and evolutionary processes. Although biodiversity is inherently a hierarchical concept covering different levels of organization (genes, population, species, ecological communities and ecosyst...
The Theory behind the Theory in DCT and SCDT: A Response to Rigazio-DiGilio.
ERIC Educational Resources Information Center
Terry, Linda L.
1994-01-01
Responds to previous article by Rigazio-DiGilio on Developmental Counseling and Therapy and Systemic Cognitive-Developmental Therapy as two integrative models that unify individual, family, and network treatment within coconstructive-developmental framework. Discusses hidden complexities in cognitive-developmental ecosystemic integration and…
Potential of DCT/SCDT in Addressing Two Elusive Themes of Mental Health Counseling.
ERIC Educational Resources Information Center
Borders, L. DiAnne
1994-01-01
Responds to previous article by Rigazio-DiGilio on Developmental Counseling and Therapy and Systemic Cognitive-Developmental Therapy as two integrative models that unify individual, family, and network treatment within coconstructive-developmental framework. Considers extent to which model breaks impasse in integrating development into counseling…
Converging Instructional Technology and Critical Intercultural Pedagogy in Teacher Education
ERIC Educational Resources Information Center
Pittman, Joyce
2007-01-01
Purpose: This paper aims to postulate an emerging unified cultural-convergence framework to converge the delivery of instructional technology and intercultural education (ICE) that extends beyond web-learning technologies to inculcate inclusive pedagogy in teacher education. Design/methodology/approach: The paper explores the literature and a…
Spending on School Infrastructure: Does Money Matter?
ERIC Educational Resources Information Center
Crampton, Faith E.
2009-01-01
Purpose: The purpose of this study is to further develop an emerging thread of quantitative research that grounds investment in school infrastructure in a unified theoretical framework of investment in human, social, and physical capital. Design/methodology/approach: To answer the research question, what is the impact of investment in human,…
Simultaneous Two-Way Clustering of Multiple Correspondence Analysis
ERIC Educational Resources Information Center
Hwang, Heungsun; Dillon, William R.
2010-01-01
A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…
ERIC Educational Resources Information Center
Arnhart, Larry
2006-01-01
Be it metaphysics, theology, or some other unifying framework, humans have long sought to determine "first principles" underlying knowledge. Larry Arnhart continues in this vein, positing a Darwinian web of genetic, cultural, and cognitive evolution to explain our social behavior in terms of human nature as governed by biology. He leaves it to us…
Unified, Insular, Firmly Policed, or Fractured, Porous, Contested, Gifted Education?
ERIC Educational Resources Information Center
Ambrose, Don; VanTassel-Baska, Joyce; Coleman, Laurence J.; Cross, Tracy L.
2010-01-01
Much like medieval, feudal nations, professional fields such as gifted education can take shape as centralized kingdoms with strong armies controlling their compliant populations and protecting closed borders, or as loose collections of conflict-prone principalities with borders open to invaders. Using an investigative framework borrowed from an…
Software for Data Analysis with Graphical Models
NASA Technical Reports Server (NTRS)
Buntine, Wray L.; Roy, H. Scott
1994-01-01
Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.
PERCH: A Unified Framework for Disease Gene Prioritization.
Feng, Bing-Jian
2017-03-01
To interpret genetic variants discovered from next-generation sequencing, integration of heterogeneous information is vital for success. This article describes a framework named PERCH (Polymorphism Evaluation, Ranking, and Classification for a Heritable trait), available at http://BJFengLab.org/. It can prioritize disease genes by quantitatively unifying a new deleteriousness measure called BayesDel, an improved assessment of the biological relevance of genes to the disease, a modified linkage analysis, a novel rare-variant association test, and a converted variant call quality score. It supports data that contain various combinations of extended pedigrees, trios, and case-controls, and allows for a reduced penetrance, an elevated phenocopy rate, liability classes, and covariates. BayesDel is more accurate than PolyPhen2, SIFT, FATHMM, LRT, Mutation Taster, Mutation Assessor, PhyloP, GERP++, SiPhy, CADD, MetaLR, and MetaSVM. The overall approach is faster and more powerful than the existing quantitative method pVAAST, as shown by the simulations of challenging situations in finding the missing heritability of a complex disease. This framework can also classify variants of unknown significance (variants of uncertain significance) by quantitatively integrating allele frequencies, deleteriousness, association, and co-segregation. PERCH is a versatile tool for gene prioritization in gene discovery research and variant classification in clinical genetic testing. © 2016 The Authors. **Human Mutation published by Wiley Periodicals, Inc.
Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung
2013-01-01
In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences. PMID:23435057
Ghanbari, Yasser; Smith, Alex R.; Schultz, Robert T.; Verma, Ragini
2014-01-01
Diffusion tensor imaging (DTI) offers rich insights into the physical characteristics of white matter (WM) fiber tracts and their development in the brain, facilitating a network representation of brain’s traffic pathways. Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging. The high dimensionality of these connectivity networks necessitates the development of methods that identify the connectivity building blocks or sub-network components that characterize the underlying variation in the population. In addition, the projection of the subject networks into the basis set provides a low dimensional representation of it, that teases apart different sources of variation in the sample, facilitating variation-specific statistical analysis. We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive basis set, as well as, additional basis sets representing variational sources in the population like age and pathology. The proposed framework is applied to a study of diffusion-based connectivity in subjects with autism that shows localized sparse sub-networks which mostly capture the changes related to pathology and developmental variations. PMID:25037933
Computable visually observed phenotype ontological framework for plants
2011-01-01
Background The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed. Results We have developed a new framework called the Computable Visually Observed Phenotype Ontological Framework for plants. This work provides a novel quantitative view of descriptions of plant phenotypes that leverages existing bio-ontologies and utilizes a computational approach to capture and represent domain knowledge in a machine-interpretable form. This is accomplished by means of a robust and accurate semantic mapping module that automatically maps high-level semantics to low-level measurements computed from phenotype imagery. The framework was applied to two different plant species with semantic rules mined and an ontology constructed. Rule quality was evaluated and showed high quality rules for most semantics. This framework also facilitates automatic annotation of phenotype images and can be adopted by different plant communities to aid in their research. Conclusions The Computable Visually Observed Phenotype Ontological Framework for plants has been developed for more efficient and accurate management of visually observed phenotypes, which play a significant role in plant genomics research. The uniqueness of this framework is its ability to bridge the knowledge of informaticians and plant science researchers by translating descriptions of visually observed phenotypes into standardized, machine-understandable representations, thus enabling the development of advanced information retrieval and phenotype annotation analysis tools for the plant science community. PMID:21702966
Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images
Gutmann, Michael U.; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús
2014-01-01
Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation. PMID:24533049
Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.
Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús
2014-01-01
Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.
The Art of Observation: A Pedagogical Framework.
Wellbery, Caroline; McAteer, Rebecca A
2015-12-01
Observational skills, honed through experience with the literary and visual arts, bring together in a timely manner many of the goals of the medical humanities, providing thematic cohesion through the act of seeing while aiming to advance clinical skills through a unified practice. In an arts observation pedagogy, nature writing serves as an apt model for precise, clinically relevant linguistic noticing because meticulous attention to the natural world involves scientific precision; additionally, a number of visual metaphors employed in medicine are derived from close observation of the natural world. Close reading reinforces observational skills as part of integrative, multidisciplinary clinical practice. Literary precision provides an educational bridge to recognizing the importance of detail in the clinical realm. In weighing multiple perspectives, observation applied to practice helps learners understand the nuances of the role of witness, activating reflection consonant with the viewer's professional identity. The realization that seeing is highly filtered through the observer's values allows the act of observation to come under scrutiny, opening the observer's gaze to disturbance and challenging the values and precepts of the prevailing medical culture. Application of observational skills can, for example, help observers recognize and address noxious effects of the built environment. As learners describe what they see, they also develop the communication skills needed to articulate both problems and possible improvements within their expanding sphere of influence. The ability to craft this speech as public narrative can lead to interventions with positive impacts on physicians, their colleagues, and patients.
Yin, X-X; Zhang, Y; Cao, J; Wu, J-L; Hadjiloucas, S
2016-12-01
We provide a comprehensive account of recent advances in biomedical image analysis and classification from two complementary imaging modalities: terahertz (THz) pulse imaging and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). The work aims to highlight underlining commonalities in both data structures so that a common multi-channel data fusion framework can be developed. Signal pre-processing in both datasets is discussed briefly taking into consideration advances in multi-resolution analysis and model based fractional order calculus system identification. Developments in statistical signal processing using principal component and independent component analysis are also considered. These algorithms have been developed independently by the THz-pulse imaging and DCE-MRI communities, and there is scope to place them in a common multi-channel framework to provide better software standardization at the pre-processing de-noising stage. A comprehensive discussion of feature selection strategies is also provided and the importance of preserving textural information is highlighted. Feature extraction and classification methods taking into consideration recent advances in support vector machine (SVM) and extreme learning machine (ELM) classifiers and their complex extensions are presented. An outlook on Clifford algebra classifiers and deep learning techniques suitable to both types of datasets is also provided. The work points toward the direction of developing a new unified multi-channel signal processing framework for biomedical image analysis that will explore synergies from both sensing modalities for inferring disease proliferation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
A movement ecology paradigm for unifying organismal movement research
Nathan, Ran; Getz, Wayne M.; Revilla, Eloy; Holyoak, Marcel; Kadmon, Ronen; Saltz, David; Smouse, Peter E.
2008-01-01
Movement of individual organisms is fundamental to life, quilting our planet in a rich tapestry of phenomena with diverse implications for ecosystems and humans. Movement research is both plentiful and insightful, and recent methodological advances facilitate obtaining a detailed view of individual movement. Yet, we lack a general unifying paradigm, derived from first principles, which can place movement studies within a common context and advance the development of a mature scientific discipline. This introductory article to the Movement Ecology Special Feature proposes a paradigm that integrates conceptual, theoretical, methodological, and empirical frameworks for studying movement of all organisms, from microbes to trees to elephants. We introduce a conceptual framework depicting the interplay among four basic mechanistic components of organismal movement: the internal state (why move?), motion (how to move?), and navigation (when and where to move?) capacities of the individual and the external factors affecting movement. We demonstrate how the proposed framework aids the study of various taxa and movement types; promotes the formulation of hypotheses about movement; and complements existing biomechanical, cognitive, random, and optimality paradigms of movement. The proposed framework integrates eclectic research on movement into a structured paradigm and aims at providing a basis for hypothesis generation and a vehicle facilitating the understanding of the causes, mechanisms, and spatiotemporal patterns of movement and their role in various ecological and evolutionary processes. ”Now we must consider in general the common reason for moving with any movement whatever.“ (Aristotle, De Motu Animalium, 4th century B.C.) PMID:19060196
A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions.
Chang, Ivan; Baldi, Pierre
2013-05-15
Oxidoreductases are a fundamental class of enzymes responsible for the catalysis of oxidation-reduction reactions, crucial in most bioenergetic metabolic pathways. From their common root in the ancient prebiotic environment, oxidoreductases have evolved into diverse and elaborate protein structures with specific kinetic properties and mechanisms adapted to their individual functional roles and environmental conditions. While accurate kinetic modeling of oxidoreductases is thus important, current models suffer from limitations to the steady-state domain, lack empirical validation or are too specialized to a single system or set of conditions. To address these limitations, we introduce a novel unifying modeling framework for kinetic descriptions of oxidoreductases. The framework is based on a set of seven elementary reactions that (i) form the basis for 69 pairs of enzyme state transitions for encoding various specific microscopic intra-enzyme reaction networks (micro-models), and (ii) lead to various specific macroscopic steady-state kinetic equations (macro-models) via thermodynamic assumptions. Thus, a synergistic bridge between the micro and macro kinetics can be achieved, enabling us to extract unitary rate constants, simulate reaction variance and validate the micro-models using steady-state empirical data. To help facilitate the application of this framework, we make available RedoxMech: a Mathematica™ software package that automates the generation and customization of micro-models. The Mathematica™ source code for RedoxMech, the documentation and the experimental datasets are all available from: http://www.igb.uci.edu/tools/sb/metabolic-modeling. pfbaldi@ics.uci.edu Supplementary data are available at Bioinformatics online.
War-gaming application for future space systems acquisition
NASA Astrophysics Data System (ADS)
Nguyen, Tien M.; Guillen, Andy T.
2016-05-01
Recently the U.S. Department of Defense (DOD) released the Defense Innovation Initiative (DII) [1] to focus DOD on five key aspects; Aspect #1: Recruit talented and innovative people, Aspect #2: Reinvigorate war-gaming, Aspect #3: Initiate long-range research and development programs, Aspect #4: Make DOD practices more innovative, and Aspect #5: Advance technology and new operational concepts. Per DII instruction, this paper concentrates on Aspect #2 and Aspect #4 by reinvigorating the war-gaming effort with a focus on an innovative approach for developing the optimum Program and Technical Baselines (PTBs) and their corresponding optimum acquisition strategies for acquiring future space systems. The paper describes a unified approach for applying the war-gaming concept for future DOD acquisition of space systems. The proposed approach includes a Unified Game-based Acquisition Framework (UGAF) and an Advanced Game-Based Mathematical Framework (AGMF) using Bayesian war-gaming engines to optimize PTB solutions and select the corresponding optimum acquisition strategies for acquiring a space system. The framework defines the action space for all players with a complete description of the elements associated with the games, including Department of Defense Acquisition Authority (DAA), stakeholders, warfighters, and potential contractors, War-Gaming Engines (WGEs) played by DAA, WGEs played by Contractor (KTR), and the players' Payoff and Cost functions (PCFs). The AGMF presented here addresses both complete and incomplete information cases. The proposed framework provides a recipe for the DAA and USAF-Space and Missile Systems Center (SMC) to acquire future space systems optimally.
Rattner, Alexander S.; Guillen, Donna Post; Joshi, Alark; ...
2016-03-17
Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaViewmore » plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.« less
NASA Technical Reports Server (NTRS)
Chan, William M.; Akien, Edwin (Technical Monitor)
2002-01-01
For many years, generation of overset grids for complex configurations has required the use of a number of different independently developed software utilities. Results created by each step were then visualized using a separate visualization tool before moving on to the next. A new software tool called OVERGRID was developed which allows the user to perform all the grid generation steps and visualization under one environment. OVERGRID provides grid diagnostic functions such as surface tangent and normal checks as well as grid manipulation functions such as extraction, extrapolation, concatenation, redistribution, smoothing, and projection. Moreover, it also contains hyperbolic surface and volume grid generation modules that are specifically suited for overset grid generation. It is the first time that such a unified interface existed for the creation of overset grids for complex geometries. New concepts on automatic overset surface grid generation around surface discontinuities will also be briefly presented. Special control curves on the surface such as intersection curves, sharp edges, open boundaries, are called seam curves. The seam curves are first automatically extracted from a multiple panel network description of the surface. Points where three or more seam curves meet are automatically identified and are called seam corners. Seam corner surface grids are automatically generated using a singular axis topology. Hyperbolic surface grids are then grown from the seam curves that are automatically trimmed away from the seam corners.
Unifying Gate Synthesis and Magic State Distillation.
Campbell, Earl T; Howard, Mark
2017-02-10
The leading paradigm for performing a computation on quantum memories can be encapsulated as distill-then-synthesize. Initially, one performs several rounds of distillation to create high-fidelity magic states that provide one good T gate, an essential quantum logic gate. Subsequently, gate synthesis intersperses many T gates with Clifford gates to realize a desired circuit. We introduce a unified framework that implements one round of distillation and multiquibit gate synthesis in a single step. Typically, our method uses the same number of T gates as conventional synthesis but with the added benefit of quadratic error suppression. Because of this, one less round of magic state distillation needs to be performed, leading to significant resource savings.
The free-energy principle: a unified brain theory?
Friston, Karl
2010-02-01
A free-energy principle has been proposed recently that accounts for action, perception and learning. This Review looks at some key brain theories in the biological (for example, neural Darwinism) and physical (for example, information theory and optimal control theory) sciences from the free-energy perspective. Crucially, one key theme runs through each of these theories - optimization. Furthermore, if we look closely at what is optimized, the same quantity keeps emerging, namely value (expected reward, expected utility) or its complement, surprise (prediction error, expected cost). This is the quantity that is optimized under the free-energy principle, which suggests that several global brain theories might be unified within a free-energy framework.
Hilltop supernatural inflation and SUSY unified models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kohri, Kazunori; Lim, C.S.; Lin, Chia-Min
2014-01-01
In this paper, we consider high scale (100TeV) supersymmetry (SUSY) breaking and realize the idea of hilltop supernatural inflation in concrete particle physics models based on flipped-SU(5)and Pati-Salam models in the framework of supersymmetric grand unified theories (SUSY GUTs). The inflaton can be a flat direction including right-handed sneutrino and the waterfall field is a GUT Higgs. The spectral index is n{sub s} = 0.96 which fits very well with recent data by PLANCK satellite. There is no both thermal and non-thermal gravitino problems. Non-thermal leptogenesis can be resulted from the decay of right-handed sneutrino which plays (part of) themore » role of inflaton.« less
Customer-experienced rapid prototyping
NASA Astrophysics Data System (ADS)
Zhang, Lijuan; Zhang, Fu; Li, Anbo
2008-12-01
In order to describe accurately and comprehend quickly the perfect GIS requirements, this article will integrate the ideas of QFD (Quality Function Deployment) and UML (Unified Modeling Language), and analyze the deficiency of prototype development model, and will propose the idea of the Customer-Experienced Rapid Prototyping (CE-RP) and describe in detail the process and framework of the CE-RP, from the angle of the characteristics of Modern-GIS. The CE-RP is mainly composed of Customer Tool-Sets (CTS), Developer Tool-Sets (DTS) and Barrier-Free Semantic Interpreter (BF-SI) and performed by two roles of customer and developer. The main purpose of the CE-RP is to produce the unified and authorized requirements data models between customer and software developer.
Unified reduction principle for the evolution of mutation, migration, and recombination
Altenberg, Lee; Liberman, Uri; Feldman, Marcus W.
2017-01-01
Modifier-gene models for the evolution of genetic information transmission between generations of organisms exhibit the reduction principle: Selection favors reduction in the rate of variation production in populations near equilibrium under a balance of constant viability selection and variation production. Whereas this outcome has been proven for a variety of genetic models, it has not been proven in general for multiallelic genetic models of mutation, migration, and recombination modification with arbitrary linkage between the modifier and major genes under viability selection. We show that the reduction principle holds for all of these cases by developing a unifying mathematical framework that characterizes all of these evolutionary models. PMID:28265103
A Unified Approach to Intra-Domain Security
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shue, Craig A; Kalafut, Andrew J.; Gupta, Prof. Minaxi
2009-01-01
While a variety of mechanisms have been developed for securing individual intra-domain protocols, none address the issue in a holistic manner. We develop a unified framework to secure prominent networking protocols within a single domain. We begin with a secure version of the DHCP protocol, which has the additional feature of providing each host with a certificate. We then leverage these certificates to secure ARP, prevent spoofing within the domain, and secure SSH and VPN connections between the domain and hosts which have previously interacted with it locally. In doing so, we also develop an incrementally deployable public key infrastructuremore » which can later be leveraged to support inter-domain authentication.« less
Baines, Darrin L
2018-05-04
This paper proposes a new conceptual framework for jointly analysing the production of staff and patient welfare in health systems. Research to date has identified a direct link between staff and patient well-being. However, until now, no one has produced a unified framework for analysing them concurrently. In response, this paper introduces the "Frontier Framework". The new conceptual framework is applicable to all health systems regardless of their structure or financing. To demonstrate the benefits of its use, an empirical example of the Frontier Framework is constructed using data from the UK's National Health Service. This paper also introduces eight "Frontier Archetypes", which represent common patterns of welfare generation observable in health organisations involved in programmes of change. These archetypes may be used in planning, monitoring or creating narratives about organisational journeys. Copyright © 2018 The Author. Published by Elsevier Ltd.. All rights reserved.
UUI: Reusable Spatial Data Services in Unified User Interface at NASA GES DISC
NASA Technical Reports Server (NTRS)
Petrenko, Maksym; Hegde, Mahabaleshwa; Bryant, Keith; Pham, Long B.
2016-01-01
Unified User Interface (UUI) is a next-generation operational data access tool that has been developed at Goddard Earth Sciences Data and Information Services Center(GES DISC) to provide a simple, unified, and intuitive one-stop shop experience for the key data services available at GES DISC, including subsetting (Simple Subset Wizard -SSW), granule file search (Mirador), plotting (Giovanni), and other legacy spatial data services. UUI has been built based on a flexible infrastructure of reusable web services self-contained building blocks that can easily be plugged into spatial applications, including third-party clients or services, to easily enable new functionality as new datasets and services become available. In this presentation, we will discuss our experience in designing UUI services based on open industry standards. We will also explain how the resulting framework can be used for a rapid development, deployment, and integration of spatial data services, facilitating efficient access and dissemination of spatial data sets.
Microphysics in Multi-scale Modeling System with Unified Physics
NASA Technical Reports Server (NTRS)
Tao, Wei-Kuo
2012-01-01
Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (1) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, a review of developments and applications of the multi-scale modeling system will be presented. In particular, the microphysics development and its performance for the multi-scale modeling system will be presented.
Modelling Participatory Geographic Information System for Customary Land Conflict Resolution
NASA Astrophysics Data System (ADS)
Gyamera, E. A.; Arko-Adjei, A.; Duncan, E. E.; Kuma, J. S. Y.
2017-11-01
Since land contributes to about 73 % of most countries Gross Domestic Product (GDP), attention on land rights have tremendously increased globally. Conflicts over land have therefore become part of the major problems associated with land administration. However, the conventional mechanisms for land conflict resolution do not provide satisfactory result to disputants due to various factors. This study sought to develop a Framework of using Participatory Geographic Information System (PGIS) for customary land conflict resolution. The framework was modelled using Unified Modelling Language (UML). The PGIS framework, called butterfly model, consists of three units namely, Social Unit (SU), Technical Unit (TU) and Decision Making Unit (DMU). The name butterfly model for land conflict resolution was adopted for the framework based on its features and properties. The framework has therefore been recommended to be adopted for land conflict resolution in customary areas.
SAFAS: Unifying Form and Structure through Interactive 3D Simulation
ERIC Educational Resources Information Center
Polys, Nicholas F.; Bacim, Felipe; Setareh, Mehdi; Jones, Brett D.
2015-01-01
There has been a significant gap between the tools used for the design of a building's architectural form and those that evaluate the structural physics of that form. Seeking to bring the perspectives of visual design and structural engineering closer together, we developed and evaluated a design tool for students and practitioners to explore the…
ERIC Educational Resources Information Center
Klemen, Jane; Buchel, Christian; Buhler, Mira; Menz, Mareike M.; Rose, Michael
2010-01-01
Attentional interference between tasks performed in parallel is known to have strong and often undesired effects. As yet, however, the mechanisms by which interference operates remain elusive. A better knowledge of these processes may facilitate our understanding of the effects of attention on human performance and the debilitating consequences…
The Metaplectic Sampling of Quantum Engineering
NASA Astrophysics Data System (ADS)
Schempp, Walter J.
2010-12-01
Due to photonic visualization, quantum physics is not restricted to the microworld. Starting off with synthetic aperture radar, the paper provides a unified approach to coherent atom optics, clinical magnetic resonance tomography and the bacterial protein dynamics of structural microbiology. Its mathematical base is harmonic analysis on the three-dimensional Heisenberg Lie group with associated nilpotent Heisenberg algebra Lie(N).
Visual Debugging of Object-Oriented Systems With the Unified Modeling Language
2004-03-01
to be “the systematic and imaginative use of the technology of interactive computer graphics and the disciplines of graphic design , typography ... Graphics volume 23 no 6, pp893-901, 1999. [SHN98] Shneiderman, B. Designing the User Interface. Strategies for Effective Human-Computer Interaction...System Design Objectives ................................................................................ 44 3.3 System Architecture
14 CFR 1221.114 - Approval of new or change proposals.
Code of Federal Regulations, 2013 CFR
2013-01-01
..., NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System § 1221.114... the design of the NASA Insignia may also be submitted to the Commission of Fine Arts for its advice as... the Commission of Fine Arts, the NASA Insignia and the use of such NASA Insignia must be prescribed in...
14 CFR 1221.114 - Approval of new or change proposals.
Code of Federal Regulations, 2010 CFR
2010-01-01
..., NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System § 1221.114... the design of the NASA Insignia may also be submitted to the Commission of Fine Arts for its advice as... the Commission of Fine Arts, the NASA Insignia and the use of such NASA Insignia must be prescribed in...
14 CFR 1221.114 - Approval of new or change proposals.
Code of Federal Regulations, 2012 CFR
2012-01-01
..., NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System § 1221.114... the design of the NASA Insignia may also be submitted to the Commission of Fine Arts for its advice as... the Commission of Fine Arts, the NASA Insignia and the use of such NASA Insignia must be prescribed in...
14 CFR 1221.114 - Approval of new or change proposals.
Code of Federal Regulations, 2011 CFR
2011-01-01
..., NASA Program Identifiers, NASA Flags, and the Agency's Unified Visual Communications System § 1221.114... the design of the NASA Insignia may also be submitted to the Commission of Fine Arts for its advice as... the Commission of Fine Arts, the NASA Insignia and the use of such NASA Insignia must be prescribed in...
Using a Functional Model to Develop a Mathematical Formula
ERIC Educational Resources Information Center
Otto, Charlotte A.; Everett, Susan A.; Luera, Gail R.
2008-01-01
The unifying theme of models was incorporated into a required Science Capstone course for pre-service elementary teachers based on national standards in science and mathematics. A model of a teeter-totter was selected for use as an example of a functional model for gathering data as well as a visual model of a mathematical equation for developing…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dowson, Scott T.; Bruce, Joseph R.; Best, Daniel M.
2009-04-14
This paper presents key components of the Law Enforcement Information Framework (LEIF) that provides communications, situational awareness, and visual analytics tools in a service-oriented architecture supporting web-based desktop and handheld device users. LEIF simplifies interfaces and visualizations of well-established visual analytical techniques to improve usability. Advanced analytics capability is maintained by enhancing the underlying processing to support the new interface. LEIF development is driven by real-world user feedback gathered through deployments at three operational law enforcement organizations in the US. LEIF incorporates a robust information ingest pipeline supporting a wide variety of information formats. LEIF also insulates interface and analyticalmore » components from information sources making it easier to adapt the framework for many different data repositories.« less
NASA Astrophysics Data System (ADS)
Lyon, A. L.; Kowalkowski, J. B.; Jones, C. D.
2017-10-01
ParaView is a high performance visualization application not widely used in High Energy Physics (HEP). It is a long standing open source project led by Kitware and involves several Department of Energy (DOE) and Department of Defense (DOD) laboratories. Futhermore, it has been adopted by many DOE supercomputing centers and other sites. ParaView is unique in speed and efficiency by using state-of-the-art techniques developed by the academic visualization community that are often not found in applications written by the HEP community. In-situ visualization of events, where event details are visualized during processing/analysis, is a common task for experiment software frameworks. Kitware supplies Catalyst, a library that enables scientific software to serve visualization objects to client ParaView viewers yielding a real-time event display. Connecting ParaView to the Fermilab art framework will be described and the capabilities it brings discussed.
EarthServer - 3D Visualization on the Web
NASA Astrophysics Data System (ADS)
Wagner, Sebastian; Herzig, Pasquale; Bockholt, Ulrich; Jung, Yvonne; Behr, Johannes
2013-04-01
EarthServer (www.earthserver.eu), funded by the European Commission under its Seventh Framework Program, is a project to enable the management, access and exploration of massive, multi-dimensional datasets using Open GeoSpatial Consortium (OGC) query and processing language standards like WCS 2.0 and WCPS. To this end, a server/client architecture designed to handle Petabyte/Exabyte volumes of multi-dimensional data is being developed and deployed. As an important part of the EarthServer project, six Lighthouse Applications, major scientific data exploitation initiatives, are being established to make cross-domain, Earth Sciences related data repositories available in an open and unified manner, as service endpoints based on solutions and infrastructure developed within the project. Clients technology developed and deployed in EarthServer ranges from mobile and web clients to immersive virtual reality systems, all designed to interact with a physically and logically distributed server infrastructure using exclusively OGC standards. In this contribution, we would like to present our work on a web-based 3D visualization and interaction client for Earth Sciences data using only technology found in standard web browsers without requiring the user to install plugins or addons. Additionally, we are able to run the earth data visualization client on a wide range of different platforms with very different soft- and hardware requirements such as smart phones (e.g. iOS, Android), different desktop systems etc. High-quality, hardware-accelerated visualization of 3D and 4D content in standard web browsers can be realized now and we believe it will become more and more common to use this fast, lightweight and ubiquitous platform to provide insights into big datasets without requiring the user to set up a specialized client first. With that in mind, we will also point out some of the limitations we encountered using current web technologies. Underlying the EarthServer web client and on top of HTML5, WebGL and JavaScript we have developed the X3DOM framework (www.x3dom.org), which makes possible to embed declarative X3D scenegraphs, an ISO standard XML-based file format for representing 3D computer graphics, directly within HTML, thus enabling developers to rapidly design 3D content that blends seamlessly into HTML interfaces using Javascript. This approach (commonly referred to as a polyfill layer) is used to mimic native web browser support for declarative 3D content and is an important component in our web client architecture.
Chronodes: Interactive Multifocus Exploration of Event Sequences
POLACK, PETER J.; CHEN, SHANG-TSE; KAHNG, MINSUK; DE BARBARO, KAYA; BASOLE, RAHUL; SHARMIN, MOUSHUMI; CHAU, DUEN HORNG
2018-01-01
The advent of mobile health (mHealth) technologies challenges the capabilities of current visualizations, interactive tools, and algorithms. We present Chronodes, an interactive system that unifies data mining and human-centric visualization techniques to support explorative analysis of longitudinal mHealth data. Chronodes extracts and visualizes frequent event sequences that reveal chronological patterns across multiple participant timelines of mHealth data. It then combines novel interaction and visualization techniques to enable multifocus event sequence analysis, which allows health researchers to interactively define, explore, and compare groups of participant behaviors using event sequence combinations. Through summarizing insights gained from a pilot study with 20 behavioral and biomedical health experts, we discuss Chronodes’s efficacy and potential impact in the mHealth domain. Ultimately, we outline important open challenges in mHealth, and offer recommendations and design guidelines for future research. PMID:29515937
ERIC Educational Resources Information Center
Dannhauser, Walter
1980-01-01
Described is an experiment designed to provide an experimental basis for a unifying point of view (utilizing theoretical framework and chemistry laboratory experiments) for physical chemistry students. Three experiments are described: phase equilibrium, chemical equilibrium, and a test of the third law of thermodynamics. (Author/DS)
Persuasive Writing, A Curriculum Design: K-12.
ERIC Educational Resources Information Center
Bennett, Susan G., Ed.
In the spirit of the Texas Hill Country Writing Project and in response to the requirements of the Texas Assessment of Basic Skills, this guide presents writing assignments reflecting a commitment to a unified writing program for kindergarten through grade twelve. The framework for the assignments is adopted from the discourse theory of James…
Practical Issues in Estimating Classification Accuracy and Consistency with R Package cacIRT
ERIC Educational Resources Information Center
Lathrop, Quinn N.
2015-01-01
There are two main lines of research in estimating classification accuracy (CA) and classification consistency (CC) under Item Response Theory (IRT). The R package cacIRT provides computer implementations of both approaches in an accessible and unified framework. Even with available implementations, there remains decisions a researcher faces when…
The Reliability of Setting Grade Boundaries Using Comparative Judgement
ERIC Educational Resources Information Center
Benton, Tom; Elliott, Gill
2016-01-01
In recent years the use of expert judgement to set and maintain examination standards has been increasingly criticised in favour of approaches based on statistical modelling. This paper reviews existing research on this controversy and attempts to unify the evidence within a framework where expertise is utilised in the form of comparative…
Optimization Techniques for Analysis of Biological and Social Networks
2012-03-28
analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms , test and fine...alternative mathematical programming formulations, their theoretical analysis, the development of exact algorithms , and heuristics. Originally, clusters...systematic fashion under a unifying theoretical and algorithmic framework. Optimization, Complex Networks, Social Network Analysis, Computational
Conceptualizing the Suicide-Alcohol Relationship.
ERIC Educational Resources Information Center
Rogers, James R.
Despite the strong empirical evidence linking alcohol use across varying levels to suicidal behavior, the field is lacking a unifying theoretical framework in this area. The concept of alcohol induced myopia to explain the varied effects of alcohol on the behaviors of individuals who drink has been proposed. The term "alcohol myopia" refers to its…
Diffusion of Innovations Theory: A Unifying Framework for HIV Peer Education
ERIC Educational Resources Information Center
Ramseyer Winter, Virginia
2013-01-01
Peer education programs are a popular approach to preventing HIV infection among adolescents. While the programs show promise for effectively preventing HIV among the peers who are provided education, little evaluation research has been conducted to determine if the peer educators themselves experience knowledge, attitude, and behavior changes. A…
Utilizing Emergency Departments as Learning Spaces through a Post-Occupancy Evaluation
ERIC Educational Resources Information Center
Guinther, Lindsey Lawry; Carll-White, Allison
2014-01-01
This case study describes the use of an emergency department as a learning space for interior design students. Kolb's (1984; 2005) framework identifies the characteristics of experiential learning and learning spaces, serving as the bridge to unify learning styles and the learning environment. A post-occupancy evaluation was conducted with…
ERIC Educational Resources Information Center
Ning, Hoi Kwan; Downing, Kevin
2010-01-01
While previous studies have examined the single directional effects of motivation constructs in influencing students' use of self-regulatory strategies, few attempts have been made to unravel their interrelationship in a unified framework. In this study we adopt the social cognitive perspective and examine the reciprocal interplay between…
Professionalization in Universities and European Convergence
ERIC Educational Resources Information Center
Vivas, Amparo Jimenez; Hevia, David Menendez Alvarez
2009-01-01
The constant assessment of the quality of higher education within the framework of European convergence is a challenge for all those universities that wish their degrees and diplomas to reflect a unified Europe. As is the case in any assessment, change and review process, the quest to improve quality implies measuring achievement of the objectives…
Reaching and Remediating "Grey-Area" Middle School Students
ERIC Educational Resources Information Center
Jorgenson, Olaf; Smolkovich, Greg E.
2004-01-01
This article presents a framework for school administrators developed by Mesa Unified School district used in identifying and assisting the subtly struggling adolescents. Mesa's "safety net" approach targets middle grades students in the midst of their formative, pre-high school experience. Here, it is stated that the first step to identify a…
Evolution of Students' Ideas about Natural Selection through a Constructivist Framework
ERIC Educational Resources Information Center
Baumgartner, Erin; Duncan, Kanesa
2009-01-01
Educating students about the process of evolution through natural selection is vitally important because not only is it the unifying theory of biological science, it is also widely regarded as difficult for students to fully comprehend. Anderson and colleagues (2002) describe alternative ideas and misconceptions about natural selection as highly…
ERIC Educational Resources Information Center
DeBray, Elizabeth; Houck, Eric A.
2011-01-01
This article uses an institutional framework to analyze the political context of the next reauthorization of the Elementary and Secondary Education Act. The authors analyze three relevant factors in the institutional environment: the role of traditional party politics, including theories of divided versus unified party government; the entrance of…
Understanding Early Childhood Student Teachers' Acceptance and Use of Interactive Whiteboard
ERIC Educational Resources Information Center
Wong, Kung-Teck; Russo, Sharon; McDowall, Janet
2013-01-01
Purpose: The purpose of this paper is to understand early childhood student teachers' self-reported acceptance and use of interactive whiteboard (IWB), by employing the Unified Theory of Acceptance and Use of Technology (UTAUT) as the research framework. Design/methodology/approach: A total of 112 student teachers enrolled in science-related…
Factors Influencing Students' Adoption of E-Learning: A Structural Equation Modeling Approach
ERIC Educational Resources Information Center
Tarhini, Ali; Masa'deh, Ra'ed; Al-Busaidi, Kamla Ali; Mohammed, Ashraf Bany; Maqableh, Mahmoud
2017-01-01
Purpose: This research aims to examine the factors that may hinder or enable the adoption of e-learning systems by university students. Design/methodology/approach: A conceptual framework was developed through extending the unified theory of acceptance and use of technology (performance expectancy, effort expectancy, hedonic motivation, habit,…
The Long Way towards Abandoning ECEC Dichotomy in Greece
ERIC Educational Resources Information Center
Rentzou, Konstantina
2018-01-01
Although Greece has a dichotomous system both in terms of Early Childhood Education and Care (ECEC) services and in terms of ECEC workers' preparation programmes, in 2016 Greek government's Organization for ECEC organized an open colloquy about the adoption of a 'Unified National Framework for Early Childhood Education and Care', causing a heated…
"A Unified Poet Alliance": The Personal and Social Outcomes of Youth Spoken Word Poetry Programming
ERIC Educational Resources Information Center
Weinstein, Susan
2010-01-01
This article places youth spoken word (YSW) poetry programming within the larger framework of arts education. Drawing primarily on transcripts of interviews with teen poets and adult teaching artists and program administrators, the article identifies specific benefits that participants ascribe to youth spoken word, including the development of…
Countering the Pedagogy of Extremism: Reflective Narratives and Critiques of Problem-Based Learning
ERIC Educational Resources Information Center
Woo, Chris W. H.; Laxman, Kumar
2013-01-01
This paper is a critique against "purist" pedagogies found in the literature of student-centred learning. The article reproves extremism in education and questions the absolutism and teleological truths expounded in exclusive problem-based learning. The paper articulates the framework of a unifying pedagogical practice through Eve…
The Four Elementary Forms of Sociality: Framework for a Unified Theory of Social Relations.
ERIC Educational Resources Information Center
Fiske, Alan Page
1992-01-01
A theory is presented that postulates that people in all cultures use four relational models to generate most kinds of social interaction, evaluation, and affect. Ethnographic and field studies (n=19) have supported cultural variations on communal sharing; authority ranking; equality matching; and market pricing. (SLD)
A Unifying Framework for Teaching Nonparametric Statistical Tests
ERIC Educational Resources Information Center
Bargagliotti, Anna E.; Orrison, Michael E.
2014-01-01
Increased importance is being placed on statistics at both the K-12 and undergraduate level. Research divulging effective methods to teach specific statistical concepts is still widely sought after. In this paper, we focus on best practices for teaching topics in nonparametric statistics at the undergraduate level. To motivate the work, we…
The road against fatalities: infrastructure spending vs. regulation??
Albalate, Daniel; Fernández, Laura; Yarygina, Anastasiya
2013-10-01
The road safety literature is typified by a high degree of compartmentalization between studies that focus on infrastructure and traffic conditions and those devoted to the evaluation of public policies and regulations. As a result, few studies adopt a unified empirical framework in their attempts at evaluating the road safety performance of public interventions, thus limiting our understanding of successful strategies in this regard. This paper considers both types of determinants in an analysis of a European country that has enjoyed considerable success in reducing road fatalities. After constructing a panel data set with road safety outcomes for all Spanish provinces between 1990 and 2009, we evaluate the role of the technical characteristics of infrastructure and recent infrastructure spending together with the main regulatory changes introduced. Our results show the importance of considering both types of determinants in a unified framework. Moreover, we highlight the importance of maintenance spending given its effectiveness in reducing fatalities and casualties in the current economic context of austerity that is having such a marked impact on investment efforts in Spain. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
de Albuquerque, Douglas F.; Fittipaldi, I. P.
1994-05-01
A unified effective-field renormalization-group framework (EFRG) for both quenched bond- and site-diluted Ising models is herein developed by extending recent works. The method, as in the previous works, follows up the same strategy of the mean-field renormalization-group scheme (MFRG), and is achieved by introducing an alternative way for constructing classical effective-field equations of state, based on rigorous Ising spin identities. The concentration dependence of the critical temperature, Tc(p), and the critical concentrations of magnetic atoms, pc, at which the transition temperature goes to zero, are evaluated for several two- and three-dimensional lattice structures. The obtained values of Tc and pc and the resulting phase diagrams for both bond and site cases are much more accurate than those estimated by the standard MFRG approach. Although preserving the same level of simplicity as the MFRG, it is shown that the present EFRG method, even by considering its simplest size-cluster version, provides results that correctly distinguishes those lattices that have the same coordination number, but differ in dimensionality or geometry.
Disaster Metrics: A Comprehensive Framework for Disaster Evaluation Typologies.
Wong, Diana F; Spencer, Caroline; Boyd, Lee; Burkle, Frederick M; Archer, Frank
2017-10-01
Introduction The frequency of disasters is increasing around the world with more people being at risk. There is a moral imperative to improve the way in which disaster evaluations are undertaken and reported with the aim of reducing preventable mortality and morbidity in future events. Disasters are complex events and undertaking disaster evaluations is a specialized area of study at an international level. Hypothesis/Problem While some frameworks have been developed to support consistent disaster research and evaluation, they lack validation, consistent terminology, and standards for reporting across the different phases of a disaster. There is yet to be an agreed, comprehensive framework to structure disaster evaluation typologies. The aim of this paper is to outline an evolving comprehensive framework for disaster evaluation typologies. It is anticipated that this new framework will facilitate an agreement on identifying, structuring, and relating the various evaluations found in the disaster setting with a view to better understand the process, outcomes, and impacts of the effectiveness and efficiency of interventions. Research was undertaken in two phases: (1) a scoping literature review (peer-reviewed and "grey literature") was undertaken to identify current evaluation frameworks and typologies used in the disaster setting; and (2) a structure was developed that included the range of typologies identified in Phase One and suggests possible relationships in the disaster setting. No core, unifying framework to structure disaster evaluation and research was identified in the literature. The authors propose a "Comprehensive Framework for Disaster Evaluation Typologies" that identifies, structures, and suggests relationships for the various typologies detected. The proposed Comprehensive Framework for Disaster Evaluation Typologies outlines the different typologies of disaster evaluations that were identified in this study and brings them together into a single framework. This unique, unifying framework has relevance at an international level and is expected to benefit the disaster, humanitarian, and development sectors. The next step is to undertake a validation process that will include international leaders with experience in evaluation, in general, and disasters specifically. This work promotes an environment for constructive dialogue on evaluations in the disaster setting to strengthen the evidence base for interventions across the disaster spectrum. It remains a work in progress. Wong DF , Spencer C , Boyd L , Burkle FM Jr. , Archer F . Disaster metrics: a comprehensive framework for disaster evaluation typologies. Prehosp Disaster Med. 2017;32(5):501-514.
Buetow, S; Adair, V; Coster, G; Hight, M; Gribben, B; Mitchell, E
2002-01-01
BACKGROUND: Different sets of literature suggest how aspects of practice time management can limit access to general practitioner (GP) care. Researchers have not organised this knowledge into a unified framework that can enhance understanding of barriers to, and opportunities for, improved access. AIM: To suggest a framework conceptualising how differences in professional and cultural understanding of practice time management in Auckland, New Zealand, influence access to GP care for children with chronic asthma. DESIGN OF STUDY: A qualitative study involving selective sampling, semi-structured interviews on barriers to access, and a general inductive approach. SETTING: Twenty-nine key informants and ten mothers of children with chronic, moderate to severe asthma and poor access to GP care in Auckland. METHOD: Development of a framework from themes describing barriers associated with, and needs for, practice time management. The themes were independently identified by two authors from transcribed interviews and confirmed through informant checking. Themes from key informant and patient interviews were triangulated with each other and with published literature. RESULTS: The framework distinguishes 'practice-centred time' from 'patient-centred time.' A predominance of 'practice-centred time' and an unmet opportunity for 'patient-centred time' are suggested by the persistence of five barriers to accessing GP care: limited hours of opening; traditional appointment systems; practice intolerance of missed appointments; long waiting times in the practice; and inadequate consultation lengths. None of the barriers is specific to asthmatic children. CONCLUSION: A unified framework was suggested for understanding how the organisation of practice work time can influence access to GP care by groups including asthmatic children. PMID:12528583
Models for evaluating the performability of degradable computing systems
NASA Technical Reports Server (NTRS)
Wu, L. T.
1982-01-01
Recent advances in multiprocessor technology established the need for unified methods to evaluate computing systems performance and reliability. In response to this modeling need, a general modeling framework that permits the modeling, analysis and evaluation of degradable computing systems is considered. Within this framework, several user oriented performance variables are identified and shown to be proper generalizations of the traditional notions of system performance and reliability. Furthermore, a time varying version of the model is developed to generalize the traditional fault tree reliability evaluation methods of phased missions.
Einstein-Yang-Mills-Dirac systems from the discretized Kaluza-Klein theory
NASA Astrophysics Data System (ADS)
Wali, Kameshwar; Viet, Nguyen Ali
2017-01-01
A unified theory of the non-Abelian gauge interactions with gravity in the framework of a discretized Kaluza-Klein theory is constructed with a modified Dirac operator and wedge product. All the couplings of chiral spinors to the non-Abelian gauge fields emerge naturally as components of the coupling of the chiral spinors in the generalized gravity together with some new interactions. In particular, the currently prevailing gravity-QCD quark and gravity-electroweak-quark and lepton models are shown to follow as special cases of the general framework.
NASA Technical Reports Server (NTRS)
Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter
2002-01-01
The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.
Freiburg RNA tools: a central online resource for RNA-focused research and teaching.
Raden, Martin; Ali, Syed M; Alkhnbashi, Omer S; Busch, Anke; Costa, Fabrizio; Davis, Jason A; Eggenhofer, Florian; Gelhausen, Rick; Georg, Jens; Heyne, Steffen; Hiller, Michael; Kundu, Kousik; Kleinkauf, Robert; Lott, Steffen C; Mohamed, Mostafa M; Mattheis, Alexander; Miladi, Milad; Richter, Andreas S; Will, Sebastian; Wolff, Joachim; Wright, Patrick R; Backofen, Rolf
2018-05-21
The Freiburg RNA tools webserver is a well established online resource for RNA-focused research. It provides a unified user interface and comprehensive result visualization for efficient command line tools. The webserver includes RNA-RNA interaction prediction (IntaRNA, CopraRNA, metaMIR), sRNA homology search (GLASSgo), sequence-structure alignments (LocARNA, MARNA, CARNA, ExpaRNA), CRISPR repeat classification (CRISPRmap), sequence design (antaRNA, INFO-RNA, SECISDesign), structure aberration evaluation of point mutations (RaSE), and RNA/protein-family models visualization (CMV), and other methods. Open education resources offer interactive visualizations of RNA structure and RNA-RNA interaction prediction as well as basic and advanced sequence alignment algorithms. The services are freely available at http://rna.informatik.uni-freiburg.de.
De Ridder, Dirk; Vanneste, Sven; Weisz, Nathan; Londero, Alain; Schlee, Winnie; Elgoyhen, Ana Belen; Langguth, Berthold
2014-07-01
Tinnitus is a considered to be an auditory phantom phenomenon, a persistent conscious percept of a salient memory trace, externally attributed, in the absence of a sound source. It is perceived as a phenomenological unified coherent percept, binding multiple separable clinical characteristics, such as its loudness, the sidedness, the type (pure tone, noise), the associated distress and so on. A theoretical pathophysiological framework capable of explaining all these aspects in one model is highly needed. The model must incorporate both the deafferentation based neurophysiological models and the dysfunctional noise canceling model, and propose a 'tinnitus core' subnetwork. The tinnitus core can be defined as the minimal set of brain areas that needs to be jointly activated (=subnetwork) for tinnitus to be consciously perceived, devoid of its affective components. The brain areas involved in the other separable characteristics of tinnitus can be retrieved by studies on spontaneous resting state magnetic and electrical activity in people with tinnitus, evaluated for the specific aspect investigated and controlled for other factors. By combining these functional imaging studies with neuromodulation techniques some of the correlations are turned into causal relationships. Thereof, a heuristic pathophysiological framework is constructed, integrating the tinnitus perceptual core with the other tinnitus related aspects. This phenomenological unified percept of tinnitus can be considered an emergent property of multiple, parallel, dynamically changing and partially overlapping subnetworks, each with a specific spontaneous oscillatory pattern and functional connectivity signature. Communication between these different subnetworks is proposed to occur at hubs, brain areas that are involved in multiple subnetworks simultaneously. These hubs can take part in each separable subnetwork at different frequencies. Communication between the subnetworks is proposed to occur at discrete oscillatory frequencies. As such, the brain uses multiple nonspecific networks in parallel, each with their own oscillatory signature, that adapt to the context to construct a unified percept possibly by synchronized activation integrated at hubs at discrete oscillatory frequencies. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Tallapragada, V.
2017-12-01
NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.
A Semantic Grid Oriented to E-Tourism
NASA Astrophysics Data System (ADS)
Zhang, Xiao Ming
With increasing complexity of tourism business models and tasks, there is a clear need of the next generation e-Tourism infrastructure to support flexible automation, integration, computation, storage, and collaboration. Currently several enabling technologies such as semantic Web, Web service, agent and grid computing have been applied in the different e-Tourism applications, however there is no a unified framework to be able to integrate all of them. So this paper presents a promising e-Tourism framework based on emerging semantic grid, in which a number of key design issues are discussed including architecture, ontologies structure, semantic reconciliation, service and resource discovery, role based authorization and intelligent agent. The paper finally provides the implementation of the framework.
Deontological coherence: A framework for commonsense moral reasoning.
Holyoak, Keith J; Powell, Derek
2016-11-01
We review a broad range of work, primarily in cognitive and social psychology, that provides insight into the processes of moral judgment. In particular, we consider research on pragmatic reasoning about regulations and on coherence in decision making, both areas in which psychological theories have been guided by work in legal philosophy. Armed with these essential prerequisites, we sketch a psychological framework for how ordinary people make judgments about moral issues. Based on a literature review, we show how the framework of deontological coherence unifies findings in moral psychology that have often been explained in terms of a grab-bag of heuristics and biases. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
A unifying framework for ghost-free Lorentz-invariant Lagrangian field theories
NASA Astrophysics Data System (ADS)
Li, Wenliang
2018-04-01
We propose a framework for Lorentz-invariant Lagrangian field theories where Ostrogradsky's scalar ghosts could be absent. A key ingredient is the generalized Kronecker delta. The general Lagrangians are reformulated in the language of differential forms. The absence of higher order equations of motion for the scalar modes stems from the basic fact that every exact form is closed. The well-established Lagrangian theories for spin-0, spin-1, p-form, spin-2 fields have natural formulations in this framework. We also propose novel building blocks for Lagrangian field theories. Some of them are novel nonlinear derivative terms for spin-2 fields. It is nontrivial that Ostrogradsky's scalar ghosts are absent in these fully nonlinear theories.
Zhai, Di-Hua; Xia, Yuanqing
2018-02-01
This paper addresses the adaptive control for task-space teleoperation systems with constrained predefined synchronization error, where a novel switched control framework is investigated. Based on multiple Lyapunov-Krasovskii functionals method, the stability of the resulting closed-loop system is established in the sense of state-independent input-to-output stability. Compared with previous work, the developed method can simultaneously handle the unknown kinematics/dynamics, asymmetric varying time delays, and prescribed performance control in a unified framework. It is shown that the developed controller can guarantee the prescribed transient-state and steady-state synchronization performances between the master and slave robots, which is demonstrated by the simulation study.
FAST: framework for heterogeneous medical image computing and visualization.
Smistad, Erik; Bozorgi, Mohammadmehdi; Lindseth, Frank
2015-11-01
Computer systems are becoming increasingly heterogeneous in the sense that they consist of different processors, such as multi-core CPUs and graphic processing units. As the amount of medical image data increases, it is crucial to exploit the computational power of these processors. However, this is currently difficult due to several factors, such as driver errors, processor differences, and the need for low-level memory handling. This paper presents a novel FrAmework for heterogeneouS medical image compuTing and visualization (FAST). The framework aims to make it easier to simultaneously process and visualize medical images efficiently on heterogeneous systems. FAST uses common image processing programming paradigms and hides the details of memory handling from the user, while enabling the use of all processors and cores on a system. The framework is open-source, cross-platform and available online. Code examples and performance measurements are presented to show the simplicity and efficiency of FAST. The results are compared to the insight toolkit (ITK) and the visualization toolkit (VTK) and show that the presented framework is faster with up to 20 times speedup on several common medical imaging algorithms. FAST enables efficient medical image computing and visualization on heterogeneous systems. Code examples and performance evaluations have demonstrated that the toolkit is both easy to use and performs better than existing frameworks, such as ITK and VTK.
Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin
2017-01-01
There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation. PMID:28225811
Sun, Mingzhu; Xu, Hui; Zeng, Xingjuan; Zhao, Xin
2017-01-01
There are various fantastic biological phenomena in biological pattern formation. Mathematical modeling using reaction-diffusion partial differential equation systems is employed to study the mechanism of pattern formation. However, model parameter selection is both difficult and time consuming. In this paper, a visual feedback simulation framework is proposed to calculate the parameters of a mathematical model automatically based on the basic principle of feedback control. In the simulation framework, the simulation results are visualized, and the image features are extracted as the system feedback. Then, the unknown model parameters are obtained by comparing the image features of the simulation image and the target biological pattern. Considering two typical applications, the visual feedback simulation framework is applied to fulfill pattern formation simulations for vascular mesenchymal cells and lung development. In the simulation framework, the spot, stripe, labyrinthine patterns of vascular mesenchymal cells, the normal branching pattern and the branching pattern lacking side branching for lung branching are obtained in a finite number of iterations. The simulation results indicate that it is easy to achieve the simulation targets, especially when the simulation patterns are sensitive to the model parameters. Moreover, this simulation framework can expand to other types of biological pattern formation.
Have We Achieved a Unified Model of Photoreceptor Cell Fate Specification in Vertebrates?
Raymond, Pamela A.
2008-01-01
How does a retinal progenitor choose to differentiate as a rod or a cone and, if it becomes a cone, which one of their different subtypes? The mechanisms of photoreceptor cell fate specification and differentiation have been extensively investigated in a variety of animal model systems, including human and non-human primates, rodents (mice and rats), chickens, frogs (Xenopus) and fish. It appears timely to discuss whether it is possible to synthesize the resulting information into a unified model applicable to all vertebrates. In this review we focus on several widely used experimental animal model systems to highlight differences in photoreceptor properties among species, the diversity of developmental strategies and solutions that vertebrates use to create retinas with photoreceptors that are adapted to the visual needs of their species, and the limitations of the methods currently available for the investigation of photoreceptor cell fate specification. Based on these considerations, we conclude that we are not yet ready to construct a unified model of photoreceptor cell fate specification in the developing vertebrate retina. PMID:17466954
A massively asynchronous, parallel brain.
Zeki, Semir
2015-05-19
Whether the visual brain uses a parallel or a serial, hierarchical, strategy to process visual signals, the end result appears to be that different attributes of the visual scene are perceived asynchronously--with colour leading form (orientation) by 40 ms and direction of motion by about 80 ms. Whatever the neural root of this asynchrony, it creates a problem that has not been properly addressed, namely how visual attributes that are perceived asynchronously over brief time windows after stimulus onset are bound together in the longer term to give us a unified experience of the visual world, in which all attributes are apparently seen in perfect registration. In this review, I suggest that there is no central neural clock in the (visual) brain that synchronizes the activity of different processing systems. More likely, activity in each of the parallel processing-perceptual systems of the visual brain is reset independently, making of the brain a massively asynchronous organ, just like the new generation of more efficient computers promise to be. Given the asynchronous operations of the brain, it is likely that the results of activities in the different processing-perceptual systems are not bound by physiological interactions between cells in the specialized visual areas, but post-perceptually, outside the visual brain.
Understanding public perceptions of biotechnology through the "Integrative Worldview Framework".
De Witt, Annick; Osseweijer, Patricia; Pierce, Robin
2015-07-03
Biotechnological innovations prompt a range of societal responses that demand understanding. Research has shown such responses are shaped by individuals' cultural worldviews. We aim to demonstrate how the Integrative Worldview Framework (IWF) can be used for analyzing perceptions of biotechnology, by reviewing (1) research on public perceptions of biotechnology and (2) analyses of the stakeholder-debate on the bio-based economy, using the Integrative Worldview Framework (IWF) as analytical lens. This framework operationalizes the concept of worldview and distinguishes between traditional, modern, and postmodern worldviews, among others. Applied to these literatures, this framework illuminates how these worldviews underlie major societal responses, thereby providing a unifying understanding of the literature on perceptions of biotechnology. We conclude the IWF has relevance for informing research on perceptions of socio-technical changes, generating insight into the paradigmatic gaps in social science, and facilitating reflexive and inclusive policy-making and debates on these timely issues. © The Author(s) 2015.
Keltner, Dacher; Kogan, Aleksandr; Piff, Paul K; Saturn, Sarina R
2014-01-01
The study of prosocial behavior--altruism, cooperation, trust, and the related moral emotions--has matured enough to produce general scholarly consensus that prosociality is widespread, intuitive, and rooted deeply within our biological makeup. Several evolutionary frameworks model the conditions under which prosocial behavior is evolutionarily viable, yet no unifying treatment exists of the psychological decision-making processes that result in prosociality. Here, we provide such a perspective in the form of the sociocultural appraisals, values, and emotions (SAVE) framework of prosociality. We review evidence for the components of our framework at four levels of analysis: intrapsychic, dyadic, group, and cultural. Within these levels, we consider how phenomena such as altruistic punishment, prosocial contagion, self-other similarity, and numerous others give rise to prosocial behavior. We then extend our reasoning to chart the biological underpinnings of prosociality and apply our framework to understand the role of social class in prosociality.
Probabilistic arithmetic automata and their applications.
Marschall, Tobias; Herms, Inke; Kaltenbach, Hans-Michael; Rahmann, Sven
2012-01-01
We present a comprehensive review on probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two algorithms to numerically compute the distribution of the results of such probabilistic calculations. PAAs provide a unifying framework to approach many problems arising in computational biology and elsewhere. We present five different applications, namely 1) pattern matching statistics on random texts, including the computation of the distribution of occurrence counts, waiting times, and clump sizes under hidden Markov background models; 2) exact analysis of window-based pattern matching algorithms; 3) sensitivity of filtration seeds used to detect candidate sequence alignments; 4) length and mass statistics of peptide fragments resulting from enzymatic cleavage reactions; and 5) read length statistics of 454 and IonTorrent sequencing reads. The diversity of these applications indicates the flexibility and unifying character of the presented framework. While the construction of a PAA depends on the particular application, we single out a frequently applicable construction method: We introduce deterministic arithmetic automata (DAAs) to model deterministic calculations on sequences, and demonstrate how to construct a PAA from a given DAA and a finite-memory random text model. This procedure is used for all five discussed applications and greatly simplifies the construction of PAAs. Implementations are available as part of the MoSDi package. Its application programming interface facilitates the rapid development of new applications based on the PAA framework.
United We Stand: Emphasizing Commonalities Across Cognitive-Behavioral Therapies
Mennin, Douglas S.; Ellard, Kristen K.; Fresco, David M.; Gross, James J.
2016-01-01
Cognitive behavioral therapy (CBT) has a rich history of alleviating the suffering associated with mental disorders. Recently, there have been exciting new developments, including multi-component approaches, incorporated alternative therapies (e.g., meditation), targeted and cost-effective technologies, and integrated biological and behavioral frameworks. These field-wide changes have led some to emphasize the differences among variants of CBT. Here, we draw attention to commonalities across cognitive-behavioral therapies, including shared goals, change principles, and therapeutic processes. Specifically, we offer a framework for examining common CBT characteristics that emphasizes behavioral adaptation as a unifying goal and three core change principles, namely (1) context engagement to promote adaptive imagining and enacting of new experiences; (2) attention change to promote adaptive sustaining, shifting, and broadening of attention; and (3) cognitive change to promote adaptive perspective taking on events so as to alter verbal meanings. Further, we argue that specific intervention components including behavioral exposure/activation, attention training, acceptance/tolerance, decentering/defusion, and cognitive reframing may be emphasized to a greater or lesser degree by different treatment packages but are still fundamentally common therapeutic processes that are present across approaches and are best understood by their relationships to these core CBT change principles. We conclude by arguing for shared methodological and design frameworks for investigating unique and common characteristics to advance a unified and strong voice for CBT in a widening, increasingly multimodal and interdisciplinary, intervention science. PMID:23611074
NASA Astrophysics Data System (ADS)
McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.
2017-06-01
Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.
McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; Connell, Dylan O'; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J
2017-06-07
Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of 'partial' imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.
McClelland, Jamie R; Modat, Marc; Arridge, Simon; Grimes, Helen; D’Souza, Derek; Thomas, David; Connell, Dylan O’; Low, Daniel A; Kaza, Evangelia; Collins, David J; Leach, Martin O; Hawkes, David J
2017-01-01
Abstract Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated. PMID:28195833
Coupled dictionary learning for joint MR image restoration and segmentation
NASA Astrophysics Data System (ADS)
Yang, Xuesong; Fan, Yong
2018-03-01
To achieve better segmentation of MR images, image restoration is typically used as a preprocessing step, especially for low-quality MR images. Recent studies have demonstrated that dictionary learning methods could achieve promising performance for both image restoration and image segmentation. These methods typically learn paired dictionaries of image patches from different sources and use a common sparse representation to characterize paired image patches, such as low-quality image patches and their corresponding high quality counterparts for the image restoration, and image patches and their corresponding segmentation labels for the image segmentation. Since learning these dictionaries jointly in a unified framework may improve the image restoration and segmentation simultaneously, we propose a coupled dictionary learning method to concurrently learn dictionaries for joint image restoration and image segmentation based on sparse representations in a multi-atlas image segmentation framework. Particularly, three dictionaries, including a dictionary of low quality image patches, a dictionary of high quality image patches, and a dictionary of segmentation label patches, are learned in a unified framework so that the learned dictionaries of image restoration and segmentation can benefit each other. Our method has been evaluated for segmenting the hippocampus in MR T1 images collected with scanners of different magnetic field strengths. The experimental results have demonstrated that our method achieved better image restoration and segmentation performance than state of the art dictionary learning and sparse representation based image restoration and image segmentation methods.
ERIC Educational Resources Information Center
Dillon, Steve; Adkins, Barbara; Brown, Andrew; Hirche, Kathy
2009-01-01
In this article, we examine the affordances of the concept of "network jamming" as a means of facilitating social and cultural interaction, that provides a basis for unified communities that use sound and visual media as their key expressive medium. This article focuses upon the development of a means of measuring social and musical benefit…
A Unified Data-Driven Approach for Programming In Situ Analysis and Visualization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aiken, Alex
The placement and movement of data is becoming the key limiting factor on both performance and energy efficiency of high performance computations. As systems generate more data, it is becoming increasingly difficult to actually move that data elsewhere for post-processing, as the rate of improvements in supporting I/O infrastructure is not keeping pace. Together, these trends are creating a shift in how we think about exascale computations, from a viewpoint that focuses on FLOPS to one that focuses on data and data-centric operations as fundamental to the reasoning about, and optimization of, scientific workflows on extreme-scale architectures. The overarching goalmore » of our effort was the study of a unified data-driven approach for programming applications and in situ analysis and visualization. Our work was to understand the interplay between data-centric programming model requirements at extreme-scale and the overall impact of those requirements on the design, capabilities, flexibility, and implementation details for both applications and the supporting in situ infrastructure. In this context, we made many improvements to the Legion programming system (one of the leading data-centric models today) and demonstrated in situ analyses on real application codes using these improvements.« less
The role of the parahippocampal cortex in cognition
Aminoff, Elissa M.; Kveraga, Kestutis; Bar, Moshe
2013-01-01
The parahippocampal cortex (PHC) has been associated with many cognitive processes, including visuospatial processing and episodic memory. To characterize the role of PHC in cognition a framework is required that unifies these disparate processes. An overarching account was proposed, whereby the PHC is part of a network of brain regions that processes contextual associations. Contextual associations are the principal element underlying many higher-level cognitive processes, and thus are suitable for unifying the PHC literature. Recent findings are reviewed that provide support for the contextual associations account of PHC function. In addition to reconciling a vast breadth of literature, the synthesis presented expands the implications of the proposed account and gives rise to new and general questions about context and cognition. PMID:23850264
Dai, Jiayu; Hou, Yong; Yuan, Jianmin
2010-06-18
Electron-ion interactions are central to numerous phenomena in the warm dense matter (WDM) regime and at higher temperature. The electron-ion collisions induced friction at high temperature is introduced in the procedure of ab initio molecular dynamics using the Langevin equation based on density functional theory. In this framework, as a test for Fe and H up to 1000 eV, the equation of state and the transition of electronic structures of the materials with very wide density and temperature can be described, which covers a full range of WDM up to high energy density physics. A unified first principles description from condensed matter to ideal ionized gas plasma is constructed.
Multiscale geometric modeling of macromolecules II: Lagrangian representation
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-01-01
Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR and cryo-EM, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger’s functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, while our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599
Geo3DML: A standard-based exchange format for 3D geological models
NASA Astrophysics Data System (ADS)
Wang, Zhangang; Qu, Honggang; Wu, Zixing; Wang, Xianghong
2018-01-01
A geological model (geomodel) in three-dimensional (3D) space is a digital representation of the Earth's subsurface, recognized by geologists and stored in resultant geological data (geodata). The increasing demand for data management and interoperable applications of geomodelscan be addressed by developing standard-based exchange formats for the representation of not only a single geological object, but also holistic geomodels. However, current standards such as GeoSciML cannot incorporate all the geomodel-related information. This paper presents Geo3DML for the exchange of 3D geomodels based on the existing Open Geospatial Consortium (OGC) standards. Geo3DML is based on a unified and formal representation of structural models, attribute models and hierarchical structures of interpreted resultant geodata in different dimensional views, including drills, cross-sections/geomaps and 3D models, which is compatible with the conceptual model of GeoSciML. Geo3DML aims to encode all geomodel-related information integrally in one framework, including the semantic and geometric information of geoobjects and their relationships, as well as visual information. At present, Geo3DML and some supporting tools have been released as a data-exchange standard by the China Geological Survey (CGS).
Wang, Changhan; Yan, Xinchen; Smith, Max; Kochhar, Kanika; Rubin, Marcie; Warren, Stephen M; Wrobel, James; Lee, Honglak
2015-01-01
Wound surface area changes over multiple weeks are highly predictive of the wound healing process. Furthermore, the quality and quantity of the tissue in the wound bed also offer important prognostic information. Unfortunately, accurate measurements of wound surface area changes are out of reach in the busy wound practice setting. Currently, clinicians estimate wound size by estimating wound width and length using a scalpel after wound treatment, which is highly inaccurate. To address this problem, we propose an integrated system to automatically segment wound regions and analyze wound conditions in wound images. Different from previous segmentation techniques which rely on handcrafted features or unsupervised approaches, our proposed deep learning method jointly learns task-relevant visual features and performs wound segmentation. Moreover, learned features are applied to further analysis of wounds in two ways: infection detection and healing progress prediction. To the best of our knowledge, this is the first attempt to automate long-term predictions of general wound healing progress. Our method is computationally efficient and takes less than 5 seconds per wound image (480 by 640 pixels) on a typical laptop computer. Our evaluations on a large-scale wound database demonstrate the effectiveness and reliability of the proposed system.
Robustness surfaces of complex networks
Manzano, Marc; Sahneh, Faryad; Scoglio, Caterina; Calle, Eusebi; Marzo, Jose Luis
2014-01-01
Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared. PMID:25178402
Toward critical spatial thinking in the social sciences and humanities.
Goodchild, Michael F; Janelle, Donald G
2010-02-01
The integration of geographically referenced information into the conceptual frameworks and applied uses of the social sciences and humanities has been an ongoing process over the past few centuries. It has gained momentum in recent decades with advances in technologies for computation and visualization and with the arrival of new data sources. This article begins with an overview of this transition, and argues that the spatial integration of information resources and the cross-disciplinary sharing of analysis and representation methodologies are important forces for the integration of scientific and artistic expression, and that they draw on core concepts in spatial (and spatio-temporal) thinking. We do not suggest that this is akin to prior concepts of unified knowledge systems, but we do maintain that the boundaries to knowledge transfer are disintegrating and that our abilities in problem solving for purposes of artistic expression and scientific development are enhanced through spatial perspectives. Moreover, approaches to education at all levels must recognize the need to impart proficiency in the critical and efficient application of these fundamental spatial concepts, if students and researchers are to make use of expanding access to a broadening range of spatialized information and data processing technologies.
Lu, Songjian; Jin, Bo; Cowart, L Ashley; Lu, Xinghua
2013-01-01
Genetic and pharmacological perturbation experiments, such as deleting a gene and monitoring gene expression responses, are powerful tools for studying cellular signal transduction pathways. However, it remains a challenge to automatically derive knowledge of a cellular signaling system at a conceptual level from systematic perturbation-response data. In this study, we explored a framework that unifies knowledge mining and data mining towards the goal. The framework consists of the following automated processes: 1) applying an ontology-driven knowledge mining approach to identify functional modules among the genes responding to a perturbation in order to reveal potential signals affected by the perturbation; 2) applying a graph-based data mining approach to search for perturbations that affect a common signal; and 3) revealing the architecture of a signaling system by organizing signaling units into a hierarchy based on their relationships. Applying this framework to a compendium of yeast perturbation-response data, we have successfully recovered many well-known signal transduction pathways; in addition, our analysis has led to many new hypotheses regarding the yeast signal transduction system; finally, our analysis automatically organized perturbed genes as a graph reflecting the architecture of the yeast signaling system. Importantly, this framework transformed molecular findings from a gene level to a conceptual level, which can be readily translated into computable knowledge in the form of rules regarding the yeast signaling system, such as "if genes involved in the MAPK signaling are perturbed, genes involved in pheromone responses will be differentially expressed."
A Unified Estimation Framework for State-Related Changes in Effective Brain Connectivity.
Samdin, S Balqis; Ting, Chee-Ming; Ombao, Hernando; Salleh, Sh-Hussain
2017-04-01
This paper addresses the critical problem of estimating time-evolving effective brain connectivity. Current approaches based on sliding window analysis or time-varying coefficient models do not simultaneously capture both slow and abrupt changes in causal interactions between different brain regions. To overcome these limitations, we develop a unified framework based on a switching vector autoregressive (SVAR) model. Here, the dynamic connectivity regimes are uniquely characterized by distinct vector autoregressive (VAR) processes and allowed to switch between quasi-stationary brain states. The state evolution and the associated directed dependencies are defined by a Markov process and the SVAR parameters. We develop a three-stage estimation algorithm for the SVAR model: 1) feature extraction using time-varying VAR (TV-VAR) coefficients, 2) preliminary regime identification via clustering of the TV-VAR coefficients, 3) refined regime segmentation by Kalman smoothing and parameter estimation via expectation-maximization algorithm under a state-space formulation, using initial estimates from the previous two stages. The proposed framework is adaptive to state-related changes and gives reliable estimates of effective connectivity. Simulation results show that our method provides accurate regime change-point detection and connectivity estimates. In real applications to brain signals, the approach was able to capture directed connectivity state changes in functional magnetic resonance imaging data linked with changes in stimulus conditions, and in epileptic electroencephalograms, differentiating ictal from nonictal periods. The proposed framework accurately identifies state-dependent changes in brain network and provides estimates of connectivity strength and directionality. The proposed approach is useful in neuroscience studies that investigate the dynamics of underlying brain states.
Systemic risk in a unifying framework for cascading processes on networks
NASA Astrophysics Data System (ADS)
Lorenz, J.; Battiston, S.; Schweitzer, F.
2009-10-01
We introduce a general framework for models of cascade and contagion processes on networks, to identify their commonalities and differences. In particular, models of social and financial cascades, as well as the fiber bundle model, the voter model, and models of epidemic spreading are recovered as special cases. To unify their description, we define the net fragility of a node, which is the difference between its fragility and the threshold that determines its failure. Nodes fail if their net fragility grows above zero and their failure increases the fragility of neighbouring nodes, thus possibly triggering a cascade. In this framework, we identify three classes depending on the way the fragility of a node is increased by the failure of a neighbour. At the microscopic level, we illustrate with specific examples how the failure spreading pattern varies with the node triggering the cascade, depending on its position in the network and its degree. At the macroscopic level, systemic risk is measured as the final fraction of failed nodes, X*, and for each of the three classes we derive a recursive equation to compute its value. The phase diagram of X* as a function of the initial conditions, thus allows for a prediction of the systemic risk as well as a comparison of the three different model classes. We could identify which model class leads to a first-order phase transition in systemic risk, i.e. situations where small changes in the initial conditions determine a global failure. Eventually, we generalize our framework to encompass stochastic contagion models. This indicates the potential for further generalizations.
VisIVO: A Library and Integrated Tools for Large Astrophysical Dataset Exploration
NASA Astrophysics Data System (ADS)
Becciani, U.; Costa, A.; Ersotelos, N.; Krokos, M.; Massimino, P.; Petta, C.; Vitello, F.
2012-09-01
VisIVO provides an integrated suite of tools and services that can be used in many scientific fields. VisIVO development starts in the Virtual Observatory framework. VisIVO allows users to visualize meaningfully highly-complex, large-scale datasets and create movies of these visualizations based on distributed infrastructures. VisIVO supports high-performance, multi-dimensional visualization of large-scale astrophysical datasets. Users can rapidly obtain meaningful visualizations while preserving full and intuitive control of the relevant parameters. VisIVO consists of VisIVO Desktop - a stand-alone application for interactive visualization on standard PCs, VisIVO Server - a platform for high performance visualization, VisIVO Web - a custom designed web portal, VisIVOSmartphone - an application to exploit the VisIVO Server functionality and the latest VisIVO features: VisIVO Library allows a job running on a computational system (grid, HPC, etc.) to produce movies directly with the code internal data arrays without the need to produce intermediate files. This is particularly important when running on large computational facilities, where the user wants to have a look at the results during the data production phase. For example, in grid computing facilities, images can be produced directly in the grid catalogue while the user code is running in a system that cannot be directly accessed by the user (a worker node). The deployment of VisIVO on the DG and gLite is carried out with the support of EDGI and EGI-Inspire projects. Depending on the structure and size of datasets under consideration, the data exploration process could take several hours of CPU for creating customized views and the production of movies could potentially last several days. For this reason an MPI parallel version of VisIVO could play a fundamental role in increasing performance, e.g. it could be automatically deployed on nodes that are MPI aware. A central concept in our development is thus to produce unified code that can run either on serial nodes or in parallel by using HPC oriented grid nodes. Another important aspect, to obtain as high performance as possible, is the integration of VisIVO processes with grid nodes where GPUs are available. We have selected CUDA for implementing a range of computationally heavy modules. VisIVO is supported by EGI-Inspire, EDGI and SCI-BUS projects.
Global Science and Social Systems: The Essentials of Montessori Education and Peace Frameworks
ERIC Educational Resources Information Center
Kahn, David
2016-01-01
Inspired by Baiba Krumins-Grazzini's interdependencies lecture at NAMTA's Portland conference, David Kahn shows the unifying structures of the program that are rooted in the natural and social sciences. Through a connective web, these sciences explore the integration of all knowledge and lead to a philosophical view of life on earth, including…
String Theory: Big Problem for Small Size
ERIC Educational Resources Information Center
Sahoo, S.
2009-01-01
String theory is the most promising candidate theory for a unified description of all the fundamental forces that exist in nature. It provides a mathematical framework that combines quantum theory with Einstein's general theory of relativity. The typical size of a string is of the order of 10[superscript -33] cm, called the Planck length. But due…
A Unified Algebraic and Logic-Based Framework Towards Safe Routing Implementations
2015-08-13
Software - defined Networks ( SDN ). We developed a declarative platform for implementing SDN protocols using declarative...and debugging several SDN applications. Example-based SDN synthesis. Recent emergence of software - defined networks offers an opportunity to design...domain of Software - defined Networks ( SDN ). We developed a declarative platform for implementing SDN protocols using declarative networking
At the Edge of Chaos: A New Paradigm for Social Work?
ERIC Educational Resources Information Center
Hudson, Christopher G.
2000-01-01
Reviews key concepts and applications of chaos theory and the broader complex systems theory in the context of general systems theory and the search for a unified conceptual framework for social work. Concludes that chaos theory shows promise as a solution to many problems posed by the now dated general systems approach. (DB)
The Qubit as Key to Quantum Physics Part II: Physical Realizations and Applications
ERIC Educational Resources Information Center
Dür, Wolfgang; Heusler, Stefan
2016-01-01
Using the simplest possible quantum system--the qubit--the fundamental concepts of quantum physics can be introduced. This highlights the common features of many different physical systems, and provides a unifying framework when teaching quantum physics at the high school or introductory level. In a previous "TPT" article and in a…
Gender Divide and Acceptance of Collaborative Web 2.0 Applications for Learning in Higher Education
ERIC Educational Resources Information Center
Huang, Wen-Hao David; Hood, Denice Ward; Yoo, Sun Joo
2013-01-01
Situated in the gender digital divide framework, this survey study investigated the role of computer anxiety in influencing female college students' perceptions toward Web 2.0 applications for learning. Based on 432 college students' "Web 2.0 for learning" perception ratings collected by relevant categories of "Unified Theory of Acceptance and Use…
The Administrator Training Program. A Model of Educational Leadership.
ERIC Educational Resources Information Center
Funderburg, Jean; And Others
This paper describes the Administrator Training Program (ATP), a joint venture between San Jose Unified School District and Stanford University. A discussion of the ATP's theoretical framework is followed by an outline of the structure and content of the program and a review of the ATP outcomes. Then the generic elements of the ATP model are…
ERIC Educational Resources Information Center
World Health Organization, Geneva (Switzerland).
The manual contains three classifications (impairments, disabilities, and handicaps), each relating to a different plane of experience consequent upon disease. Section 1 attempts to clarify the nature of health related experiences by addressing reponse to acute and chronic illness; the unifying framework for classification (principle events in the…
A Unifying Framework for Causal Analysis in Set-Theoretic Multimethod Research
ERIC Educational Resources Information Center
Rohlfing, Ingo; Schneider, Carsten Q.
2018-01-01
The combination of Qualitative Comparative Analysis (QCA) with process tracing, which we call set-theoretic multimethod research (MMR), is steadily becoming more popular in empirical research. Despite the fact that both methods have an elected affinity based on set theory, it is not obvious how a within-case method operating in a single case and a…
ERIC Educational Resources Information Center
Salinas, Esther Charlotte
2013-01-01
Using the Gap Analysis problem-solving framework (Clark & Estes, 2008), this project examined collaboration around student achievement at the school site leadership level in the Pasadena Unified School District (PUSD). This project is one of three concurrent studies focused on collaboration around student achievement in the PUSD that include…
Unity of elementary particles and forces in higher dimensions.
Gogoladze, Ilia; Mimura, Yukihiro; Nandi, S
2003-10-03
The idea of unifying all the gauge and Yukawa forces as well as the gauge, Higgs, and fermionic matter particles naturally leads us to a simple gauge symmetry in higher dimensions with supersymmetry. We present a model in which, for the first time, such a unification is achieved in the framework of quantum field theory.
ERIC Educational Resources Information Center
Llamas, Sonia Rodarte
2013-01-01
Using the Gap Analysis problem-solving framework (Clark & Estes, 2008), this study examined collaboration around student achievement at the central office leadership level in the Pasadena Unified School District (PUSD). This study is one of three concurrent studies focused on collaboration around student achievement in the PUSD that include…
ERIC Educational Resources Information Center
Carruthers, Anthony Steven
2013-01-01
Using the Gap Analysis problem-solving framework (Clark & Estes, 2008), this project examined collaboration around student achievement in the Pasadena Unified School District (PUSD) from the teacher perspective. As part of a tri-level study, two other projects examined collaboration around student achievement in PUSD from the perspectives of…
ERIC Educational Resources Information Center
Seung, Eulsun; Bryan, Lynn A.; Haugan, Mark P.
2012-01-01
In this study, we investigated the pedagogical content knowledge (PCK) that physics graduate teaching assistants (TAs) developed in the context of teaching a new introductory physics curriculum, "Matter and Interactions" ("M&I"). "M&I" is an innovative introductory physics course that emphasizes a unified framework for understanding the world and…
High Maneuverability Airframe: Investigation of Fin and Canard Sizing for Optimum Maneuverability
2014-09-01
overset grids (unified- grid); 5) total variation diminishing discretization based on a new multidimensional interpolation framework; 6) Riemann solvers to...Aerodynamics .........................................................................................3 3.1.1 Solver ...describes the methodology used for the simulations. 3.1.1 Solver The double-precision solver of a commercially available code, CFD ++ v12.1.1, 9
A Unified Framework for Bounded and Unbounded Numerical Estimation
ERIC Educational Resources Information Center
Kim, Dan; Opfer, John E.
2017-01-01
Representations of numerical value have been assessed by using bounded (e.g., 0-1,000) and unbounded (e.g., 0-?) number-line tasks, with considerable debate regarding whether 1 or both tasks elicit unique cognitive strategies (e.g., addition or subtraction) and require unique cognitive models. To test this, we examined how well a mixed log-linear…
In Search of Optimal Cognitive Diagnostic Model(s) for ESL Grammar Test Data
ERIC Educational Resources Information Center
Yi, Yeon-Sook
2017-01-01
This study compares five cognitive diagnostic models in search of optimal one(s) for English as a Second Language grammar test data. Using a unified modeling framework that can represent specific models with proper constraints, the article first fit the full model (the log-linear cognitive diagnostic model, LCDM) and investigated which model…
Visual attention spreads broadly but selects information locally.
Shioiri, Satoshi; Honjyo, Hajime; Kashiwase, Yoshiyuki; Matsumiya, Kazumichi; Kuriki, Ichiro
2016-10-19
Visual attention spreads over a range around the focus as the spotlight metaphor describes. Spatial spread of attentional enhancement and local selection/inhibition are crucial factors determining the profile of the spatial attention. Enhancement and ignorance/suppression are opposite effects of attention, and appeared to be mutually exclusive. Yet, no unified view of the factors has been provided despite their necessity for understanding the functions of spatial attention. This report provides electroencephalographic and behavioral evidence for the attentional spread at an early stage and selection/inhibition at a later stage of visual processing. Steady state visual evoked potential showed broad spatial tuning whereas the P3 component of the event related potential showed local selection or inhibition of the adjacent areas. Based on these results, we propose a two-stage model of spatial attention with broad spread at an early stage and local selection at a later stage.
What can fish brains tell us about visual perception?
Rosa Salva, Orsola; Sovrano, Valeria Anna; Vallortigara, Giorgio
2014-01-01
Fish are a complex taxonomic group, whose diversity and distance from other vertebrates well suits the comparative investigation of brain and behavior: in fish species we observe substantial differences with respect to the telencephalic organization of other vertebrates and an astonishing variety in the development and complexity of pallial structures. We will concentrate on the contribution of research on fish behavioral biology for the understanding of the evolution of the visual system. We shall review evidence concerning perceptual effects that reflect fundamental principles of the visual system functioning, highlighting the similarities and differences between distant fish groups and with other vertebrates. We will focus on perceptual effects reflecting some of the main tasks that the visual system must attain. In particular, we will deal with subjective contours and optical illusions, invariance effects, second order motion and biological motion and, finally, perceptual binding of object properties in a unified higher level representation. PMID:25324728
Authoritarianism, cognitive rigidity, and the processing of ambiguous visual information.
Duncan, Lauren E; Peterson, Bill E
2014-01-01
Intolerance of ambiguity and cognitive rigidity are unifying aspects of authoritarianism as defined by Adorno, Frenkel-Brunswik, Levinson, and Sanford (1982/1950), who hypothesized that authoritarians view the world in absolute terms (e.g., good or evil). Past studies have documented the relationship between authoritarianism and intolerance of ambiguity and rigidity. Frenkel-Brunswik (1949) hypothesized that this desire for absolutism was rooted in perceptual processes. We present a study with three samples that directly tests the relationship between right wing authoritarianism (RWA) and the processing of ideologically neutral but ambiguous visual stimuli. As hypothesized, in all three samples we found that RWA was related to the slower processing of visual information that required participants to recategorize objects. In a fourth sample, RWA was unrelated to speed of processing visual information that did not require recategorization. Overall, results suggest a relationship between RWA and rigidity in categorization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lyon, A. L.; Kowalkowski, J. B.; Jones, C. D.
ParaView is a high performance visualization application not widely used in High Energy Physics (HEP). It is a long standing open source project led by Kitware and involves several Department of Energy (DOE) and Department of Defense (DOD) laboratories. Futhermore, it has been adopted by many DOE supercomputing centers and other sites. ParaView is unique in speed and efficiency by using state-of-the-art techniques developed by the academic visualization community that are often not found in applications written by the HEP community. In-situ visualization of events, where event details are visualized during processing/analysis, is a common task for experiment software frameworks.more » Kitware supplies Catalyst, a library that enables scientific software to serve visualization objects to client ParaView viewers yielding a real-time event display. Connecting ParaView to the Fermilab art framework will be described and the capabilities it brings discussed.« less
Aggarwal, Vinod
2002-10-01
This paper concerns itself with the beneficial effects of the Unified Modeling Language (UML), a nonproprietary object modeling standard, in specifying, visualizing, constructing, documenting, and communicating the model of a healthcare information system from the user's perspective. The author outlines the process of object-oriented analysis (OOA) using the UML and illustrates this with healthcare examples to demonstrate the practicality of application of the UML by healthcare personnel to real-world information system problems. The UML will accelerate advanced uses of object-orientation such as reuse technology, resulting in significantly higher software productivity. The UML is also applicable in the context of a component paradigm that promises to enhance the capabilities of healthcare information systems and simplify their management and maintenance.
Classifying clinical decision making: a unifying approach.
Buckingham, C D; Adams, A
2000-10-01
This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.
Towards a Grand Unified Theory of sports performance.
Glazier, Paul S
2017-12-01
Sports performance is generally considered to be governed by a range of interacting physiological, biomechanical, and psychological variables, amongst others. Despite sports performance being multi-factorial, however, the majority of performance-oriented sports science research has predominantly been monodisciplinary in nature, presumably due, at least in part, to the lack of a unifying theoretical framework required to integrate the various subdisciplines of sports science. In this target article, I propose a Grand Unified Theory (GUT) of sports performance-and, by elaboration, sports science-based around the constraints framework introduced originally by Newell (1986). A central tenet of this GUT is that, at both the intra- and inter-individual levels of analysis, patterns of coordination and control, which directly determine the performance outcome, emerge from the confluence of interacting organismic, environmental, and task constraints via the formation and self-organisation of coordinative structures. It is suggested that this GUT could be used to: foster interdisciplinary research collaborations; break down the silos that have developed in sports science and restore greater disciplinary balance to the field; promote a more holistic understanding of sports performance across all levels of analysis; increase explanatory power of applied research work; provide stronger rationale for data collection and variable selection; and direct the development of integrated performance monitoring technologies. This GUT could also provide a scientifically rigorous basis for integrating the subdisciplines of sports science in applied sports science support programmes adopted by high-performance agencies and national governing bodies for various individual and team sports. Copyright © 2017 Elsevier B.V. All rights reserved.
Katzner, Steffen; Busse, Laura; Treue, Stefan
2009-01-01
Directing visual attention to spatial locations or to non-spatial stimulus features can strongly modulate responses of individual cortical sensory neurons. Effects of attention typically vary in magnitude, not only between visual cortical areas but also between individual neurons from the same area. Here, we investigate whether the size of attentional effects depends on the match between the tuning properties of the recorded neuron and the perceptual task at hand. We recorded extracellular responses from individual direction-selective neurons in the middle temporal area (MT) of rhesus monkeys trained to attend either to the color or the motion signal of a moving stimulus. We found that effects of spatial and feature-based attention in MT, which are typically observed in tasks allocating attention to motion, were very similar even when attention was directed to the color of the stimulus. We conclude that attentional modulation can occur in extrastriate cortex, even under conditions without a match between the tuning properties of the recorded neuron and the perceptual task at hand. Our data are consistent with theories of object-based attention describing a transfer of attention from relevant to irrelevant features, within the attended object and across the visual field. These results argue for a unified attentional system that modulates responses to a stimulus across cortical areas, even if a given area is specialized for processing task-irrelevant aspects of that stimulus.
RAVE: Rapid Visualization Environment
NASA Technical Reports Server (NTRS)
Klumpar, D. M.; Anderson, Kevin; Simoudis, Avangelos
1994-01-01
Visualization is used in the process of analyzing large, multidimensional data sets. However, the selection and creation of visualizations that are appropriate for the characteristics of a particular data set and the satisfaction of the analyst's goals is difficult. The process consists of three tasks that are performed iteratively: generate, test, and refine. The performance of these tasks requires the utilization of several types of domain knowledge that data analysts do not often have. Existing visualization systems and frameworks do not adequately support the performance of these tasks. In this paper we present the RApid Visualization Environment (RAVE), a knowledge-based system that interfaces with commercial visualization frameworks and assists a data analyst in quickly and easily generating, testing, and refining visualizations. RAVE was used for the visualization of in situ measurement data captured by spacecraft.
A framework for small infrared target real-time visual enhancement
NASA Astrophysics Data System (ADS)
Sun, Xiaoliang; Long, Gucan; Shang, Yang; Liu, Xiaolin
2015-03-01
This paper proposes a framework for small infrared target real-time visual enhancement. The framework is consisted of three parts: energy accumulation for small infrared target enhancement, noise suppression and weighted fusion. Dynamic programming based track-before-detection algorithm is adopted in the energy accumulation to detect the target accurately and enhance the target's intensity notably. In the noise suppression, the target region is weighted by a Gaussian mask according to the target's Gaussian shape. In order to fuse the processed target region and unprocessed background smoothly, the intensity in the target region is treated as weight in the fusion. Experiments on real small infrared target images indicate that the framework proposed in this paper can enhances the small infrared target markedly and improves the image's visual quality notably. The proposed framework outperforms tradition algorithms in enhancing the small infrared target, especially for image in which the target is hardly visible.
A graph algebra for scalable visual analytics.
Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V
2012-01-01
Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.
NASA Astrophysics Data System (ADS)
Rahman, Hameedur; Arshad, Haslina; Mahmud, Rozi; Mahayuddin, Zainal Rasyid
2017-10-01
Breast Cancer patients who require breast biopsy has increased over the past years. Augmented Reality guided core biopsy of breast has become the method of choice for researchers. However, this cancer visualization has limitations to the extent of superimposing the 3D imaging data only. In this paper, we are introducing an Augmented Reality visualization framework that enables breast cancer biopsy image guidance by using X-Ray vision technique on a mobile display. This framework consists of 4 phases where it initially acquires the image from CT/MRI and process the medical images into 3D slices, secondly it will purify these 3D grayscale slices into 3D breast tumor model using 3D modeling reconstruction technique. Further, in visualization processing this virtual 3D breast tumor model has been enhanced using X-ray vision technique to see through the skin of the phantom and the final composition of it is displayed on handheld device to optimize the accuracy of the visualization in six degree of freedom. The framework is perceived as an improved visualization experience because the Augmented Reality x-ray vision allowed direct understanding of the breast tumor beyond the visible surface and direct guidance towards accurate biopsy targets.
A generalized 3D framework for visualization of planetary data.
NASA Astrophysics Data System (ADS)
Larsen, K. W.; De Wolfe, A. W.; Putnam, B.; Lindholm, D. M.; Nguyen, D.
2016-12-01
As the volume and variety of data returned from planetary exploration missions continues to expand, new tools and technologies are needed to explore the data and answer questions about the formation and evolution of the solar system. We have developed a 3D visualization framework that enables the exploration of planetary data from multiple instruments on the MAVEN mission to Mars. This framework not only provides the opportunity for cross-instrument visualization, but is extended to include model data as well, helping to bridge the gap between theory and observation. This is made possible through the use of new web technologies, namely LATIS, a data server that can stream data and spacecraft ephemerides to a web browser, and Cesium, a Javascript library for 3D globes. The common visualization framework we have developed is flexible and modular so that it can easily be adapted for additional missions. In addition to demonstrating the combined data and modeling capabilities of the system for the MAVEN mission, we will display the first ever near real-time `QuickLook', interactive, 4D data visualization for the Magnetospheric Multiscale Mission (MMS). In this application, data from all four spacecraft can be manipulated and visualized as soon as the data is ingested into the MMS Science Data Center, less than one day after collection.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dumbser, Michael, E-mail: michael.dumbser@unitn.it; Peshkov, Ilya, E-mail: peshkov@math.nsc.ru; Romenski, Evgeniy, E-mail: evrom@math.nsc.ru
Highlights: • High order schemes for a unified first order hyperbolic formulation of continuum mechanics. • The mathematical model applies simultaneously to fluid mechanics and solid mechanics. • Viscous fluids are treated in the frame of hyper-elasticity as generalized visco-plastic solids. • Formal asymptotic analysis reveals the connection with the Navier–Stokes equations. • The distortion tensor A in the model appears to be well-suited for flow visualization. - Abstract: This paper is concerned with the numerical solution of the unified first order hyperbolic formulation of continuum mechanics recently proposed by Peshkov and Romenski [110], further denoted as HPR model. Inmore » that framework, the viscous stresses are computed from the so-called distortion tensor A, which is one of the primary state variables in the proposed first order system. A very important key feature of the HPR model is its ability to describe at the same time the behavior of inviscid and viscous compressible Newtonian and non-Newtonian fluids with heat conduction, as well as the behavior of elastic and visco-plastic solids. Actually, the model treats viscous and inviscid fluids as generalized visco-plastic solids. This is achieved via a stiff source term that accounts for strain relaxation in the evolution equations of A. Also heat conduction is included via a first order hyperbolic system for the thermal impulse, from which the heat flux is computed. The governing PDE system is hyperbolic and fully consistent with the first and the second principle of thermodynamics. It is also fundamentally different from first order Maxwell–Cattaneo-type relaxation models based on extended irreversible thermodynamics. The HPR model represents therefore a novel and unified description of continuum mechanics, which applies at the same time to fluid mechanics and solid mechanics. In this paper, the direct connection between the HPR model and the classical hyperbolic–parabolic Navier–Stokes–Fourier theory is established for the first time via a formal asymptotic analysis in the stiff relaxation limit. From a numerical point of view, the governing partial differential equations are very challenging, since they form a large nonlinear hyperbolic PDE system that includes stiff source terms and non-conservative products. We apply the successful family of one-step ADER–WENO finite volume (FV) and ADER discontinuous Galerkin (DG) finite element schemes to the HPR model in the stiff relaxation limit, and compare the numerical results with exact or numerical reference solutions obtained for the Euler and Navier–Stokes equations. Numerical convergence results are also provided. To show the universality of the HPR model, the paper is rounded-off with an application to wave propagation in elastic solids, for which one only needs to switch off the strain relaxation source term in the governing PDE system. We provide various examples showing that for the purpose of flow visualization, the distortion tensor A seems to be particularly useful.« less
Salience and Attention in Surprisal-Based Accounts of Language Processing.
Zarcone, Alessandra; van Schijndel, Marten; Vogels, Jorrig; Demberg, Vera
2016-01-01
The notion of salience has been singled out as the explanatory factor for a diverse range of linguistic phenomena. In particular, perceptual salience (e.g., visual salience of objects in the world, acoustic prominence of linguistic sounds) and semantic-pragmatic salience (e.g., prominence of recently mentioned or topical referents) have been shown to influence language comprehension and production. A different line of research has sought to account for behavioral correlates of cognitive load during comprehension as well as for certain patterns in language usage using information-theoretic notions, such as surprisal. Surprisal and salience both affect language processing at different levels, but the relationship between the two has not been adequately elucidated, and the question of whether salience can be reduced to surprisal / predictability is still open. Our review identifies two main challenges in addressing this question: terminological inconsistency and lack of integration between high and low levels of representations in salience-based accounts and surprisal-based accounts. We capitalize upon work in visual cognition in order to orient ourselves in surveying the different facets of the notion of salience in linguistics and their relation with models of surprisal. We find that work on salience highlights aspects of linguistic communication that models of surprisal tend to overlook, namely the role of attention and relevance to current goals, and we argue that the Predictive Coding framework provides a unified view which can account for the role played by attention and predictability at different levels of processing and which can clarify the interplay between low and high levels of processes and between predictability-driven expectation and attention-driven focus.
Jerath, Ravinder; Cearley, Shannon M; Barnes, Vernon A; Jensen, Mike
2018-01-01
A fundamental function of the visual system is detecting motion, yet visual perception is poorly understood. Current research has determined that the retina and ganglion cells elicit responses for motion detection; however, the underlying mechanism for this is incompletely understood. Previously we proposed that retinogeniculo-cortical oscillations and photoreceptors work in parallel to process vision. Here we propose that motion could also be processed within the retina, and not in the brain as current theory suggests. In this paper, we discuss: 1) internal neural space formation; 2) primary, secondary, and tertiary roles of vision; 3) gamma as the secondary role; and 4) synchronization and coherence. Movement within the external field is instantly detected by primary processing within the space formed by the retina, providing a unified view of the world from an internal point of view. Our new theory begins to answer questions about: 1) perception of space, erect images, and motion, 2) purpose of lateral inhibition, 3) speed of visual perception, and 4) how peripheral color vision occurs without a large population of cones located peripherally in the retina. We explain that strong oscillatory activity influences on brain activity and is necessary for: 1) visual processing, and 2) formation of the internal visuospatial area necessary for visual consciousness, which could allow rods to receive precise visual and visuospatial information, while retinal waves could link the lateral geniculate body with the cortex to form a neural space formed by membrane potential-based oscillations and photoreceptors. We propose that vision is tripartite, with three components that allow a person to make sense of the world, terming them "primary, secondary, and tertiary roles" of vision. Finally, we propose that Gamma waves that are higher in strength and volume allow communication among the retina, thalamus, and various areas of the cortex, and synchronization brings cortical faculties to the retina, while the thalamus is the link that couples the retina to the rest of the brain through activity by gamma oscillations. This novel theory lays groundwork for further research by providing a theoretical understanding that expands upon the functions of the retina, photoreceptors, and retinal plexus to include parallel processing needed to form the internal visual space that we perceive as the external world. Copyright © 2017 Elsevier Ltd. All rights reserved.