Spatiotemporal dynamics of similarity-based neural representations of facial identity

PubMed Central

Vida, Mark D.; Nestor, Adrian; Plaut, David C.; Behrmann, Marlene

2017-01-01

Humans’ remarkable ability to quickly and accurately discriminate among thousands of highly similar complex objects demands rapid and precise neural computations. To elucidate the process by which this is achieved, we used magnetoencephalography to measure spatiotemporal patterns of neural activity with high temporal resolution during visual discrimination among a large and carefully controlled set of faces. We also compared these neural data to lower level “image-based” and higher level “identity-based” model-based representations of our stimuli and to behavioral similarity judgments of our stimuli. Between ∼50 and 400 ms after stimulus onset, face-selective sources in right lateral occipital cortex and right fusiform gyrus and sources in a control region (left V1) yielded successful classification of facial identity. In all regions, early responses were more similar to the image-based representation than to the identity-based representation. In the face-selective regions only, responses were more similar to the identity-based representation at several time points after 200 ms. Behavioral responses were more similar to the identity-based representation than to the image-based representation, and their structure was predicted by responses in the face-selective regions. These results provide a temporally precise description of the transformation from low- to high-level representations of facial identity in human face-selective cortex and demonstrate that face-selective cortical regions represent multiple distinct types of information about face identity at different times over the first 500 ms after stimulus onset. These results have important implications for understanding the rapid emergence of fine-grained, high-level representations of object identity, a computation essential to human visual expertise. PMID:28028220

Uncertainty representation of grey numbers and grey sets.

PubMed

Yang, Yingjie; Liu, Sifeng; John, Robert

2014-09-01

In the literature, there is a presumption that a grey set and an interval-valued fuzzy set are equivalent. This presumption ignores the existence of discrete components in a grey number. In this paper, new measurements of uncertainties of grey numbers and grey sets, consisting of both absolute and relative uncertainties, are defined to give a comprehensive representation of uncertainties in a grey number and a grey set. Some simple examples are provided to illustrate that the proposed uncertainty measurement can give an effective representation of both absolute and relative uncertainties in a grey number and a grey set. The relationships between grey sets and interval-valued fuzzy sets are also analyzed from the point of view of the proposed uncertainty representation. The analysis demonstrates that grey sets and interval-valued fuzzy sets provide different but overlapping models for uncertainty representation in sets.

Contingent attentional capture occurs by activated target congruence.

PubMed

Ariga, Atsunori; Yokosawa, Kazuhiko

2008-05-01

Contingent attentional capture occurs when a stimulus property captures an observer's attention, usually related to the observer's top-down attentional set for target-defining properties. In this study, we examined whether contingent attentional capture occurs for a distractor that does not share the target-defining property at a physical level, but does share that property at an abstract level of representation. In a rapid serial visual presentation stream, we defined the target by color (e.g., a green-colored Japanese kanji character). Before the target onset, we presented a distractor that referred to the target-defining color (e.g., a white-colored character meaning "green"). We observed contingent attentional capture by the distractor, which was reflected by a deficit in identifying the subsequent target. This result suggests that because of the attentional set, stimuli were scanned on the basis of the target-defining property at an abstract semantic level of representation.

Detection of CMOS bridging faults using minimal stuck-at fault test sets

NASA Technical Reports Server (NTRS)

Ijaz, Nabeel; Frenzel, James F.

1993-01-01

The performance of minimal stuck-at fault test sets at detecting bridging faults are evaluated. New functional models of circuit primitives are presented which allow accurate representation of bridging faults under switch-level simulation. The effectiveness of the patterns is evaluated using both voltage and current testing.

Reduced set averaging of face identity in children and adolescents with autism.

PubMed

Rhodes, Gillian; Neumann, Markus F; Ewing, Louise; Palermo, Romina

2015-01-01

Individuals with autism have difficulty abstracting and updating average representations from their diet of faces. These averages function as perceptual norms for coding faces, and poorly calibrated norms may contribute to face recognition difficulties in autism. Another kind of average, known as an ensemble representation, can be abstracted from briefly glimpsed sets of faces. Here we show for the first time that children and adolescents with autism also have difficulty abstracting ensemble representations from sets of faces. On each trial, participants saw a study set of four identities and then indicated whether a test face was present. The test face could be a set average or a set identity, from either the study set or another set. Recognition of set averages was reduced in participants with autism, relative to age- and ability-matched typically developing participants. This difference, which actually represents more accurate responding, indicates weaker set averaging and thus weaker ensemble representations of face identity in autism. Our finding adds to the growing evidence for atypical abstraction of average face representations from experience in autism. Weak ensemble representations may have negative consequences for face processing in autism, given the importance of ensemble representations in dealing with processing capacity limitations.

Speech perception at the interface of neurobiology and linguistics.

PubMed

Poeppel, David; Idsardi, William J; van Wassenhove, Virginie

2008-03-12

Speech perception consists of a set of computations that take continuously varying acoustic waveforms as input and generate discrete representations that make contact with the lexical representations stored in long-term memory as output. Because the perceptual objects that are recognized by the speech perception enter into subsequent linguistic computation, the format that is used for lexical representation and processing fundamentally constrains the speech perceptual processes. Consequently, theories of speech perception must, at some level, be tightly linked to theories of lexical representation. Minimally, speech perception must yield representations that smoothly and rapidly interface with stored lexical items. Adopting the perspective of Marr, we argue and provide neurobiological and psychophysical evidence for the following research programme. First, at the implementational level, speech perception is a multi-time resolution process, with perceptual analyses occurring concurrently on at least two time scales (approx. 20-80 ms, approx. 150-300 ms), commensurate with (sub)segmental and syllabic analyses, respectively. Second, at the algorithmic level, we suggest that perception proceeds on the basis of internal forward models, or uses an 'analysis-by-synthesis' approach. Third, at the computational level (in the sense of Marr), the theory of lexical representation that we adopt is principally informed by phonological research and assumes that words are represented in the mental lexicon in terms of sequences of discrete segments composed of distinctive features. One important goal of the research programme is to develop linking hypotheses between putative neurobiological primitives (e.g. temporal primitives) and those primitives derived from linguistic inquiry, to arrive ultimately at a biologically sensible and theoretically satisfying model of representation and computation in speech.

Understanding Deep Representations Learned in Modeling Users Likes.

PubMed

Guntuku, Sharath Chandra; Zhou, Joey Tianyi; Roy, Sujoy; Lin, Weisi; Tsang, Ivor W

2016-08-01

Automatically understanding and discriminating different users' liking for an image is a challenging problem. This is because the relationship between image features (even semantic ones extracted by existing tools, viz., faces, objects, and so on) and users' likes is non-linear, influenced by several subtle factors. This paper presents a deep bi-modal knowledge representation of images based on their visual content and associated tags (text). A mapping step between the different levels of visual and textual representations allows for the transfer of semantic knowledge between the two modalities. Feature selection is applied before learning deep representation to identify the important features for a user to like an image. The proposed representation is shown to be effective in discriminating users based on images they like and also in recommending images that a given user likes, outperforming the state-of-the-art feature representations by  ∼ 15 %-20%. Beyond this test-set performance, an attempt is made to qualitatively understand the representations learned by the deep architecture used to model user likes.

Individual- and School-Level Predictors of Student Office Disciplinary Referrals

ERIC Educational Resources Information Center

Martinez, Andrew; McMahon, Susan D.; Treger, Stan

2016-01-01

Research has widely documented the over-representation of office disciplinary referrals (ODRs) among specific student groups (e.g., African American, boys). Despite extant research documenting individual-level predictors of ODRs, few studies have accounted for the nested structure of the settings in which these events occur. Guided by critical…

Dynamic Trial-by-Trial Recoding of Task-Set Representations in the Frontoparietal Cortex Mediates Behavioral Flexibility

PubMed Central

Qiao, Lei; Zhang, Lijie

2017-01-01

Cognitive flexibility forms the core of the extraordinary ability of humans to adapt, but the precise neural mechanisms underlying our ability to nimbly shift between task sets remain poorly understood. Recent functional magnetic resonance imaging (fMRI) studies employing multivoxel pattern analysis (MVPA) have shown that a currently relevant task set can be decoded from activity patterns in the frontoparietal cortex, but whether these regions support the dynamic transformation of task sets from trial to trial is not clear. Here, we combined a cued task-switching protocol with human (both sexes) fMRI, and harnessed representational similarity analysis (RSA) to facilitate a novel assessment of trial-by-trial changes in neural task-set representations. We first used MVPA to define task-sensitive frontoparietal and visual regions and found that neural task-set representations on switch trials are less stably encoded than on repeat trials. We then exploited RSA to show that the neural representational pattern dissimilarity across consecutive trials is greater for switch trials than for repeat trials, and that the degree of this pattern dissimilarity predicts behavior. Moreover, the overall neural pattern of representational dissimilarities followed from the assumption that repeating sets, compared with switching sets, results in stronger neural task representations. Finally, when moving from cue to target phase within a trial, pattern dissimilarities tracked the transformation from previous-trial task representations to the currently relevant set. These results provide neural evidence for the longstanding assumptions of an effortful task-set reconfiguration process hampered by task-set inertia, and they demonstrate that frontoparietal and stimulus processing regions support “dynamic adaptive coding,” flexibly representing changing task sets in a trial-by-trial fashion. SIGNIFICANCE STATEMENT Humans can fluently switch between different tasks, reflecting an ability to dynamically configure “task sets,” rule representations that link stimuli to appropriate responses. Recent studies show that neural signals in frontal and parietal brain regions can tell us which of two tasks a person is currently performing. However, it is not known whether these regions are also involved in dynamically reconfiguring task-set representations when switching between tasks. Here we measured human brain activity during task switching and tracked the similarity of neural task-set representations from trial to trial. We show that frontal and parietal brain regions flexibly recode changing task sets in a trial-by-trial fashion, and that task-set similarity over consecutive trials predicts behavior. PMID:28972126

High-resolution method for evolving complex interface networks

NASA Astrophysics Data System (ADS)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

Object-based benefits without object-based representations.

PubMed

Fougnie, Daryl; Cormiea, Sarah M; Alvarez, George A

2013-08-01

Influential theories of visual working memory have proposed that the basic units of memory are integrated object representations. Key support for this proposal is provided by the same object benefit: It is easier to remember multiple features of a single object than the same set of features distributed across multiple objects. Here, we replicate the object benefit but demonstrate that features are not stored as single, integrated representations. Specifically, participants could remember 10 features better when arranged in 5 objects compared to 10 objects, yet memory for one object feature was largely independent of memory for the other object feature. These results rule out the possibility that integrated representations drive the object benefit and require a revision of the concept of object-based memory representations. We propose that working memory is object-based in regard to the factors that enhance performance but feature based in regard to the level of representational failure. PsycINFO Database Record (c) 2013 APA, all rights reserved.

discovery toolset for Emulytics v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, David; Crussell, Jonathan

The discovery toolset for Emulytics enables the construction of high-fidelity emulation models of systems. The toolset consists of a set of tools and techniques to automatically go from network discovery of operational systems to emulating those complex systems. Our toolset combines data from host discovery and network mapping tools into an intermediate representation that can then be further refined. Once the intermediate representation reaches the desired state, our toolset supports emitting the Emulytics models with varying levels of specificity based on experiment needs.

Mid-level image representations for real-time heart view plane classification of echocardiograms.

PubMed

Penatti, Otávio A B; Werneck, Rafael de O; de Almeida, Waldir R; Stein, Bernardo V; Pazinato, Daniel V; Mendes Júnior, Pedro R; Torres, Ricardo da S; Rocha, Anderson

2015-11-01

In this paper, we explore mid-level image representations for real-time heart view plane classification of 2D echocardiogram ultrasound images. The proposed representations rely on bags of visual words, successfully used by the computer vision community in visual recognition problems. An important element of the proposed representations is the image sampling with large regions, drastically reducing the execution time of the image characterization procedure. Throughout an extensive set of experiments, we evaluate the proposed approach against different image descriptors for classifying four heart view planes. The results show that our approach is effective and efficient for the target problem, making it suitable for use in real-time setups. The proposed representations are also robust to different image transformations, e.g., downsampling, noise filtering, and different machine learning classifiers, keeping classification accuracy above 90%. Feature extraction can be performed in 30 fps or 60 fps in some cases. This paper also includes an in-depth review of the literature in the area of automatic echocardiogram view classification giving the reader a through comprehension of this field of study. Copyright © 2015 Elsevier Ltd. All rights reserved.

International Classification of Functioning, Disability and Health Core Sets for cerebral palsy, autism spectrum disorder, and attention-deficit-hyperactivity disorder.

PubMed

Schiariti, Verónica; Mahdi, Soheil; Bölte, Sven

2018-05-30

Capturing functional information is crucial in childhood disability. The International Classification of Functioning, Disability and Health (ICF) Core Sets promote assessments of functional abilities and disabilities in clinical practice regarding circumscribed diagnoses. However, the specificity of ICF Core Sets for childhood-onset disabilities has been doubted. This study aimed to identify content commonalities and differences among the ICF Core Sets for cerebral palsy (CP), and the newly developed Core Sets for autism spectrum disorder (ASD) and attention-deficit-hyperactivity disorder (ADHD). The categories within each Core Set were aggregated at the ICF component and chapter levels. Content comparison was conducted using descriptive analyses. The activities and participation component of the ICF was the most covered across all Core Sets. Main differences included representation of ICF components and coverage of ICF chapters within each component. CP included all ICF components, while ADHD and ASD predominantly focused on activities and participation. Environmental factors were highly represented in the ADHD Core Sets (40.5%) compared to the ASD (28%) and CP (27%) Core Sets. International Classification of Functioning, Disability and Health Core Sets for CP, ASD, and ADHD capture both common but also unique functional information, showing the importance of creating condition-specific, ICF-based tools to build functional profiles of individuals with childhood-onset disabilities. The International Classification of Functioning, Disability and Health (ICF) Core Sets for cerebral palsy (CP), autism spectrum disorder (ASD), and attention-deficit-hyperactivity disorder (ADHD) include unique functional information. The ICF-based tools for CP, ASD, and ADHD differ in terms of representation and coverage of ICF components and ICF chapters. Representation of environmental factors uniquely influences functioning and disability across ICF Core Sets for CP, ASD and ADHD. © 2018 Mac Keith Press.

Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

Deep learning

NASA Astrophysics Data System (ADS)

Lecun, Yann; Bengio, Yoshua; Hinton, Geoffrey

2015-05-01

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

Deep learning.

PubMed

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey

2015-05-28

Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. These methods have dramatically improved the state-of-the-art in speech recognition, visual object recognition, object detection and many other domains such as drug discovery and genomics. Deep learning discovers intricate structure in large data sets by using the backpropagation algorithm to indicate how a machine should change its internal parameters that are used to compute the representation in each layer from the representation in the previous layer. Deep convolutional nets have brought about breakthroughs in processing images, video, speech and audio, whereas recurrent nets have shone light on sequential data such as text and speech.

Women and Minorities in Psychology.

ERIC Educational Resources Information Center

Russo, Nancy Felipe; And Others

1981-01-01

Presents data on women and minorities in the field of psychology in terms of representation, subfields, degree level, experience, licensure/certification, employment status, employment setting, income, and membership in graduate psychology faculty. Discusses continuing underrepresentation of minorities and pervasive subfield segregation and pay…

A potential energy surface for the process H2 + H2O yielding H + H + H2O - Ab initio calculations and analytical representation

NASA Technical Reports Server (NTRS)

Schwenke, David W.; Walch, Stephen P.; Taylor, Peter R.

1991-01-01

Extensive ab initio calculations on the ground state potential energy surface of H2 + H2O were performed using a large contracted Gaussian basis set and a high level of correlation treatment. An analytical representation of the potential energy surface was then obtained which reproduces the calculated energies with an overall root-mean-square error of only 0.64 mEh. The analytic representation explicitly includes all nine internal degrees of freedom and is also well behaved as the H2 dissociates; it thus can be used to study collision-induced dissociation or recombination of H2. The strategy used to minimize the number of energy calculations is discussed, as well as other advantages of the present method for determining the analytical representation.

Representations and uses of light distribution functions

NASA Astrophysics Data System (ADS)

Lalonde, Paul Albert

1998-11-01

At their lowest level, all rendering algorithms depend on models of local illumination to define the interplay of light with the surfaces being rendered. These models depend both on the representations of light scattering at a surface due to reflection and to an equal extent on the representation of light sources and light fields. Both emission and reflection have in common that they describe how light leaves a surface as a function of direction. Reflection also depends on an incident light direction. Emission can depend on the position on the light source We call the functions representing emission and reflection light distribution functions (LDF's). There are some difficulties to using measured light distribution functions. The data sets are very large-the size of the data grows with the fourth power of the sampling resolution. For example, a bidirectional reflectance distribution function (BRDF) sampled at five degrees angular resolution, which is arguably insufficient to capture highlights and other high frequency effects in the reflection, can easily require one and a half million samples. Once acquired this data requires some form of interpolation to use them. Any compression method used must be efficient, both in space and in the time required to evaluate the function at a point or over a range of points. This dissertation examines a wavelet representation of light distribution functions that addresses these issues. A data structure is presented that allows efficient reconstruction of LDFs for a given set of parameters, making the wavelet representation feasible for rendering tasks. Texture mapping methods that take advantage of our LDF representations are examined, as well as techniques for filtering LDFs, and methods for using wavelet compressed bidirection reflectance distribution functions (BRDFs) and light sources with Monte Carlo path tracing algorithms. The wavelet representation effectively compresses BRDF and emission data while inducing only a small error in the reconstructed signal. The representation can be used to evaluate efficiently some integrals that appear in shading computation which allows fast, accurate computation of local shading. The representation can be used to represent light fields and is used to reconstruct views of environments interactively from a precomputed set of views. The representation of the BRDF also allows the efficient generation of reflected directions for Monte Carlo array tracing applications. The method can be integrated into many different global illumination algorithms, including ray tracers and wavelet radiosity systems.

Reinstatement of Individual Past Events Revealed by the Similarity of Distributed Activation Patterns during Encoding and Retrieval

PubMed Central

Wing, Erik A.; Ritchey, Maureen; Cabeza, Roberto

2015-01-01

Neurobiological memory models assume memory traces are stored in neocortex, with pointers in the hippocampus, and are then reactivated during retrieval, yielding the experience of remembering. Whereas most prior neuroimaging studies on reactivation have focused on the reactivation of sets or categories of items, the current study sought to identify cortical patterns pertaining to memory for individual scenes. During encoding, participants viewed pictures of scenes paired with matching labels (e.g., “barn,” “tunnel”), and, during retrieval, they recalled the scenes in response to the labels and rated the quality of their visual memories. Using representational similarity analyses, we interrogated the similarity between activation patterns during encoding and retrieval both at the item level (individual scenes) and the set level (all scenes). The study yielded four main findings. First, in occipitotemporal cortex, memory success increased with encoding-retrieval similarity (ERS) at the item level but not at the set level, indicating the reactivation of individual scenes. Second, in ventrolateral pFC, memory increased with ERS for both item and set levels, indicating the recapitulation of memory processes that benefit encoding and retrieval of all scenes. Third, in retrosplenial/posterior cingulate cortex, ERS was sensitive to individual scene information irrespective of memory success, suggesting automatic activation of scene contexts. Finally, consistent with neurobiological models, hippocampal activity during encoding predicted the subsequent reactivation of individual items. These findings show the promise of studying memory with greater specificity by isolating individual mnemonic representations and determining their relationship to factors like the detail with which past events are remembered. PMID:25313659

Dynamic Mesh Adaptation for Front Evolution Using Discontinuous Galerkin Based Weighted Condition Number Mesh Relaxation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

2016-06-21

A new mesh smoothing method designed to cluster mesh cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function being computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered elds, such as amore » volume fraction or index function, is provided. Results show that the low-order level set works equally well for the weight function as the actual level set. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Dynamic cases for moving interfaces are presented to demonstrate the method's potential usefulness to arbitrary Lagrangian Eulerian (ALE) methods.« less

A unified data representation theory for network visualization, ordering and coarse-graining

PubMed Central

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

Deep Convolutional Neural Networks Outperform Feature-Based But Not Categorical Models in Explaining Object Similarity Judgments

PubMed Central

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Storrs, Katherine R.; Mur, Marieke

2017-01-01

Recent advances in Deep convolutional Neural Networks (DNNs) have enabled unprecedentedly accurate computational models of brain representations, and present an exciting opportunity to model diverse cognitive functions. State-of-the-art DNNs achieve human-level performance on object categorisation, but it is unclear how well they capture human behavior on complex cognitive tasks. Recent reports suggest that DNNs can explain significant variance in one such task, judging object similarity. Here, we extend these findings by replicating them for a rich set of object images, comparing performance across layers within two DNNs of different depths, and examining how the DNNs’ performance compares to that of non-computational “conceptual” models. Human observers performed similarity judgments for a set of 92 images of real-world objects. Representations of the same images were obtained in each of the layers of two DNNs of different depths (8-layer AlexNet and 16-layer VGG-16). To create conceptual models, other human observers generated visual-feature labels (e.g., “eye”) and category labels (e.g., “animal”) for the same image set. Feature labels were divided into parts, colors, textures and contours, while category labels were divided into subordinate, basic, and superordinate categories. We fitted models derived from the features, categories, and from each layer of each DNN to the similarity judgments, using representational similarity analysis to evaluate model performance. In both DNNs, similarity within the last layer explains most of the explainable variance in human similarity judgments. The last layer outperforms almost all feature-based models. Late and mid-level layers outperform some but not all feature-based models. Importantly, categorical models predict similarity judgments significantly better than any DNN layer. Our results provide further evidence for commonalities between DNNs and brain representations. Models derived from visual features other than object parts perform relatively poorly, perhaps because DNNs more comprehensively capture the colors, textures and contours which matter to human object perception. However, categorical models outperform DNNs, suggesting that further work may be needed to bring high-level semantic representations in DNNs closer to those extracted by humans. Modern DNNs explain similarity judgments remarkably well considering they were not trained on this task, and are promising models for many aspects of human cognition. PMID:29062291

MetaJC++: A flexible and automatic program transformation technique using meta framework

NASA Astrophysics Data System (ADS)

Beevi, Nadera S.; Reghu, M.; Chitraprasad, D.; Vinodchandra, S. S.

2014-09-01

Compiler is a tool to translate abstract code containing natural language terms to machine code. Meta compilers are available to compile more than one languages. We have developed a meta framework intends to combine two dissimilar programming languages, namely C++ and Java to provide a flexible object oriented programming platform for the user. Suitable constructs from both the languages have been combined, thereby forming a new and stronger Meta-Language. The framework is developed using the compiler writing tools, Flex and Yacc to design the front end of the compiler. The lexer and parser have been developed to accommodate the complete keyword set and syntax set of both the languages. Two intermediate representations have been used in between the translation of the source program to machine code. Abstract Syntax Tree has been used as a high level intermediate representation that preserves the hierarchical properties of the source program. A new machine-independent stack-based byte-code has also been devised to act as a low level intermediate representation. The byte-code is essentially organised into an output class file that can be used to produce an interpreted output. The results especially in the spheres of providing C++ concepts in Java have given an insight regarding the potential strong features of the resultant meta-language.

Forced to remember: when memory is biased by salient information.

PubMed

Santangelo, Valerio

2015-04-15

The last decades have seen a rapid growing in the attempt to understand the key factors involved in the internal memory representation of the external world. Visual salience have been found to provide a major contribution in predicting the probability for an item/object embedded in a complex setting (i.e., a natural scene) to be encoded and then remembered later on. Here I review the existing literature highlighting the impact of perceptual- (based on low-level sensory features) and semantics-related salience (based on high-level knowledge) on short-term memory representation, along with the neural mechanisms underpinning the interplay between these factors. The available evidence reveal that both perceptual- and semantics-related factors affect attention selection mechanisms during the encoding of natural scenes. Biasing internal memory representation, both perceptual and semantics factors increase the probability to remember high- to the detriment of low-saliency items. The available evidence also highlight an interplay between these factors, with a reduced impact of perceptual-related salience in biasing memory representation as a function of the increasing availability of semantics-related salient information. The neural mechanisms underpinning this interplay involve the activation of different portions of the frontoparietal attention control network. Ventral regions support the assignment of selection/encoding priorities based on high-level semantics, while the involvement of dorsal regions reflects priorities assignment based on low-level sensory features. Copyright © 2015 Elsevier B.V. All rights reserved.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

A scale-invariant internal representation of time.

PubMed

Shankar, Karthik H; Howard, Marc W

2012-01-01

We propose a principled way to construct an internal representation of the temporal stimulus history leading up to the present moment. A set of leaky integrators performs a Laplace transform on the stimulus function, and a linear operator approximates the inversion of the Laplace transform. The result is a representation of stimulus history that retains information about the temporal sequence of stimuli. This procedure naturally represents more recent stimuli more accurately than less recent stimuli; the decrement in accuracy is precisely scale invariant. This procedure also yields time cells that fire at specific latencies following the stimulus with a scale-invariant temporal spread. Combined with a simple associative memory, this representation gives rise to a moment-to-moment prediction that is also scale invariant in time. We propose that this scale-invariant representation of temporal stimulus history could serve as an underlying representation accessible to higher-level behavioral and cognitive mechanisms. In order to illustrate the potential utility of this scale-invariant representation in a variety of fields, we sketch applications using minimal performance functions to problems in classical conditioning, interval timing, scale-invariant learning in autoshaping, and the persistence of the recency effect in episodic memory across timescales.

Learning Semantic Tags from Big Data for Clinical Text Representation.

PubMed

Li, Yanpeng; Liu, Hongfang

2015-01-01

In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

Cognitive and artificial representations in handwriting recognition

NASA Astrophysics Data System (ADS)

Lenaghan, Andrew P.; Malyan, Ron

1996-03-01

Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

Effect of different implementations of the same ice history in GIA modeling

NASA Astrophysics Data System (ADS)

Barletta, V. R.; Bordoni, A.

2013-11-01

This study shows the effect of changing the way ice histories are implemented in Glacial Isostatic Adjustment (GIA) codes to solve the sea level equation. The ice history models are being constantly improved and are provided in different formats. The overall algorithmic design of the sea-level equation solver often forces to implement the ice model in a representation that differs from the one originally provided. We show that using different representations of the same ice model gives important differences and artificial contributions to the sea level estimates, both at global and at regional scale. This study is not a speculative exercise. The ICE-5G model adopted in this work is widely used in present day sea-level analysis, but discrepancies between the results obtained by different groups for the same ice models still exist, and it was the effort to set a common reference for the sea-level community that inspired this work. Understanding this issue is important to be able to reduce the artefacts introduced by a non-suitable ice model representation. This is especially important when developing new GIA models, since neglecting this problem can easily lead to wrong alignment of the ice and sea-level histories, particularly close to the deglaciation areas, like Antarctica.

[Primary health care--the "apple of the eye" of SUS: about social representations of the protagonists of the Unified Health System].

PubMed

Gomes, Karine de Oliveira; Cotta, Rosângela Minardi Mitre; Araújo, Raquel Maria Amaral; Cherchiglia, Mariângela Leal; Martins, Tatiana de Castro Pereira

2011-01-01

The Primary Health Care (PHC) is the first contact level with the health system. In Brazil, the Family Health Program (PSF) is the main implementation and organization strategy of the PHC. The objective of this study is to evaluate the actions and services of health offered by the PSF, starting from the social representations of the interviewee on the exclusive dimensions of PHC - attention to the first contact, longitudinality, integrality and coordination. It is a quali-quantitative research, accomplished in Cajuri, Minas Gerais State. Municipal managers, PSF professionals and pregnant women assisted by PSF were interviewed. Regarding social representations on SUS, it was observed an inadequate level of apprehension and knowledge of their principles and guidelines. As for PSF, several positive connotations were expressed and the set of perceptions of the protagonists identified it as a restructuring strategy of PHC in the municipality. In spite of this, strong influences of the biomedical model and the challenge of the integration with the other levels of attention were noticed, indicating the need of investments in the professional's training and in the organization of the other levels of attention to health.

Processing statistics: an examination of focused and distributed attention using event related potentials.

PubMed

Baijal, Shruti; Nakatani, Chie; van Leeuwen, Cees; Srinivasan, Narayanan

2013-06-07

Human observers show remarkable efficiency in statistical estimation; they are able, for instance, to estimate the mean size of visual objects, even if their number exceeds the capacity limits of focused attention. This ability has been understood as the result of a distinct mode of attention, i.e. distributed attention. Compared to the focused attention mode, working memory representations under distributed attention are proposed to be more compressed, leading to reduced working memory loads. An alternate proposal is that distributed attention uses less structured, feature-level representations. These would fill up working memory (WM) more, even when target set size is low. Using event-related potentials, we compared WM loading in a typical distributed attention task (mean size estimation) to that in a corresponding focused attention task (object recognition), using a measure called contralateral delay activity (CDA). Participants performed both tasks on 2, 4, or 8 different-sized target disks. In the recognition task, CDA amplitude increased with set size; notably, however, in the mean estimation task the CDA amplitude was high regardless of set size. In particular for set-size 2, the amplitude was higher in the mean estimation task than in the recognition task. The result showed that the task involves full WM loading even with a low target set size. This suggests that in the distributed attention mode, representations are not compressed, but rather less structured than under focused attention conditions. Copyright © 2012 Elsevier Ltd. All rights reserved.

A compression algorithm for the combination of PDF sets.

PubMed

Carrazza, Stefano; Latorre, José I; Rojo, Juan; Watt, Graeme

The current PDF4LHC recommendation to estimate uncertainties due to parton distribution functions (PDFs) in theoretical predictions for LHC processes involves the combination of separate predictions computed using PDF sets from different groups, each of which comprises a relatively large number of either Hessian eigenvectors or Monte Carlo (MC) replicas. While many fixed-order and parton shower programs allow the evaluation of PDF uncertainties for a single PDF set at no additional CPU cost, this feature is not universal, and, moreover, the a posteriori combination of the predictions using at least three different PDF sets is still required. In this work, we present a strategy for the statistical combination of individual PDF sets, based on the MC representation of Hessian sets, followed by a compression algorithm for the reduction of the number of MC replicas. We illustrate our strategy with the combination and compression of the recent NNPDF3.0, CT14 and MMHT14 NNLO PDF sets. The resulting compressed Monte Carlo PDF sets are validated at the level of parton luminosities and LHC inclusive cross sections and differential distributions. We determine that around 100 replicas provide an adequate representation of the probability distribution for the original combined PDF set, suitable for general applications to LHC phenomenology.

Mapping Hydrophobicity on the Protein Molecular Surface at Atom-Level Resolution

PubMed Central

Nicolau Jr., Dan V.; Paszek, Ewa; Fulga, Florin; Nicolau, Dan V.

2014-01-01

A precise representation of the spatial distribution of hydrophobicity, hydrophilicity and charges on the molecular surface of proteins is critical for the understanding of the interaction with small molecules and larger systems. The representation of hydrophobicity is rarely done at atom-level, as this property is generally assigned to residues. A new methodology for the derivation of atomic hydrophobicity from any amino acid-based hydrophobicity scale was used to derive 8 sets of atomic hydrophobicities, one of which was used to generate the molecular surfaces for 35 proteins with convex structures, 5 of which, i.e., lysozyme, ribonuclease, hemoglobin, albumin and IgG, have been analyzed in more detail. Sets of the molecular surfaces of the model proteins have been constructed using spherical probes with increasingly large radii, from 1.4 to 20 Å, followed by the quantification of (i) the surface hydrophobicity; (ii) their respective molecular surface areas, i.e., total, hydrophilic and hydrophobic area; and (iii) their relative densities, i.e., divided by the total molecular area; or specific densities, i.e., divided by property-specific area. Compared with the amino acid-based formalism, the atom-level description reveals molecular surfaces which (i) present an approximately two times more hydrophilic areas; with (ii) less extended, but between 2 to 5 times more intense hydrophilic patches; and (iii) 3 to 20 times more extended hydrophobic areas. The hydrophobic areas are also approximately 2 times more hydrophobicity-intense. This, more pronounced “leopard skin”-like, design of the protein molecular surface has been confirmed by comparing the results for a restricted set of homologous proteins, i.e., hemoglobins diverging by only one residue (Trp37). These results suggest that the representation of hydrophobicity on the protein molecular surfaces at atom-level resolution, coupled with the probing of the molecular surface at different geometric resolutions, can capture processes that are otherwise obscured to the amino acid-based formalism. PMID:25462574

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Completing the Physical Representation of Quantum Algorithms Provides a Quantitative Explanation of Their Computational Speedup

NASA Astrophysics Data System (ADS)

Castagnoli, Giuseppe

2018-03-01

The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete. We complete it in three steps: (i) extending the representation to the process of setting the problem, (ii) relativizing the extended representation to the problem solver to whom the problem setting must be concealed, and (iii) symmetrizing the relativized representation for time reversal to represent the reversibility of the underlying physical process. The third steps projects the input state of the representation, where the problem solver is completely ignorant of the setting and thus the solution of the problem, on one where she knows half solution (half of the information specifying it when the solution is an unstructured bit string). Completing the physical representation shows that the number of computation steps (oracle queries) required to solve any oracle problem in an optimal quantum way should be that of a classical algorithm endowed with the advanced knowledge of half solution.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

A computational model of the human visual cortex

NASA Astrophysics Data System (ADS)

Albus, James S.

2008-04-01

The brain is first and foremost a control system that is capable of building an internal representation of the external world, and using this representation to make decisions, set goals and priorities, formulate plans, and control behavior with intent to achieve its goals. The computational model proposed here assumes that this internal representation resides in arrays of cortical columns. More specifically, it models each cortical hypercolumn together with its underlying thalamic nuclei as a Fundamental Computational Unit (FCU) consisting of a frame-like data structure (containing attributes and pointers) plus the computational processes and mechanisms required to maintain it. In sensory-processing areas of the brain, FCUs enable segmentation, grouping, and classification. Pointers stored in FCU frames link pixels and signals to objects and events in situations and episodes that are overlaid with meaning and emotional values. In behavior-generating areas of the brain, FCUs make decisions, set goals and priorities, generate plans, and control behavior. Pointers are used to define rules, grammars, procedures, plans, and behaviors. It is suggested that it may be possible to reverse engineer the human brain at the FCU level of fidelity using nextgeneration massively parallel computer hardware and software. Key Words: computational modeling, human cortex, brain modeling, reverse engineering the brain, image processing, perception, segmentation, knowledge representation

An unbiased Hessian representation for Monte Carlo PDFs.

PubMed

Carrazza, Stefano; Forte, Stefano; Kassabov, Zahari; Latorre, José Ignacio; Rojo, Juan

We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set.

Semantic enrichment of clinical models towards semantic interoperability. The heart failure summary use case.

PubMed

Martínez-Costa, Catalina; Cornet, Ronald; Karlsson, Daniel; Schulz, Stefan; Kalra, Dipak

2015-05-01

To improve semantic interoperability of electronic health records (EHRs) by ontology-based mediation across syntactically heterogeneous representations of the same or similar clinical information. Our approach is based on a semantic layer that consists of: (1) a set of ontologies supported by (2) a set of semantic patterns. The first aspect of the semantic layer helps standardize the clinical information modeling task and the second shields modelers from the complexity of ontology modeling. We applied this approach to heterogeneous representations of an excerpt of a heart failure summary. Using a set of finite top-level patterns to derive semantic patterns, we demonstrate that those patterns, or compositions thereof, can be used to represent information from clinical models. Homogeneous querying of the same or similar information, when represented according to heterogeneous clinical models, is feasible. Our approach focuses on the meaning embedded in EHRs, regardless of their structure. This complex task requires a clear ontological commitment (ie, agreement to consistently use the shared vocabulary within some context), together with formalization rules. These requirements are supported by semantic patterns. Other potential uses of this approach, such as clinical models validation, require further investigation. We show how an ontology-based representation of a clinical summary, guided by semantic patterns, allows homogeneous querying of heterogeneous information structures. Whether there are a finite number of top-level patterns is an open question. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Recognizing Chromospheric Objects via Markov Chain Monte Carlo

NASA Technical Reports Server (NTRS)

Mukhtar, Saleem; Turmon, Michael J.

1997-01-01

The solar chromosphere consists of three classes which contribute differentially to ultraviolet radiation reaching the earth. We describe a data set of solar images, means of segmenting the images into the constituent classes, and a novel high-level representation for compact objects based on a triangulated spatial membership function.

Evidence for sparse synergies in grasping actions.

PubMed

Prevete, Roberto; Donnarumma, Francesco; d'Avella, Andrea; Pezzulo, Giovanni

2018-01-12

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) - sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) - sparsity in synergy representation - i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) - a novel view combining both SC and SE - i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks.

Dynamic mesh adaptation for front evolution using discontinuous Galerkin based weighted condition number relaxation

DOE PAGES

Greene, Patrick T.; Schofield, Samuel P.; Nourgaliev, Robert

2017-01-27

A new mesh smoothing method designed to cluster cells near a dynamically evolving interface is presented. The method is based on weighted condition number mesh relaxation with the weight function computed from a level set representation of the interface. The weight function is expressed as a Taylor series based discontinuous Galerkin projection, which makes the computation of the derivatives of the weight function needed during the condition number optimization process a trivial matter. For cases when a level set is not available, a fast method for generating a low-order level set from discrete cell-centered fields, such as a volume fractionmore » or index function, is provided. Results show that the low-order level set works equally well as the actual level set for mesh smoothing. Meshes generated for a number of interface geometries are presented, including cases with multiple level sets. Lastly, dynamic cases with moving interfaces show the new method is capable of maintaining a desired resolution near the interface with an acceptable number of relaxation iterations per time step, which demonstrates the method's potential to be used as a mesh relaxer for arbitrary Lagrangian Eulerian (ALE) methods.« less

Identifying secondary-school students' difficulties when reading visual representations displayed in physics simulations

NASA Astrophysics Data System (ADS)

López, Víctor; Pintó, Roser

2017-07-01

Computer simulations are often considered effective educational tools, since their visual and communicative power enable students to better understand physical systems and phenomena. However, previous studies have found that when students read visual representations some reading difficulties can arise, especially when these are complex or dynamic representations. We have analyzed how secondary-school students read the visual representations displayed in two PhET simulations (one addressing the friction-heating at microscopic level, and the other addressing the electromagnetic induction), and different typologies of reading difficulties have been identified: when reading the compositional structure of the representation, when giving appropriate relevance and semantic meaning to each visual element, and also when dealing with multiple representations and dynamic information. All students experienced at least one of these difficulties, and very similar difficulties appeared in the two groups of students, despite the different scientific content of the simulations. In conclusion, visualisation does not imply a full comprehension of the content of scientific simulations per se, and an effective reading process requires a set of reading skills, previous knowledge, attention, and external supports. Science teachers should bear in mind these issues in order to help students read images to take benefit of their educational potential.

Video based object representation and classification using multiple covariance matrices.

PubMed

Zhang, Yurong; Liu, Quan

2017-01-01

Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.

Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives.

PubMed

Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan

2014-01-01

The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a model that relates the conceptualization of the higher-level information from visual stimuli to the development of ventral/dorsal visual streams. This model employs neural network architecture incorporating a predictive sensory module based on an RNNPB (Recurrent Neural Network with Parametric Biases) and a horizontal product model. We exemplify this model through a robot passively observing an object to learn its features and movements. During the learning process of observing sensorimotor primitives, i.e., observing a set of trajectories of arm movements and its oriented object features, the pre-symbolic representation is self-organized in the parametric units. These representational units act as bifurcation parameters, guiding the robot to recognize and predict various learned sensorimotor primitives. The pre-symbolic representation also accounts for the learning of sensorimotor primitives in a latent learning context.

Toward a self-organizing pre-symbolic neural model representing sensorimotor primitives

PubMed Central

Zhong, Junpei; Cangelosi, Angelo; Wermter, Stefan

2014-01-01

The acquisition of symbolic and linguistic representations of sensorimotor behavior is a cognitive process performed by an agent when it is executing and/or observing own and others' actions. According to Piaget's theory of cognitive development, these representations develop during the sensorimotor stage and the pre-operational stage. We propose a model that relates the conceptualization of the higher-level information from visual stimuli to the development of ventral/dorsal visual streams. This model employs neural network architecture incorporating a predictive sensory module based on an RNNPB (Recurrent Neural Network with Parametric Biases) and a horizontal product model. We exemplify this model through a robot passively observing an object to learn its features and movements. During the learning process of observing sensorimotor primitives, i.e., observing a set of trajectories of arm movements and its oriented object features, the pre-symbolic representation is self-organized in the parametric units. These representational units act as bifurcation parameters, guiding the robot to recognize and predict various learned sensorimotor primitives. The pre-symbolic representation also accounts for the learning of sensorimotor primitives in a latent learning context. PMID:24550798

The contribution of foveal and peripheral visual information to ensemble representation of face race.

PubMed

Jung, Wonmo; Bülthoff, Isabelle; Armann, Regine G M

2017-11-01

The brain can only attend to a fraction of all the information that is entering the visual system at any given moment. One way of overcoming the so-called bottleneck of selective attention (e.g., J. M. Wolfe, Võ, Evans, & Greene, 2011) is to make use of redundant visual information and extract summarized statistical information of the whole visual scene. Such ensemble representation occurs for low-level features of textures or simple objects, but it has also been reported for complex high-level properties. While the visual system has, for example, been shown to compute summary representations of facial expression, gender, or identity, it is less clear whether perceptual input from all parts of the visual field contributes equally to the ensemble percept. Here we extend the line of ensemble-representation research into the realm of race and look at the possibility that ensemble perception relies on weighting visual information differently depending on its origin from either the fovea or the visual periphery. We find that observers can judge the mean race of a set of faces, similar to judgments of mean emotion from faces and ensemble representations in low-level domains of visual processing. We also find that while peripheral faces seem to be taken into account for the ensemble percept, far more weight is given to stimuli presented foveally than peripherally. Whether this precision weighting of information stems from differences in the accuracy with which the visual system processes information across the visual field or from statistical inferences about the world needs to be determined by further research.

Evidence for a Non-Linguistic Distinction between Singular and Plural Sets in Rhesus Monkeys

ERIC Educational Resources Information Center

Barner, David; Wood, Justin; Hauser, Marc; Carey, Susan

2008-01-01

Set representations are explicitly expressed in natural language. For example, many languages distinguish between sets and subsets ("all" vs. "some"), as well as between singular and plural sets ("a cat" vs. "some cats"). Three experiments explored the hypothesis that these representations are language specific, and thus absent from the conceptual…

Ensemble representations: effects of set size and item heterogeneity on average size perception.

PubMed

Marchant, Alexander P; Simons, Daniel J; de Fockert, Jan W

2013-02-01

Observers can accurately perceive and evaluate the statistical properties of a set of objects, forming what is now known as an ensemble representation. The accuracy and speed with which people can judge the mean size of a set of objects have led to the proposal that ensemble representations of average size can be computed in parallel when attention is distributed across the display. Consistent with this idea, judgments of mean size show little or no decrement in accuracy when the number of objects in the set increases. However, the lack of a set size effect might result from the regularity of the item sizes used in previous studies. Here, we replicate these previous findings, but show that judgments of mean set size become less accurate when set size increases and the heterogeneity of the item sizes increases. This pattern can be explained by assuming that average size judgments are computed using a limited capacity sampling strategy, and it does not necessitate an ensemble representation computed in parallel across all items in a display. Copyright © 2012 Elsevier B.V. All rights reserved.

Mapping Topographic Structure in White Matter Pathways with Level Set Trees

PubMed Central

Kent, Brian P.; Rinaldo, Alessandro; Yeh, Fang-Cheng; Verstynen, Timothy

2014-01-01

Fiber tractography on diffusion imaging data offers rich potential for describing white matter pathways in the human brain, but characterizing the spatial organization in these large and complex data sets remains a challenge. We show that level set trees–which provide a concise representation of the hierarchical mode structure of probability density functions–offer a statistically-principled framework for visualizing and analyzing topography in fiber streamlines. Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. Level set trees were used for interactive exploration of patterns in the endpoint distributions of the mapped fiber pathways and an efficient segmentation of the pathways that had empirical accuracy comparable to standard nonparametric clustering techniques. We show that level set trees can also be generalized to model pseudo-density functions in order to analyze a broader array of data types, including entire fiber streamlines. Finally, resampling methods show the reliability of the level set tree as a descriptive measure of topographic structure, illustrating its potential as a statistical descriptor in brain imaging analysis. These results highlight the broad applicability of level set trees for visualizing and analyzing high-dimensional data like fiber tractography output. PMID:24714673

In Which Ways and to What Extent Do English and Shanghai Students Understand Linear Function?

ERIC Educational Resources Information Center

Wang, Yuqian; Barmby, Patrick; Bolden, David

2017-01-01

This study investigates how students in England and Shanghai understand linear function. Understanding is defined theoretically in terms of five hierarchical levels: Dependent Relationship; Connecting Representations; Property Noticing; Object Analysis; and Inventising. A pilot study instrument presented a set of problems to both cohorts, showing…

Refining Uses and Gratifications with a Human Information Processing Model.

ERIC Educational Resources Information Center

Griffin, Robert J.

A study was conducted as part of a program to develop and test an individual level communications model. The model proposes that audience members bring to communications situations a set of learned cognitive processing strategies that produce cognitive structural representations of information in memory to facilitate the meeting of the various…

Mapped grid methods for long-range molecules and cold collisions

NASA Astrophysics Data System (ADS)

Willner, K.; Dulieu, O.; Masnou-Seeuws, F.

2004-01-01

The paper discusses ways of improving the accuracy of numerical calculations for vibrational levels of diatomic molecules close to the dissociation limit or for ultracold collisions, in the framework of a grid representation. In order to avoid the implementation of very large grids, Kokoouline et al. [J. Chem. Phys. 110, 9865 (1999)] have proposed a mapping procedure through introduction of an adaptive coordinate x subjected to the variation of the local de Broglie wavelength as a function of the internuclear distance R. Some unphysical levels ("ghosts") then appear in the vibrational series computed via a mapped Fourier grid representation. In the present work the choice of the basis set is reexamined, and two alternative expansions are discussed: Sine functions and Hardy functions. It is shown that use of a basis set with fixed nodes at both grid ends is efficient to eliminate "ghost" solutions. It is further shown that the Hamiltonian matrix in the sine basis can be calculated very accurately by using an auxiliary basis of cosine functions, overcoming the problems arising from numerical calculation of the Jacobian J(x) of the R→x coordinate transformation.

Developing PFC representations using reinforcement learning

PubMed Central

Reynolds, Jeremy R.; O'Reilly, Randall C.

2009-01-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically (Fuster, 1990, Koechlin, Ody, & Kouneiher, 2003, & Miller, Galanter, & Pribram, 1960) However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data. PMID:19591977

"Interactive Classification Technology"

NASA Technical Reports Server (NTRS)

deBessonet, Cary

1999-01-01

The investigators are upgrading a knowledge representation language called SL (Symbolic Language) and an automated reasoning system called SMS (Symbolic Manipulation System) to enable the technologies to be used in automated reasoning and interactive classification systems. The overall goals of the project are: a) the enhancement of the representation language SL to accommodate multiple perspectives and a wider range of meaning; b) the development of a sufficient set of operators to enable the interpreter of SL to handle representations of basic cognitive acts; and c) the development of a default inference scheme to operate over SL notation as it is encoded. As to particular goals the first-year work plan focused on inferencing and.representation issues, including: 1) the development of higher level cognitive/ classification functions and conceptual models for use in inferencing and decision making; 2) the specification of a more detailed scheme of defaults and the enrichment of SL notation to accommodate the scheme; and 3) the adoption of additional perspectives for inferencing.

Qualitative aspects of representational competence among college chemistry students: Multiple representations and their role in the understanding of ideal gases

NASA Astrophysics Data System (ADS)

Madden, Sean Patrick

This study examined the role of multiple representations of chemical phenomena, specifically, the temperature-pressure relationship of ideal gases, in the problem solving strategies of college chemistry students. Volunteers included students enrolled in a first semester general chemistry course at a western university. Two additional volunteers from the same university were asked to participate and serve as models of greater sophistication. One was a senior chemistry major; another was a junior science writing major. Volunteers completed an initial screening task involving multiple representations of concentration and dilution concepts. Based on the results of this screening instrument a smaller set of subjects were asked to complete a think aloud session involving multiple representations of the temperature-pressure relationship. Data consisted of the written work of the volunteers and transcripts from videotaped think aloud sessions. The data were evaluated by the researcher and two other graduate students in chemical education using a coding scheme (Kozma, Schank, Coppola, Michalchik, and Allen. 2000). This coding scheme was designed to identify essential features of representational competence and differences in uses of multiple representations. The results indicate that students tend to have a strong preference for one type of representation. Students scoring low on representational competence, as measured by the rubric, ignored important features of some representations or acknowledged them only superficially. Students scoring higher on representational competence made meaningful connections among representations. The more advanced students, those who rated highly on representational competence, tended to use their preferred representation in a heuristic manner to establish meaning for other representations. The more advanced students also reflected upon the problem at greater length before beginning work. Molecular level sketches seemed to be the most difficult type of representation for students to interpret. Most subjects scored higher on representational competence when engaged in creating graphs and sketches than when evaluating provided representations. This study suggests that students may benefit from an instruction that emphasizes heuristic use of multiple representations in chemistry problem solving. An instructional strategy that makes use of a variety of representations and requires students to create their own representations may have measurable benefits to chemistry students.

Detection of dual-band infrared small target based on joint dynamic sparse representation

NASA Astrophysics Data System (ADS)

Zhou, Jinwei; Li, Jicheng; Shi, Zhiguang; Lu, Xiaowei; Ren, Dongwei

2015-10-01

Infrared small target detection is a crucial and yet still is a difficult issue in aeronautic and astronautic applications. Sparse representation is an important mathematic tool and has been used extensively in image processing in recent years. Joint sparse representation is applied in dual-band infrared dim target detection in this paper. Firstly, according to the characters of dim targets in dual-band infrared images, 2-dimension Gaussian intensity model was used to construct target dictionary, then the dictionary was classified into different sub-classes according to different positions of Gaussian function's center point in image block; The fact that dual-band small targets detection can use the same dictionary and the sparsity doesn't lie in atom-level but in sub-class level was utilized, hence the detection of targets in dual-band infrared images was converted to be a joint dynamic sparse representation problem. And the dynamic active sets were used to describe the sparse constraint of coefficients. Two modified sparsity concentration index (SCI) criteria was proposed to evaluate whether targets exist in the images. In experiments, it shows that the proposed algorithm can achieve better detecting performance and dual-band detection is much more robust to noise compared with single-band detection. Moreover, the proposed method can be expanded to multi-spectrum small target detection.

Children's Representation and Imitation of Events: How Goal Organization Influences 3-Year-Old Children's Memory for Action Sequences.

PubMed

Loucks, Jeff; Mutschler, Christina; Meltzoff, Andrew N

2017-09-01

Children's imitation of adults plays a prominent role in human cognitive development. However, few studies have investigated how children represent the complex structure of observed actions which underlies their imitation. We integrate theories of action segmentation, memory, and imitation to investigate whether children's event representation is organized according to veridical serial order or a higher level goal structure. Children were randomly assigned to learn novel event sequences either through interactive hands-on experience (Study 1) or via storybook (Study 2). Results demonstrate that children's representation of observed actions is organized according to higher level goals, even at the cost of representing the veridical temporal ordering of the sequence. We argue that prioritizing goal structure enhances event memory, and that this mental organization is a key mechanism of social-cognitive development in real-world, dynamic environments. It supports cultural learning and imitation in ecologically valid settings when social agents are multitasking and not demonstrating one isolated goal at a time. Copyright © 2016 Cognitive Science Society, Inc.

LOD map--A visual interface for navigating multiresolution volume visualization.

PubMed

Wang, Chaoli; Shen, Han-Wei

2006-01-01

In multiresolution volume visualization, a visual representation of level-of-detail (LOD) quality is important for us to examine, compare, and validate different LOD selection algorithms. While traditional methods rely on ultimate images for quality measurement, we introduce the LOD map--an alternative representation of LOD quality and a visual interface for navigating multiresolution data exploration. Our measure for LOD quality is based on the formulation of entropy from information theory. The measure takes into account the distortion and contribution of multiresolution data blocks. A LOD map is generated through the mapping of key LOD ingredients to a treemap representation. The ordered treemap layout is used for relative stable update of the LOD map when the view or LOD changes. This visual interface not only indicates the quality of LODs in an intuitive way, but also provides immediate suggestions for possible LOD improvement through visually-striking features. It also allows us to compare different views and perform rendering budget control. A set of interactive techniques is proposed to make the LOD adjustment a simple and easy task. We demonstrate the effectiveness and efficiency of our approach on large scientific and medical data sets.

Representational Realism, Closed Theories and the Quantum to Classical Limit

NASA Astrophysics Data System (ADS)

de Ronde, Christian

In this chapter, we discuss the representational realist stance as a pluralistontic approach to inter-theoretic relationships. Our stance stresses the fact that physical theories require the necessary consideration of a conceptual level of discourse which determines and configures the specific field of phenomena discussed by each particular theory. We will criticize the orthodox line of research which has grounded the analysis about QM in two (Bohrian) metaphysical presuppositions - accepted in the present as dogmas that all interpretations must follow. We will also examine how the orthodox project of "bridging the gap" between the quantum and the classical domains has constrained the possibilities of research, producing only a limited set of interpretational problems which only focus in the justification of "classical reality" and exclude the possibility of analyzing the possibilities of non-classical conceptual representations of QM. The representational realist stance introduces two new problems, namely, the superposition problem and the contextuality problem, which consider explicitly the conceptual representation of orthodox QM beyond the mere reference to mathematical structures and measurement outcomes. In the final part of the chapter, we revisit, from representational realist perspective, the quantum to classical limit and the orthodox claim that this inter-theoretic relation can be explained through the principle of decoherence.

One step forward, two steps back: worker representation and health and safety in the United Kingdom.

PubMed

Walters, David

2006-01-01

There is now quite strong evidence for a set of preconditions that help determine the effectiveness of worker representation and consultation in improving health and safety outcomes. One of these preconditions is a regulatory framework that defines workers' rights to representation and employers' obligations to respond. Using the United Kingdom as its focus, this article explores developments at the national policy level. It shows how long-awaited legislative reforms to improve provisions for worker representation in health and safety have so far failed to materialize and, instead, government strategy has concentrated on promoting voluntary approaches. The author reviews the evidence of what makes worker representation in health and safety effective and suggests that, far from abandoning approaches to legislative reform, the U.K. agencies should be seeking to make improvements to the British provisions if they are to provide the necessary stimulus and support for worker representation in health and safety at work. Such improvements need to address long-standing weaknesses in existing provisions and their relevance to the changing world of work. The arguments presented here apply to the essential role of regulatory support for worker participation in all advanced market economies if it is to improve health and safety outcomes.

Spatial versus Tree Representations of Proximity Data.

ERIC Educational Resources Information Center

Pruzansky, Sandra; And Others

1982-01-01

Two-dimensional euclidean planes and additive trees are two of the most common representations of proximity data for multidimensional scaling. Guidelines for comparing these representations and discovering properties that could help identify which representation is more appropriate for a given data set are presented. (Author/JKS)

Fuzzy associative memories

NASA Technical Reports Server (NTRS)

Kosko, Bart

1991-01-01

Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

Representations of Violence in Social Science Textbooks: Rethinking Opportunities for Peacebuilding in the Colombian and South African Post-Conflict Scenarios

ERIC Educational Resources Information Center

Rodríguez-Gómez, Diana; Foulds, Kim; Sayed, Yusuf

2016-01-01

Recent years have witnessed violence in educational settings becoming an object of public concern and global mobilisation. International initiatives indicate rising levels of awareness regarding the interconnectedness of violence and education. In this context, international educational agendas identify violence in schools as a challenge to the…

Alzheimer's disease detection via automatic 3D caudate nucleus segmentation using coupled dictionary learning with level set formulation.

PubMed

Al-Shaikhli, Saif Dawood Salman; Yang, Michael Ying; Rosenhahn, Bodo

2016-12-01

This paper presents a novel method for Alzheimer's disease classification via an automatic 3D caudate nucleus segmentation. The proposed method consists of segmentation and classification steps. In the segmentation step, we propose a novel level set cost function. The proposed cost function is constrained by a sparse representation of local image features using a dictionary learning method. We present coupled dictionaries: a feature dictionary of a grayscale brain image and a label dictionary of a caudate nucleus label image. Using online dictionary learning, the coupled dictionaries are learned from the training data. The learned coupled dictionaries are embedded into a level set function. In the classification step, a region-based feature dictionary is built. The region-based feature dictionary is learned from shape features of the caudate nucleus in the training data. The classification is based on the measure of the similarity between the sparse representation of region-based shape features of the segmented caudate in the test image and the region-based feature dictionary. The experimental results demonstrate the superiority of our method over the state-of-the-art methods by achieving a high segmentation (91.5%) and classification (92.5%) accuracy. In this paper, we find that the study of the caudate nucleus atrophy gives an advantage over the study of whole brain structure atrophy to detect Alzheimer's disease. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Reproducibility of UAV-based earth surface topography based on structure-from-motion algorithms.

NASA Astrophysics Data System (ADS)

Clapuyt, François; Vanacker, Veerle; Van Oost, Kristof

2014-05-01

A representation of the earth surface at very high spatial resolution is crucial to accurately map small geomorphic landforms with high precision. Very high resolution digital surface models (DSM) can then be used to quantify changes in earth surface topography over time, based on differencing of DSMs taken at various moments in time. However, it is compulsory to have both high accuracy for each topographic representation and consistency between measurements over time, as DSM differencing automatically leads to error propagation. This study investigates the reproducibility of reconstructions of earth surface topography based on structure-from-motion (SFM) algorithms. To this end, we equipped an eight-propeller drone with a standard reflex camera. This equipment can easily be deployed in the field, as it is a lightweight, low-cost system in comparison with classic aerial photo surveys and terrestrial or airborne LiDAR scanning. Four sets of aerial photographs were created for one test field. The sets of airphotos differ in focal length, and viewing angles, i.e. nadir view and ground-level view. In addition, the importance of the accuracy of ground control points for the construction of a georeferenced point cloud was assessed using two different GPS devices with horizontal accuracy at resp. the sub-meter and sub-decimeter level. Airphoto datasets were processed with SFM algorithm and the resulting point clouds were georeferenced. Then, the surface representations were compared with each other to assess the reproducibility of the earth surface topography. Finally, consistency between independent datasets is discussed.

Representing Chemistry: How Instructional Use of Symbolic, Microscopic, and Macroscopic Mode Influences Student Conceptual Understanding in Chemistry

NASA Astrophysics Data System (ADS)

Wood, Lorelei

Chemistry as a subject is difficult to learn and understand, due in part to the specific language used by practitioners in their professional and scientific communications. The language and ways of representing chemical interactions have been grouped into three modes of representation used by chemistry instructors, and ultimately by students in understanding the discipline. The first of these three modes of representation is the symbolic mode, which uses a standard set of rules for chemical nomenclature set out by the IUPAC. The second mode of representation is that of microscopic, which depicts chemical compounds as discrete units made up of atoms and molecules, with a particular ratio of atoms to a molecule or formula unit. The third mode of representation is macroscopic, what can be seen, experienced, or measured directly, like ice melting or a color change during a chemical reaction. Recent evidence suggests that chemistry instructors can assist their students in making the connections between the modes of representation by incorporating all three modes into their teaching and discussions, and overtly connecting the modes during instruction. In this research, chemistry teachers at the community college level were observed over the course of an entire semester, to evaluate their instructional use of mode of representation. The students of these teachers were tested prior to and after a semester's worth of instruction, and changes in the basic chemistry conceptual knowledge of these students were compared. Additionally, a subset of the overall population that was pre- and post-tested was interviewed at length using demonstrations of chemical phenomenon that students were asked to translate using all three modes of representation. Analysis of the instruction of three community college teachers shows there were significant differences among these teachers in their instructional use of mode of representation. Additionally, the students of these three teachers had differential and statistically significant achievement over the course of the semester. This research supports results of other similar studies, as well as providing some unexpected results from the students involved.

Computer-aided detection of initial polyp candidates with level set-based adaptive convolution

NASA Astrophysics Data System (ADS)

Zhu, Hongbin; Duan, Chaijie; Liang, Zhengrong

2009-02-01

In order to eliminate or weaken the interference between different topological structures on the colon wall, adaptive and normalized convolution methods were used to compute the first and second order spatial derivatives of computed tomographic colonography images, which is the beginning of various geometric analyses. However, the performance of such methods greatly depends on the single-layer representation of the colon wall, which is called the starting layer (SL) in the following text. In this paper, we introduce a level set-based adaptive convolution (LSAC) method to compute the spatial derivatives, in which the level set method is employed to determine a more reasonable SL. The LSAC was applied to a computer-aided detection (CAD) scheme to detect the initial polyp candidates, and experiments showed that it benefits the CAD scheme in both the detection sensitivity and specificity as compared to our previous work.

Two-way coupled SPH and particle level set fluid simulation.

PubMed

Losasso, Frank; Talton, Jerry; Kwatra, Nipun; Fedkiw, Ronald

2008-01-01

Grid-based methods have difficulty resolving features on or below the scale of the underlying grid. Although adaptive methods (e.g. RLE, octrees) can alleviate this to some degree, separate techniques are still required for simulating small-scale phenomena such as spray and foam, especially since these more diffuse materials typically behave quite differently than their denser counterparts. In this paper, we propose a two-way coupled simulation framework that uses the particle level set method to efficiently model dense liquid volumes and a smoothed particle hydrodynamics (SPH) method to simulate diffuse regions such as sprays. Our novel SPH method allows us to simulate both dense and diffuse water volumes, fully incorporates the particles that are automatically generated by the particle level set method in under-resolved regions, and allows for two way mixing between dense SPH volumes and grid-based liquid representations.

The Chemical Validation and Standardization Platform (CVSP): large-scale automated validation of chemical structure datasets.

PubMed

Karapetyan, Karen; Batchelor, Colin; Sharpe, David; Tkachenko, Valery; Williams, Antony J

2015-01-01

There are presently hundreds of online databases hosting millions of chemical compounds and associated data. As a result of the number of cheminformatics software tools that can be used to produce the data, subtle differences between the various cheminformatics platforms, as well as the naivety of the software users, there are a myriad of issues that can exist with chemical structure representations online. In order to help facilitate validation and standardization of chemical structure datasets from various sources we have delivered a freely available internet-based platform to the community for the processing of chemical compound datasets. The chemical validation and standardization platform (CVSP) both validates and standardizes chemical structure representations according to sets of systematic rules. The chemical validation algorithms detect issues with submitted molecular representations using pre-defined or user-defined dictionary-based molecular patterns that are chemically suspicious or potentially requiring manual review. Each identified issue is assigned one of three levels of severity - Information, Warning, and Error - in order to conveniently inform the user of the need to browse and review subsets of their data. The validation process includes validation of atoms and bonds (e.g., making aware of query atoms and bonds), valences, and stereo. The standard form of submission of collections of data, the SDF file, allows the user to map the data fields to predefined CVSP fields for the purpose of cross-validating associated SMILES and InChIs with the connection tables contained within the SDF file. This platform has been applied to the analysis of a large number of data sets prepared for deposition to our ChemSpider database and in preparation of data for the Open PHACTS project. In this work we review the results of the automated validation of the DrugBank dataset, a popular drug and drug target database utilized by the community, and ChEMBL 17 data set. CVSP web site is located at http://cvsp.chemspider.com/. A platform for the validation and standardization of chemical structure representations of various formats has been developed and made available to the community to assist and encourage the processing of chemical structure files to produce more homogeneous compound representations for exchange and interchange between online databases. While the CVSP platform is designed with flexibility inherent to the rules that can be used for processing the data we have produced a recommended rule set based on our own experiences with the large data sets such as DrugBank, ChEMBL, and data sets from ChemSpider.

Determination and representation of electric charge distributions associated with adverse weather conditions

NASA Technical Reports Server (NTRS)

Rompala, John T.

1992-01-01

Algorithms are presented for determining the size and location of electric charges which model storm systems and lightning strikes. The analysis utilizes readings from a grid of ground level field mills and geometric constraints on parameters to arrive at a representative set of charges. This set is used to generate three dimensional graphical depictions of the set as well as contour maps of the ground level electrical environment over the grid. The composite, analytic and graphic package is demonstrated and evaluated using controlled input data and archived data from a storm system. The results demonstrate the packages utility as: an operational tool in appraising adverse weather conditions; a research tool in studies of topics such as storm structure, storm dynamics, and lightning; and a tool in designing and evaluating grid systems.

A geometric modeler based on a dual-geometry representation polyhedra and rational b-splines

NASA Technical Reports Server (NTRS)

Klosterman, A. L.

1984-01-01

For speed and data base reasons, solid geometric modeling of large complex practical systems is usually approximated by a polyhedra representation. Precise parametric surface and implicit algebraic modelers are available but it is not yet practical to model the same level of system complexity with these precise modelers. In response to this contrast the GEOMOD geometric modeling system was built so that a polyhedra abstraction of the geometry would be available for interactive modeling without losing the precise definition of the geometry. Part of the reason that polyhedra modelers are effective is that all bounded surfaces can be represented in a single canonical format (i.e., sets of planar polygons). This permits a very simple and compact data structure. Nonuniform rational B-splines are currently the best representation to describe a very large class of geometry precisely with one canonical format. The specific capabilities of the modeler are described.

Design of an activity landscape view taking compound-based feature probabilities into account.

PubMed

Zhang, Bijun; Vogt, Martin; Bajorath, Jürgen

2014-09-01

Activity landscapes (ALs) of compound data sets are rationalized as graphical representations that integrate similarity and potency relationships between active compounds. ALs enable the visualization of structure-activity relationship (SAR) information and are thus computational tools of interest for medicinal chemistry. For AL generation, similarity and potency relationships are typically evaluated in a pairwise manner and major AL features are assessed at the level of compound pairs. In this study, we add a conditional probability formalism to AL design that makes it possible to quantify the probability of individual compounds to contribute to characteristic AL features. Making this information graphically accessible in a molecular network-based AL representation is shown to further increase AL information content and helps to quickly focus on SAR-informative compound subsets. This feature probability-based AL variant extends the current spectrum of AL representations for medicinal chemistry applications.

Three-dimensional fractional-spin gravity

NASA Astrophysics Data System (ADS)

Boulanger, Nicolas; Sundell, Per; Valenzuela, Mauricio

2014-02-01

Using Wigner-deformed Heisenberg oscillators, we construct 3D Chern-Simons models consisting of fractional-spin fields coupled to higher-spin gravity and internal nonabelian gauge fields. The gauge algebras consist of Lorentz-tensorial Blencowe-Vasiliev higher-spin algebras and compact internal algebras intertwined by infinite-dimensional generators in lowest-weight representations of the Lorentz algebra with fractional spin. In integer or half-integer non-unitary cases, there exist truncations to gl(ℓ , ℓ ± 1) or gl(ℓ|ℓ ± 1) models. In all non-unitary cases, the internal gauge fields can be set to zero. At the semi-classical level, the fractional-spin fields are either Grassmann even or odd. The action requires the enveloping-algebra representation of the deformed oscillators, while their Fock-space representation suffices on-shell. The project was funded in part by F.R.S.-FNRS " Ulysse" Incentive Grant for Mobility in Scientific Research.

Sequence Diversity Diagram for comparative analysis of multiple sequence alignments.

PubMed

Sakai, Ryo; Aerts, Jan

2014-01-01

The sequence logo is a graphical representation of a set of aligned sequences, commonly used to depict conservation of amino acid or nucleotide sequences. Although it effectively communicates the amount of information present at every position, this visual representation falls short when the domain task is to compare between two or more sets of aligned sequences. We present a new visual presentation called a Sequence Diversity Diagram and validate our design choices with a case study. Our software was developed using the open-source program called Processing. It loads multiple sequence alignment FASTA files and a configuration file, which can be modified as needed to change the visualization. The redesigned figure improves on the visual comparison of two or more sets, and it additionally encodes information on sequential position conservation. In our case study of the adenylate kinase lid domain, the Sequence Diversity Diagram reveals unexpected patterns and new insights, for example the identification of subgroups within the protein subfamily. Our future work will integrate this visual encoding into interactive visualization tools to support higher level data exploration tasks.

Achievement emotions in elementary, middle, and high school: how do students feel about specific contexts in terms of settings and subject-domains?

PubMed

Raccanello, Daniela; Brondino, Margherita; De Bernardi, Bianca

2013-12-01

The present work investigates students' representation of achievement emotions, focusing in context-specific situations in terms of settings and subject-domains, as a function of grade level. We involved 527 fourth-, seventh-, and eleventh-graders, who evaluated ten discrete emotions through questionnaires, with reference to verbal language and mathematics, and different settings (class, homework, tests). Confirmatory multitrait-multimethod analyses indicated higher salience of subject-domains rather than settings for all the emotions; however, complexity of reality was best explained when also settings were accounted for. Analyses of variance revealed higher intensity of positive emotions for younger students, and the opposite pattern for older students; significant differences for most of the emotions based on the evaluative nature of settings, moderated by class levels; more intense positive emotions for mathematics and more intense negative emotions for Italian. Results are discussed considering their theoretical and applied relevance, corroborating previous literature on domain-specificity. © 2013 The Scandinavian Psychological Associations.

If you want to save, focus on the forest rather than on trees. The effects of shifts in levels of construal on saving decisions.

PubMed

Rudzinska-Wojciechowska, Joanna

2017-01-01

Although financial decisions are expected to be rational, there is a growing body of experimental research indicating that small psychological changes in one's mind-set in the actual decision-making moment might affect saving ratios. In this article, another type of change in one's mind-set, which can influence saving decisions, is explored, namely the level of construal. Construal level is a key descriptor of people's cognitive representations of targets, and is a way of characterising the mental mind-sets people use. Building on recent advances in the link between construal levels and intertemporal choices, the present research evaluates the effect of shifts in levels of construal in the very moment of decision making on people's propensity to save money. It is suggested that triggering a high-level construal mind-set would influence individuals' financial decisions and result in greater willingness to save than triggering a low-level construal mind-set. This assumption is supported by the findings: across three experiments, those with an abstract mind-set showed an increased willingness to save when compared to those with a concrete mind-set. The first experiment demonstrated that people in an abstract mind-set are more willing to delay financial gratification than those in a concrete mind-set. In the second and third experiments, those with an abstract mind-set showed an increased willingness to save when compared to those with a concrete mind-set. The research provides further evidence that mental states, which can be evoked by previous, unrelated tasks, such as level of cognitive abstraction, can influence everyday financial decisions. It, thus, highlights the role of situational factors that consumers may be not aware of, which still affect their savings decisions.

The contribution of stimulus frequency and recency to set-size effects.

PubMed

van 't Wout, Félice

2018-06-01

Hick's law describes the increase in choice reaction time (RT) with the number of stimulus-response (S-R) mappings. However, in choice RT experiments, set-size is typically confounded with stimulus recency and frequency: With a smaller set-size, each stimulus occurs on average more frequently and more recently than with a larger set-size. To determine to what extent stimulus recency and frequency contribute to the set-size effect, stimulus set-size was manipulated independently of stimulus recency and frequency, by keeping recency and frequency constant for a subset of the stimuli. Although this substantially reduced the set-size effect (by approximately two-thirds for these stimuli), it did not eliminate it. Thus, the time required to retrieve an S-R mapping from memory is (at least in part) determined by the number of alternatives. In contrast, a recent task switching study (Van 't Wout et al. in Journal of Experimental Psychology: Learning, Memory & Cognition., 41, 363-376, 2015) using the same manipulation found that the time required to retrieve a task-set from memory is not influenced by the number of alternatives per se. Hence, this experiment further supports a distinction between two levels of representation in task-set control: The level of task-sets, and the level of S-R mappings.

Emergent categorical representation of natural, complex sounds resulting from the early post-natal sound environment

PubMed Central

Bao, Shaowen; Chang, Edward F.; Teng, Ching-Ling; Heiser, Marc A.; Merzenich, Michael M.

2013-01-01

Cortical sensory representations can be reorganized by sensory exposure in an epoch of early development. The adaptive role of this type of plasticity for natural sounds in sensory development is, however, unclear. We have reared rats in a naturalistic, complex acoustic environment and examined their auditory representations. We found that cortical neurons became more selective to spectrotemporal features in the experienced sounds. At the neuronal population level, more neurons were involved in representing the whole set of complex sounds, but fewer neurons actually responded to each individual sound, but with greater magnitudes. A comparison of population-temporal responses to the experienced complex sounds revealed that cortical responses to different renderings of the same song motif were more similar, indicating that the cortical neurons became less sensitive to natural acoustic variations associated with stimulus context and sound renderings. By contrast, cortical responses to sounds of different motifs became more distinctive, suggesting that cortical neurons were tuned to the defining features of the experienced sounds. These effects lead to emergent “categorical” representations of the experienced sounds, which presumably facilitate their recognition. PMID:23747304

Pedagogy and Quality in Indian Slum School Settings: A Bernsteinian Analysis of Visual Representations in the Integrated Child Development Service

ERIC Educational Resources Information Center

Chawla-Duggan, Rita

2016-01-01

This paper focuses upon the micro level of the pre-school classroom, taking the example of the Indian Integrated Child Development Service (ICDS), and the discourse of "child-centred" pedagogy that is often associated with quality pre-schooling. Through an analysis of visual data, semi-structured and film elicitation interviews drawn…

Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization.

PubMed

Craft, David

2010-10-01

A discrete set of points and their convex combinations can serve as a sparse representation of the Pareto surface in multiple objective convex optimization. We develop a method to evaluate the quality of such a representation, and show by example that in multiple objective radiotherapy planning, the number of Pareto optimal solutions needed to represent Pareto surfaces of up to five dimensions grows at most linearly with the number of objectives. The method described is also applicable to the representation of convex sets. Copyright © 2009 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Representations of mechanical assembly sequences

NASA Technical Reports Server (NTRS)

Homem De Mello, Luiz S.; Sanderson, Arthur C.

1991-01-01

Five types of representations for assembly sequences are reviewed: the directed graph of feasible assembly sequences, the AND/OR graph of feasible assembly sequences, the set of establishment conditions, and two types of sets of precedence relationships. (precedence relationships between the establishment of one connection between parts and the establishment of another connection, and precedence relationships between the establishment of one connection and states of the assembly process). The mappings of one representation into the others are established. The correctness and completeness of these representations are established. The results presented are needed in the proof of correctness and completeness of algorithms for the generation of mechanical assembly sequences.

A path-oriented matrix-based knowledge representation system

NASA Technical Reports Server (NTRS)

Feyock, Stefan; Karamouzis, Stamos T.

1993-01-01

Experience has shown that designing a good representation is often the key to turning hard problems into simple ones. Most AI (Artificial Intelligence) search/representation techniques are oriented toward an infinite domain of objects and arbitrary relations among them. In reality much of what needs to be represented in AI can be expressed using a finite domain and unary or binary predicates. Well-known vector- and matrix-based representations can efficiently represent finite domains and unary/binary predicates, and allow effective extraction of path information by generalized transitive closure/path matrix computations. In order to avoid space limitations a set of abstract sparse matrix data types was developed along with a set of operations on them. This representation forms the basis of an intelligent information system for representing and manipulating relational data.

On the representation of atmospheric blocking in EURO-CORDEX control runs

NASA Astrophysics Data System (ADS)

Jury, Martin W.; García, Sixto; Gutiérrez, José M.

2017-04-01

While regional climate models (RCMs) have been shown to yield improved projections, due to better representations of orography and higher resolved scales, impacts on mesoscale phenomena like atmospheric blocking have been hardly addressed. In this study we clarify if the EURO-CORDEX domain is large enough to allow the RCMs to significantly amplify the blocking representation in reference to the underlying driving data. Therefore, we analyzed blocking accompanying anomalies in temperature near the surface (TAS) and precipitation rate (PR) for a set of RCMs. 5 RCMs stem from the ensemble of EURO-CORDEX control runs, while 3 RCMs are WRF models with different nudging realizations, all of them are driven by ERA-Interim. The used blocking detection method detects blockings by localizing high pressure systems between 55°N and 65°N with the use of geopotential height gradients on the 500 hPa level (Z500), and was applied to ERA-Interim and the mentioned RCM data between 1981 and 2010. Detected blockings centers were spatially attributed to three sectors, which have been shown to display distinctive impacts on TAS and PR during blocking episodes. As a reference for TAS and PR we used 86 weather stations across Europe from the ECA&D dataset. Our results indicate, that little improvement can be expected in the representation of Z500 fields by the RCMs. Most of them show less blocking than the driving data, while blocking representation was most in agreement with the driving data for RCMs that have been strongly conditioned to the driving data. Further, in our idealized setting the RCMs were not able to reproduce the anomalies for TAS connected to blocking. Moreover, using the blocking index of the driving data could be considered correct, because the representation of TAS and PR for falsely detected blocking and non-blocking days in the RCMs did not deviate strongly.

An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs

PubMed Central

Mosaliganti, Kishore R.; Gelas, Arnaud; Megason, Sean G.

2013-01-01

In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) and grid representations (point, mesh, and image-based). Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g., gradient and Hessians) across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a developing zebrafish embryo. PMID:24501592

An efficient, scalable, and adaptable framework for solving generic systems of level-set PDEs.

PubMed

Mosaliganti, Kishore R; Gelas, Arnaud; Megason, Sean G

2013-01-01

In the last decade, level-set methods have been actively developed for applications in image registration, segmentation, tracking, and reconstruction. However, the development of a wide variety of level-set PDEs and their numerical discretization schemes, coupled with hybrid combinations of PDE terms, stopping criteria, and reinitialization strategies, has created a software logistics problem. In the absence of an integrative design, current toolkits support only specific types of level-set implementations which restrict future algorithm development since extensions require significant code duplication and effort. In the new NIH/NLM Insight Toolkit (ITK) v4 architecture, we implemented a level-set software design that is flexible to different numerical (continuous, discrete, and sparse) and grid representations (point, mesh, and image-based). Given that a generic PDE is a summation of different terms, we used a set of linked containers to which level-set terms can be added or deleted at any point in the evolution process. This container-based approach allows the user to explore and customize terms in the level-set equation at compile-time in a flexible manner. The framework is optimized so that repeated computations of common intensity functions (e.g., gradient and Hessians) across multiple terms is eliminated. The framework further enables the evolution of multiple level-sets for multi-object segmentation and processing of large datasets. For doing so, we restrict level-set domains to subsets of the image domain and use multithreading strategies to process groups of subdomains or level-set functions. Users can also select from a variety of reinitialization policies and stopping criteria. Finally, we developed a visualization framework that shows the evolution of a level-set in real-time to help guide algorithm development and parameter optimization. We demonstrate the power of our new framework using confocal microscopy images of cells in a developing zebrafish embryo.

Representational Competence in Chemistry: A Comparison between Students with Different Levels of Understanding of Basic Chemical Concepts and Chemical Representations

ERIC Educational Resources Information Center

Sim, Joong Hiong; Daniel, Esther Gnanamalar Sarojini

2014-01-01

Representational competence is defined as "skills in interpreting and using representations". This study attempted to compare students' of high, medium, and low levels of understanding of (1) basic chemical concepts, and (2) chemical representations, in their representational competence. A total of 411 Form 4 science students (mean age =…

Shape Similarity, Better than Semantic Membership, Accounts for the Structure of Visual Object Representations in a Population of Monkey Inferotemporal Neurons

PubMed Central

DiCarlo, James J.; Zecchina, Riccardo; Zoccolan, Davide

2013-01-01

The anterior inferotemporal cortex (IT) is the highest stage along the hierarchy of visual areas that, in primates, processes visual objects. Although several lines of evidence suggest that IT primarily represents visual shape information, some recent studies have argued that neuronal ensembles in IT code the semantic membership of visual objects (i.e., represent conceptual classes such as animate and inanimate objects). In this study, we investigated to what extent semantic, rather than purely visual information, is represented in IT by performing a multivariate analysis of IT responses to a set of visual objects. By relying on a variety of machine-learning approaches (including a cutting-edge clustering algorithm that has been recently developed in the domain of statistical physics), we found that, in most instances, IT representation of visual objects is accounted for by their similarity at the level of shape or, more surprisingly, low-level visual properties. Only in a few cases we observed IT representations of semantic classes that were not explainable by the visual similarity of their members. Overall, these findings reassert the primary function of IT as a conveyor of explicit visual shape information, and reveal that low-level visual properties are represented in IT to a greater extent than previously appreciated. In addition, our work demonstrates how combining a variety of state-of-the-art multivariate approaches, and carefully estimating the contribution of shape similarity to the representation of object categories, can substantially advance our understanding of neuronal coding of visual objects in cortex. PMID:23950700

Individual differences in ensemble perception reveal multiple, independent levels of ensemble representation.

PubMed

Haberman, Jason; Brady, Timothy F; Alvarez, George A

2015-04-01

Ensemble perception, including the ability to "see the average" from a group of items, operates in numerous feature domains (size, orientation, speed, facial expression, etc.). Although the ubiquity of ensemble representations is well established, the large-scale cognitive architecture of this process remains poorly defined. We address this using an individual differences approach. In a series of experiments, observers saw groups of objects and reported either a single item from the group or the average of the entire group. High-level ensemble representations (e.g., average facial expression) showed complete independence from low-level ensemble representations (e.g., average orientation). In contrast, low-level ensemble representations (e.g., orientation and color) were correlated with each other, but not with high-level ensemble representations (e.g., facial expression and person identity). These results suggest that there is not a single domain-general ensemble mechanism, and that the relationship among various ensemble representations depends on how proximal they are in representational space. (c) 2015 APA, all rights reserved).

[Stakeholder representations of the role of the intermediate level of the DRC health system].

PubMed

Mbeva, Jean Bosco Kahindo; Karemere, Hermès; Schirvel, Carole; Porignon, Denis

2014-01-01

Intermediate health care structures in the DRC were designed during the setting-up of primary health care in a perspective of health district support. This study was designed to describe stakeholder representations of the intermediate level of the DRC health system during the first 30 years of the primary health care system. This case study was based on inductive analysis of data from 27 key informant interviews.. The intermediate level of the health system, lacking sufficient expertise and funding during the 1980s, was confined to inspection and control functions, answering to the central level of the Ministry of health and provincial authorities. Since the 1990s, faced with the pressing demand for support from health district teams, whose self-management had to deal with humanitarian emergencies, the need to integrate vertical programmes, and cope with the logistics of many different actors, the intermediate heath system developed methods and tools to support heath districts. This resulted in a subsidiary model of the intermediate level, the perceived efficacy of which varies according to the province over recent years. The "subsidiary" model of the intermediary health system level seems a good alternative to the "control" model in DRC.

The M-Factor, a Bilingual Asset for Plurilinguals? Learners' Representations, Discourse Strategies and Third Language Acquisition in Institutional Contexts

ERIC Educational Resources Information Center

Bono, Mariana; Stratilaki, Sofia

2009-01-01

Within the framework of our research on learners' language practices and representations, this contribution explores how their representations about language uses and language learning shape the processes of learning and communication in school settings. More precisely, we will study learners' representations regarding the existence of a…

Establishing a group of endpoints to support collective operations without specifying unique identifiers for any endpoints

DOEpatents

Archer, Charles J.; Blocksom, Michael A.; Ratterman, Joseph D.; Smith, Brian E.; Xue, Hanghon

2016-02-02

A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

Establishing a group of endpoints in a parallel computer

DOEpatents

Archer, Charles J.; Blocksome, Michael A.; Ratterman, Joseph D.; Smith, Brian E.; Xue, Hanhong

2016-02-02

A parallel computer executes a number of tasks, each task includes a number of endpoints and the endpoints are configured to support collective operations. In such a parallel computer, establishing a group of endpoints receiving a user specification of a set of endpoints included in a global collection of endpoints, where the user specification defines the set in accordance with a predefined virtual representation of the endpoints, the predefined virtual representation is a data structure setting forth an organization of tasks and endpoints included in the global collection of endpoints and the user specification defines the set of endpoints without a user specification of a particular endpoint; and defining a group of endpoints in dependence upon the predefined virtual representation of the endpoints and the user specification.

Spatio-Temporal Data Model for Integrating Evolving Nation-Level Datasets

NASA Astrophysics Data System (ADS)

Sorokine, A.; Stewart, R. N.

2017-10-01

Ability to easily combine the data from diverse sources in a single analytical workflow is one of the greatest promises of the Big Data technologies. However, such integration is often challenging as datasets originate from different vendors, governments, and research communities that results in multiple incompatibilities including data representations, formats, and semantics. Semantics differences are hardest to handle: different communities often use different attribute definitions and associate the records with different sets of evolving geographic entities. Analysis of global socioeconomic variables across multiple datasets over prolonged time is often complicated by the difference in how boundaries and histories of countries or other geographic entities are represented. Here we propose an event-based data model for depicting and tracking histories of evolving geographic units (countries, provinces, etc.) and their representations in disparate data. The model addresses the semantic challenge of preserving identity of geographic entities over time by defining criteria for the entity existence, a set of events that may affect its existence, and rules for mapping between different representations (datasets). Proposed model is used for maintaining an evolving compound database of global socioeconomic and environmental data harvested from multiple sources. Practical implementation of our model is demonstrated using PostgreSQL object-relational database with the use of temporal, geospatial, and NoSQL database extensions.

Contour Tracking in Echocardiographic Sequences via Sparse Representation and Dictionary Learning

PubMed Central

Huang, Xiaojie; Dione, Donald P.; Compas, Colin B.; Papademetris, Xenophon; Lin, Ben A.; Bregasi, Alda; Sinusas, Albert J.; Staib, Lawrence H.; Duncan, James S.

2013-01-01

This paper presents a dynamical appearance model based on sparse representation and dictionary learning for tracking both endocardial and epicardial contours of the left ventricle in echocardiographic sequences. Instead of learning offline spatiotemporal priors from databases, we exploit the inherent spatiotemporal coherence of individual data to constraint cardiac contour estimation. The contour tracker is initialized with a manual tracing of the first frame. It employs multiscale sparse representation of local image appearance and learns online multiscale appearance dictionaries in a boosting framework as the image sequence is segmented frame-by-frame sequentially. The weights of multiscale appearance dictionaries are optimized automatically. Our region-based level set segmentation integrates a spectrum of complementary multilevel information including intensity, multiscale local appearance, and dynamical shape prediction. The approach is validated on twenty-six 4D canine echocardiographic images acquired from both healthy and post-infarct canines. The segmentation results agree well with expert manual tracings. The ejection fraction estimates also show good agreement with manual results. Advantages of our approach are demonstrated by comparisons with a conventional pure intensity model, a registration-based contour tracker, and a state-of-the-art database-dependent offline dynamical shape model. We also demonstrate the feasibility of clinical application by applying the method to four 4D human data sets. PMID:24292554

Representation and display of vector field topology in fluid flow data sets

NASA Technical Reports Server (NTRS)

Helman, James; Hesselink, Lambertus

1989-01-01

The visualization of physical processes in general and of vector fields in particular is discussed. An approach to visualizing flow topology that is based on the physics and mathematics underlying the physical phenomenon is presented. It involves determining critical points in the flow where the velocity vector vanishes. The critical points, connected by principal lines or planes, determine the topology of the flow. The complexity of the data is reduced without sacrificing the quantitative nature of the data set. By reducing the original vector field to a set of critical points and their connections, a representation of the topology of a two-dimensional vector field that is much smaller than the original data set but retains with full precision the information pertinent to the flow topology is obtained. This representation can be displayed as a set of points and tangent curves or as a graph. Analysis (including algorithms), display, interaction, and implementation aspects are discussed.

Representations of S{sub {infinity}} admissible with respect to Young subgroups

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nessonov, Nikolai I

2012-03-31

Let N be the set of positive integers and S{sub {infinity}} the set of finite permutations of N. For a partition {Pi} of the set N into infinite parts A{sub 1},A{sub 2},... we denote by S{sub {Pi}} the subgroup of S{sub {infinity}} whose elements leave invariant each of the sets A{sub j}. We set S{sub {infinity}}{sup (N)}={l_brace}s element of S{sub {infinity}:} s(i)=i for any i=1,2,...,N{r_brace}. A factor representation T of the group S{sub {infinity}} is said to be {Pi}-admissible if for some N it contains a nontrivial identity subrepresentation of the subgroup S{sub {Pi}} intersection S{sub {infinity}}{sup (N)}. In themore » paper, we obtain a classification of the {Pi}-admissible factor representations of S{sub {infinity}}. Bibliography: 14 titles.« less

A group matrix representation relevant to scales of measurement of clinical disease states via stratified vectors.

PubMed

Sawamura, Jitsuki; Morishita, Shigeru; Ishigooka, Jun

2016-02-09

Previously, we applied basic group theory and related concepts to scales of measurement of clinical disease states and clinical findings (including laboratory data). To gain a more concrete comprehension, we here apply the concept of matrix representation, which was not explicitly exploited in our previous work. Starting with a set of orthonormal vectors, called the basis, an operator Rj (an N-tuple patient disease state at the j-th session) was expressed as a set of stratified vectors representing plural operations on individual components, so as to satisfy the group matrix representation. The stratified vectors containing individual unit operations were combined into one-dimensional square matrices [Rj]s. The [Rj]s meet the matrix representation of a group (ring) as a K-algebra. Using the same-sized matrix of stratified vectors, we can also express changes in the plural set of [Rj]s. The method is demonstrated on simple examples. Despite the incompleteness of our model, the group matrix representation of stratified vectors offers a formal mathematical approach to clinical medicine, aligning it with other branches of natural science.

Continuous family of finite-dimensional representations of a solvable Lie algebra arising from singularities

PubMed Central

Yau, Stephen S.-T.

1983-01-01

A natural mapping from the set of complex analytic isolated hypersurface singularities to the set of finite dimensional Lie algebras is first defined. It is proven that the image under this natural mapping is contained in the set of solvable Lie algebras. This approach gives rise to a continuous inequivalent family of finite dimensional representations of a solvable Lie algebra. PMID:16593401

Coordinating complex decision support activities across distributed applications

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1994-01-01

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

Acceptance Presentation and Research Study Summary: Research in Educational Communications and Technology. 1982 Association for Educational Communications and Technology Young Researcher Award, Research and Theory Division.

ERIC Educational Resources Information Center

Canelos, James

An internal cognitive variable--mental imagery representation--was studied using a set of three information-processing strategies under external stimulus visual display conditions for various learning levels. The copy strategy provided verbal and visual dual-coding and required formation of a vivid mental image. The relational strategy combined…

High-Level Connectionist Models

DTIC Science & Technology

1993-10-01

subject of intense research since Axelrod (1984) showed that two agents engaged in a prisoner’s dilemma ( Poundstone , 1992) can evolve into mutually...The various parameter values for the program are set as described above unless otherwise noted. 4.1 Williams ’ Trigger Problem As an initial test...M. P. Vecchi. Optimization by simulated annealing. Sci- ence, 220:671-680, 1983. [39] R. J. Williams . Adaptive State Representation and Estimation

Braid group representation on quantum computation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aziz, Ryan Kasyfil, E-mail: kasyfilryan@gmail.com; Muchtadi-Alamsyah, Intan, E-mail: ntan@math.itb.ac.id

2015-09-30

There are many studies about topological representation of quantum computation recently. One of diagram representation of quantum computation is by using ZX-Calculus. In this paper we will make a diagrammatical scheme of Dense Coding. We also proved that ZX-Calculus diagram of maximally entangle state satisfies Yang-Baxter Equation and therefore, we can construct a Braid Group representation of set of maximally entangle state.

Impossibility Theorem in Proportional Representation Problem

NASA Astrophysics Data System (ADS)

Karpov, Alexander

2010-09-01

The study examines general axiomatics of Balinski and Young and analyzes existed proportional representation methods using this approach. The second part of the paper provides new axiomatics based on rational choice models. New system of axioms is applied to study known proportional representation systems. It is shown that there is no proportional representation method satisfying a minimal set of the axioms (monotonicity and neutrality).

The current practice of using multiple representations in year 4 science classrooms

NASA Astrophysics Data System (ADS)

Chuenmanee, Chanoknat; Thathong, Kongsak

2018-01-01

Multiple representations have been widely used as a reasoning tool for understanding complex scientific concepts. Thus this study attempted to investigate the current practice of using multiple representations on Year 4 science classrooms in terms of modes and levels which appear in curriculum documents, teaching plans, tasks and assessments, teaching practices, and students' behaviors. Indeed, documentary analysis, classroom observation, and interview were used as the data collection methods. First of all, Year 4 science documents were analyzed. Then classroom observation was used as a collecting method to seek what actually happen in the classroom. Finally, in-depth interviews were used to gather more information and obtain meaningful data. The finding reveals that many modes of verbal, visual, and tactile representations within three levels of representations are posed in Year 4 documents. Moreover, according to classroom observations and interviews, there are three main points of applying multiple representations into classrooms. First of all, various modes of representations were used, however, a huge number of them did not come together with the levels. The levels of representations, secondly, macroscopic and cellular levels were introduced into all classrooms while symbolic level was provided only in some classrooms. Finally, the connection of modes and levels pointed out that modes of representations were used without the considerations on the levels of them. So, it seems to be that teaching practice did not meet the aims of curriculum. Therefore, these issues were being considered in order to organize and design the further science lessons.

48 CFR 2052.209-71 - Contractor organizational conflicts of interest (representation).

Code of Federal Regulations, 2012 CFR

2012-10-01

... System NUCLEAR REGULATORY COMMISSION CLAUSES AND FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Text... / / involve situations or relationships of the type set forth in 48 CFR 2009.570-3(b). (a) If the representation, as completed, indicates that situations or relationships of the type set forth in 48 CFR 2009.570...

48 CFR 2052.209-71 - Contractor organizational conflicts of interest (representation).

Code of Federal Regulations, 2014 CFR

2014-10-01

... System NUCLEAR REGULATORY COMMISSION CLAUSES AND FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Text... / / involve situations or relationships of the type set forth in 48 CFR 2009.570-3(b). (a) If the representation, as completed, indicates that situations or relationships of the type set forth in 48 CFR 2009.570...

48 CFR 2052.209-71 - Contractor organizational conflicts of interest (representation).

Code of Federal Regulations, 2011 CFR

2011-10-01

... System NUCLEAR REGULATORY COMMISSION CLAUSES AND FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Text... / / involve situations or relationships of the type set forth in 48 CFR 2009.570-3(b). (a) If the representation, as completed, indicates that situations or relationships of the type set forth in 48 CFR 2009.570...

48 CFR 2052.209-71 - Contractor organizational conflicts of interest (representation).

Code of Federal Regulations, 2013 CFR

2013-10-01

... System NUCLEAR REGULATORY COMMISSION CLAUSES AND FORMS SOLICITATION PROVISIONS AND CONTRACT CLAUSES Text... / / involve situations or relationships of the type set forth in 48 CFR 2009.570-3(b). (a) If the representation, as completed, indicates that situations or relationships of the type set forth in 48 CFR 2009.570...

Classification of chemical substances, reactions, and interactions: The effect of expertise

NASA Astrophysics Data System (ADS)

Stains, Marilyne Nicole Olivia

2007-12-01

This project explored the strategies that undergraduate and graduate chemistry students engaged in when solving classification tasks involving microscopic (particulate) representations of chemical substances and microscopic and symbolic representations of different chemical reactions. We were specifically interested in characterizing the basic features to which students pay attention while classifying, identifying the patterns of reasoning that they follow, and comparing the performance of students with different levels of preparation in the discipline. In general, our results suggest that advanced levels of expertise in chemical classification do not necessarily evolve in a linear and continuous way with academic training. Novice students had a tendency to reduce the cognitive demand of the task and rely on common-sense reasoning; they had difficulties differentiating concepts (conceptual undifferentiation) and based their classification decisions on only one variable (reduction). These ways of thinking lead them to consider extraneous features, pay more attention to explicit or surface features than implicit features and to overlook important and relevant features. However, unfamiliar levels of representations (microscopic level) seemed to trigger deeper and more meaningful thinking processes. On the other hand, expert students classified entities using a specific set of rules that they applied throughout the classification tasks. They considered a larger variety of implicit features and the unfamiliarity with the microscopic level of representation did not affect their reasoning processes. Consequently, novices created numerous small groups, few of them being chemically meaningful, while experts created few but large chemically meaningful groups. Novices also had difficulties correctly classifying entities in chemically meaningful groups. Finally, expert chemists in our study used classification schemes that are not necessarily traditionally taught in classroom chemistry (e.g. the structure of substances is more relevant to them than their composition when classifying substances as compounds or elements). This result suggests that practice in the field may develop different types of knowledge framework than those usually presented in chemistry textbooks.

Towards an Effective Theory of Reformulation. Part 1; Semantics

NASA Technical Reports Server (NTRS)

Benjamin, D. Paul

1992-01-01

This paper describes an investigation into the structure of representations of sets of actions, utilizing semigroup theory. The goals of this project are twofold: to shed light on the relationship between tasks and representations, leading to a classification of tasks according to the representations they admit; and to develop techniques for automatically transforming representations so as to improve problem-solving performance. A method is demonstrated for automatically generating serial algorithms for representations whose actions form a finite group. This method is then extended to representations whose actions form a finite inverse semigroup.

Neural networks for data mining electronic text collections

NASA Astrophysics Data System (ADS)

Walker, Nicholas; Truman, Gregory

1997-04-01

The use of neural networks in information retrieval and text analysis has primarily suffered from the issues of adequate document representation, the ability to scale to very large collections, dynamism in the face of new information and the practical difficulties of basing the design on the use of supervised training sets. Perhaps the most important approach to begin solving these problems is the use of `intermediate entities' which reduce the dimensionality of document representations and the size of documents collections to manageable levels coupled with the use of unsupervised neural network paradigms. This paper describes the issues, a fully configured neural network-based text analysis system--dataHARVEST--aimed at data mining text collections which begins this process, along with the remaining difficulties and potential ways forward.

Mental Imagery: Functional Mechanisms and Clinical Applications

PubMed Central

Pearson, Joel; Naselaris, Thomas; Holmes, Emily A.; Kosslyn, Stephen M.

2015-01-01

Mental imagery research has weathered both disbelief of the phenomenon and inherent methodological limitations. Here we review recent behavioral, brain imaging, and clinical research that has reshaped our understanding of mental imagery. Research supports the claim that visual mental imagery is a depictive internal representation that functions like a weak form of perception. Brain imaging work has demonstrated that neural representations of mental and perceptual images resemble one another as early as the primary visual cortex (V1). Activity patterns in V1 encode mental images and perceptual images via a common set of low-level depictive visual features. Recent translational and clinical research reveals the pivotal role that imagery plays in many mental disorders and suggests how clinicians can utilize imagery in treatment. PMID:26412097

The contents of visual working memory reduce uncertainty during visual search.

PubMed

Cosman, Joshua D; Vecera, Shaun P

2011-05-01

Information held in visual working memory (VWM) influences the allocation of attention during visual search, with targets matching the contents of VWM receiving processing benefits over those that do not. Such an effect could arise from multiple mechanisms: First, it is possible that the contents of working memory enhance the perceptual representation of the target. Alternatively, it is possible that when a target is presented among distractor items, the contents of working memory operate postperceptually to reduce uncertainty about the location of the target. In both cases, a match between the contents of VWM and the target should lead to facilitated processing. However, each effect makes distinct predictions regarding set-size manipulations; whereas perceptual enhancement accounts predict processing benefits regardless of set size, uncertainty reduction accounts predict benefits only with set sizes larger than 1, when there is uncertainty regarding the target location. In the present study, in which briefly presented, masked targets were presented in isolation, there was a negligible effect of the information held in VWM on target discrimination. However, in displays containing multiple masked items, information held in VWM strongly affected target discrimination. These results argue that working memory representations act at a postperceptual level to reduce uncertainty during visual search.

Structure and energetics of Cr(CO)6 and Cr(CO)5

NASA Technical Reports Server (NTRS)

Barnes, Leslie A.; Liu, Bowen; Lindh, Roland

1993-01-01

The geometric structures and energetics of Cr(CO)6 and Cr(CO)5 are determined at the modified coupled-pair functional, single and double excitation coupled-cluster (CCSD), and CCSD(T) levels of theory. For Cr(CO)6, the structure and force constants for the totally symmetric representation are in good agreement with experimental data once basis set constants are taken into account. In the largest basis set at the CCSD(T) level of theory, the total binding energy of CR(CO)6 is estimated at around 140 kcal/mol, or about 86 percent of the experimental value. In contrast, the first bond energy of Cr(CO)6 is very well described at the CCSD(T) level of theory, with the best estimated value of 38 kcal/mol being within the experimental uncertainty.

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques

PubMed Central

2014-01-01

Background Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. Results We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. Conclusions SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats. PMID:25093070

SEE: structured representation of scientific evidence in the biomedical domain using Semantic Web techniques.

PubMed

Bölling, Christian; Weidlich, Michael; Holzhütter, Hermann-Georg

2014-01-01

Accounts of evidence are vital to evaluate and reproduce scientific findings and integrate data on an informed basis. Currently, such accounts are often inadequate, unstandardized and inaccessible for computational knowledge engineering even though computational technologies, among them those of the semantic web, are ever more employed to represent, disseminate and integrate biomedical data and knowledge. We present SEE (Semantic EvidencE), an RDF/OWL based approach for detailed representation of evidence in terms of the argumentative structure of the supporting background for claims even in complex settings. We derive design principles and identify minimal components for the representation of evidence. We specify the Reasoning and Discourse Ontology (RDO), an OWL representation of the model of scientific claims, their subjects, their provenance and their argumentative relations underlying the SEE approach. We demonstrate the application of SEE and illustrate its design patterns in a case study by providing an expressive account of the evidence for certain claims regarding the isolation of the enzyme glutamine synthetase. SEE is suited to provide coherent and computationally accessible representations of evidence-related information such as the materials, methods, assumptions, reasoning and information sources used to establish a scientific finding by adopting a consistently claim-based perspective on scientific results and their evidence. SEE allows for extensible evidence representations, in which the level of detail can be adjusted and which can be extended as needed. It supports representation of arbitrary many consecutive layers of interpretation and attribution and different evaluations of the same data. SEE and its underlying model could be a valuable component in a variety of use cases that require careful representation or examination of evidence for data presented on the semantic web or in other formats.

Mental Models in Expert Physics Reasoning.

ERIC Educational Resources Information Center

Roschelle, Jeremy; Greeno, James G.

Proposed is a relational framework for characterizing experienced physicists' representations of physics problem situations and the process of constructing these representations. A representation includes a coherent set of relations among: (1) a mental model of the objects in the situation, along with their relevant properties and relations; (2) a…

Behavioral model of visual perception and recognition

NASA Astrophysics Data System (ADS)

Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

1993-09-01

In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and successive verification of the expected sets of features (stored in Sensory Memory). The model shows the ability of recognition of complex objects (such as faces) in gray-level images invariant with respect to shift, rotation, and scale.

A unified tensor level set for image segmentation.

PubMed

Wang, Bin; Gao, Xinbo; Tao, Dacheng; Li, Xuelong

2010-06-01

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt- and pepper-type noise. Second, considering the local geometrical features, e.g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

Rough Set Approach to Incomplete Multiscale Information System

PubMed Central

Yang, Xibei; Qi, Yong; Yu, Dongjun; Yu, Hualong; Song, Xiaoning; Yang, Jingyu

2014-01-01

Multiscale information system is a new knowledge representation system for expressing the knowledge with different levels of granulations. In this paper, by considering the unknown values, which can be seen everywhere in real world applications, the incomplete multiscale information system is firstly investigated. The descriptor technique is employed to construct rough sets at different scales for analyzing the hierarchically structured data. The problem of unravelling decision rules at different scales is also addressed. Finally, the reduct descriptors are formulated to simplify decision rules, which can be derived from different scales. Some numerical examples are employed to substantiate the conceptual arguments. PMID:25276852

Bessel functions in mass action modeling of memories and remembrances

NASA Astrophysics Data System (ADS)

Freeman, Walter J.; Capolupo, Antonio; Kozma, Robert; Olivares del Campo, Andrés; Vitiello, Giuseppe

2015-10-01

Data from experimental observations of a class of neurological processes (Freeman K-sets) present functional distribution reproducing Bessel function behavior. We model such processes with couples of damped/amplified oscillators which provide time dependent representation of Bessel equation. The root loci of poles and zeros conform to solutions of K-sets. Some light is shed on the problem of filling the gap between the cellular level dynamics and the brain functional activity. Breakdown of time-reversal symmetry is related with the cortex thermodynamic features. This provides a possible mechanism to deduce lifetime of recorded memory.

Developing PFC representations using reinforcement learning.

PubMed

Reynolds, Jeremy R; O'Reilly, Randall C

2009-12-01

From both functional and biological considerations, it is widely believed that action production, planning, and goal-oriented behaviors supported by the frontal cortex are organized hierarchically [Fuster (1991); Koechlin, E., Ody, C., & Kouneiher, F. (2003). Neuroscience: The architecture of cognitive control in the human prefrontal cortex. Science, 424, 1181-1184; Miller, G. A., Galanter, E., & Pribram, K. H. (1960). Plans and the structure of behavior. New York: Holt]. However, the nature of the different levels of the hierarchy remains unclear, and little attention has been paid to the origins of such a hierarchy. We address these issues through biologically-inspired computational models that develop representations through reinforcement learning. We explore several different factors in these models that might plausibly give rise to a hierarchical organization of representations within the PFC, including an initial connectivity hierarchy within PFC, a hierarchical set of connections between PFC and subcortical structures controlling it, and differential synaptic plasticity schedules. Simulation results indicate that architectural constraints contribute to the segregation of different types of representations, and that this segregation facilitates learning. These findings are consistent with the idea that there is a functional hierarchy in PFC, as captured in our earlier computational models of PFC function and a growing body of empirical data.

Learning with Multiple Representations: Extending Multimedia Learning beyond the Lab

ERIC Educational Resources Information Center

Eilam, Billie; Poyas, Yael

2008-01-01

The present study extended multimedia learning principles beyond the lab to an ecologically valid setting (homework). Eighteen information cards were used to perform three homework tasks. The control group students learned from single representation (SR) cards that presented all information as printed text. The multiple representation (MR) group…

Uncovering Mental Representations with Markov Chain Monte Carlo

ERIC Educational Resources Information Center

Sanborn, Adam N.; Griffiths, Thomas L.; Shiffrin, Richard M.

2010-01-01

A key challenge for cognitive psychology is the investigation of mental representations, such as object categories, subjective probabilities, choice utilities, and memory traces. In many cases, these representations can be expressed as a non-negative function defined over a set of objects. We present a behavioral method for estimating these…

All Numbers Are Not Equal: An Electrophysiological Investigation of Small and Large Number Representations

ERIC Educational Resources Information Center

Hyde, Daniel C.; Spelke, Elizabeth S.

2009-01-01

Behavioral and brain imaging research indicates that human infants, humans adults, and many nonhuman animals represent large nonsymbolic numbers approximately, discriminating between sets with a ratio limit on accuracy. Some behavioral evidence, especially with human infants, suggests that these representations differ from representations of small…

The neural correlates of morphological complexity processing: Detecting structure in pseudowords.

PubMed

Schuster, Swetlana; Scharinger, Mathias; Brooks, Colin; Lahiri, Aditi; Hartwigsen, Gesa

2018-06-01

Morphological complexity is a highly debated issue in visual word recognition. Previous neuroimaging studies have shown that speakers are sensitive to degrees of morphological complexity. Two-step derived complex words (bridging through bridge N  > bridge V  > bridging) led to more enhanced activation in the left inferior frontal gyrus than their 1-step derived counterparts (running through run V  > running). However, it remains unclear whether sensitivity to degrees of morphological complexity extends to pseudowords. If this were the case, it would indicate that abstract knowledge of morphological structure is independent of lexicality. We addressed this question by investigating the processing of two sets of pseudowords in German. Both sets contained morphologically viable two-step derived pseudowords differing in the number of derivational steps required to access an existing lexical representation and therefore the degree of structural analysis expected during processing. Using a 2 × 2 factorial design, we found lexicality effects to be distinct from processing signatures relating to structural analysis in pseudowords. Semantically-driven processes such as lexical search showed a more frontal distribution while combinatorial processes related to structural analysis engaged more parietal parts of the network. Specifically, more complex pseudowords showed increased activation in parietal regions (right superior parietal lobe and left precuneus) relative to pseudowords that required less structural analysis to arrive at an existing lexical representation. As the two sets were matched on cohort size and surface form, these results highlight the role of internal levels of morphological structure even in forms that do not possess a lexical representation. © 2018 Wiley Periodicals, Inc.

Set size, individuation, and attention to shape

PubMed Central

Cantrell, Lisa; Smith, Linda B.

2013-01-01

Much research has demonstrated a shape bias in categorizing and naming solid objects. This research has shown that when an entity is conceptualized as an individual object, adults and children attend to the object’s shape. Separate research in the domain of numerical cognition suggest that there are distinct processes for quantifying small and large sets of discrete items. This research shows that small set discrimination, comparison, and apprehension is often precise for 1–3 and sometimes 4 items; however, large numerosity representation is imprecise. Results from three experiments suggest a link between the processes for small and large number representation and the shape bias in a forced choice categorization task using naming and non-naming procedures. Experiment 1 showed that adults generalized a newly learned name for an object to new instances of the same shape only when those instances were presented in sets of less than 3 or 4. Experiment 2 showed that preschool children who were monolingual speakers of three different languages were also influenced by set size when categorizing objects in sets. Experiment 3 extended these results and showed the same effect in a non-naming task and when the novel noun was presented in a count-noun syntax frame. The results are discussed in terms of a relation between the precision of object representation and the precision of small and large number representation. PMID:23167969

Set size, individuation, and attention to shape.

PubMed

Cantrell, Lisa; Smith, Linda B

2013-02-01

Much research has demonstrated a shape bias in categorizing and naming solid objects. This research has shown that when an entity is conceptualized as an individual object, adults and children attend to the object's shape. Separate research in the domain of numerical cognition suggest that there are distinct processes for quantifying small and large sets of discrete items. This research shows that small set discrimination, comparison, and apprehension is often precise for 1-3 and sometimes 4 items; however, large numerosity representation is imprecise. Results from three experiments suggest a link between the processes for small and large number representation and the shape bias in a forced choice categorization task using naming and non-naming procedures. Experiment 1 showed that adults generalized a newly learned name for an object to new instances of the same shape only when those instances were presented in sets of less than 3 or 4. Experiment 2 showed that preschool children who were monolingual speakers of three different languages were also influenced by set size when categorizing objects in sets. Experiment 3 extended these results and showed the same effect in a non-naming task and when the novel noun was presented in a count-noun syntax frame. The results are discussed in terms of a relation between the precision of object representation and the precision of small and large number representation. Copyright © 2012 Elsevier B.V. All rights reserved.

Weakly Supervised Dictionary Learning

NASA Astrophysics Data System (ADS)

You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

2018-05-01

We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

If you want to save, focus on the forest rather than on trees. The effects of shifts in levels of construal on saving decisions

PubMed Central

2017-01-01

Although financial decisions are expected to be rational, there is a growing body of experimental research indicating that small psychological changes in one’s mind-set in the actual decision-making moment might affect saving ratios. In this article, another type of change in one’s mind-set, which can influence saving decisions, is explored, namely the level of construal. Construal level is a key descriptor of people’s cognitive representations of targets, and is a way of characterising the mental mind-sets people use. Building on recent advances in the link between construal levels and intertemporal choices, the present research evaluates the effect of shifts in levels of construal in the very moment of decision making on people’s propensity to save money. It is suggested that triggering a high-level construal mind-set would influence individuals’ financial decisions and result in greater willingness to save than triggering a low-level construal mind-set. This assumption is supported by the findings: across three experiments, those with an abstract mind-set showed an increased willingness to save when compared to those with a concrete mind-set. The first experiment demonstrated that people in an abstract mind-set are more willing to delay financial gratification than those in a concrete mind-set. In the second and third experiments, those with an abstract mind-set showed an increased willingness to save when compared to those with a concrete mind-set. The research provides further evidence that mental states, which can be evoked by previous, unrelated tasks, such as level of cognitive abstraction, can influence everyday financial decisions. It, thus, highlights the role of situational factors that consumers may be not aware of, which still affect their savings decisions. PMID:28552943

Volta-Based Cells Materials Chemical Multiple Representation to Improve Ability of Student Representation

NASA Astrophysics Data System (ADS)

Helsy, I.; Maryamah; Farida, I.; Ramdhani, M. A.

2017-09-01

This study aimed to describe the application of teaching materials, analyze the increase in the ability of students to connect the three levels of representation and student responses after application of multiple representations based teaching materials chemistry. The method used quasi one-group pretest-posttest design to 71 students. The results showed the application of teaching materials carried 88% with very good category. A significant increase ability to connect the three levels of representation of students after the application of multiple representations based teaching materials chemistry with t-value > t-crit (11.402 > 1.991). Recapitulation N-gain pretest and posttest showed relatively similar for all groups is 0.6 criterion being achievement. Students gave a positive response to the application of multiple representations based teaching materials chemistry. Students agree teaching materials used in teaching chemistry (88%), and agrees teaching materials to provide convenience in connecting the three levels of representation (95%).

Ray Casting of Large Multi-Resolution Volume Datasets

NASA Astrophysics Data System (ADS)

Lux, C.; Fröhlich, B.

2009-04-01

High quality volume visualization through ray casting on graphics processing units (GPU) has become an important approach for many application domains. We present a GPU-based, multi-resolution ray casting technique for the interactive visualization of massive volume data sets commonly found in the oil and gas industry. Large volume data sets are represented as a multi-resolution hierarchy based on an octree data structure. The original volume data is decomposed into small bricks of a fixed size acting as the leaf nodes of the octree. These nodes are the highest resolution of the volume. Coarser resolutions are represented through inner nodes of the hierarchy which are generated by down sampling eight neighboring nodes on a finer level. Due to limited memory resources of current desktop workstations and graphics hardware only a limited working set of bricks can be locally maintained for a frame to be displayed. This working set is chosen to represent the whole volume at different local resolution levels depending on the current viewer position, transfer function and distinct areas of interest. During runtime the working set of bricks is maintained in CPU- and GPU memory and is adaptively updated by asynchronously fetching data from external sources like hard drives or a network. The CPU memory hereby acts as a secondary level cache for these sources from which the GPU representation is updated. Our volume ray casting algorithm is based on a 3D texture-atlas in GPU memory. This texture-atlas contains the complete working set of bricks of the current multi-resolution representation of the volume. This enables the volume ray casting algorithm to access the whole working set of bricks through only a single 3D texture. For traversing rays through the volume, information about the locations and resolution levels of visited bricks are required for correct compositing computations. We encode this information into a small 3D index texture which represents the current octree subdivision on its finest level and spatially organizes the bricked data. This approach allows us to render a bricked multi-resolution volume data set utilizing only a single rendering pass with no loss of compositing precision. In contrast most state-of-the art volume rendering systems handle the bricked data as individual 3D textures, which are rendered one at a time while the results are composited into a lower precision frame buffer. Furthermore, our method enables us to integrate advanced volume rendering techniques like empty-space skipping, adaptive sampling and preintegrated transfer functions in a very straightforward manner with virtually no extra costs. Our interactive volume ray tracing implementation allows high quality visualizations of massive volume data sets of tens of Gigabytes in size on standard desktop workstations.

Simulation of Heterogeneous Atom Probe Tip Shapes Evolution during Field Evaporation Using a Level Set Method and Different Evaporation Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Zhijie; Li, Dongsheng; Xu, Wei

2015-04-01

In atom probe tomography (APT), accurate reconstruction of the spatial positions of field evaporated ions from measured detector patterns depends upon a correct understanding of the dynamic tip shape evolution and evaporation laws of component atoms. Artifacts in APT reconstructions of heterogeneous materials can be attributed to the assumption of homogeneous evaporation of all the elements in the material in addition to the assumption of a steady state hemispherical dynamic tip shape evolution. A level set method based specimen shape evolution model is developed in this study to simulate the evaporation of synthetic layered-structured APT tips. The simulation results ofmore » the shape evolution by the level set model qualitatively agree with the finite element method and the literature data using the finite difference method. The asymmetric evolving shape predicted by the level set model demonstrates the complex evaporation behavior of heterogeneous tip and the interface curvature can potentially lead to the artifacts in the APT reconstruction of such materials. Compared with other APT simulation methods, the new method provides smoother interface representation with the aid of the intrinsic sub-grid accuracy. Two evaporation models (linear and exponential evaporation laws) are implemented in the level set simulations and the effect of evaporation laws on the tip shape evolution is also presented.« less

Unfixing Design Fixation: From Cause to Computer Simulation

ERIC Educational Resources Information Center

Dong, Andy; Sarkar, Somwrita

2011-01-01

This paper argues that design fixation, in part, entails fixation at the level of meta-representation, the representation of the relation between a representation and its reference. In this paper, we present a mathematical model that mimics the idea of how fixation can occur at the meta-representation level. In this model, new abstract concepts…

Visualization of diversity in large multivariate data sets.

PubMed

Pham, Tuan; Hess, Rob; Ju, Crystal; Zhang, Eugene; Metoyer, Ronald

2010-01-01

Understanding the diversity of a set of multivariate objects is an important problem in many domains, including ecology, college admissions, investing, machine learning, and others. However, to date, very little work has been done to help users achieve this kind of understanding. Visual representation is especially appealing for this task because it offers the potential to allow users to efficiently observe the objects of interest in a direct and holistic way. Thus, in this paper, we attempt to formalize the problem of visualizing the diversity of a large (more than 1000 objects), multivariate (more than 5 attributes) data set as one worth deeper investigation by the information visualization community. In doing so, we contribute a precise definition of diversity, a set of requirements for diversity visualizations based on this definition, and a formal user study design intended to evaluate the capacity of a visual representation for communicating diversity information. Our primary contribution, however, is a visual representation, called the Diversity Map, for visualizing diversity. An evaluation of the Diversity Map using our study design shows that users can judge elements of diversity consistently and as or more accurately than when using the only other representation specifically designed to visualize diversity.

Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity.

PubMed

Drew, Trafton; Boettcher, Sage E P; Wolfe, Jeremy M

2016-02-01

In "hybrid search" tasks, such as finding items on a grocery list, one must search the scene for targets while also searching the list in memory. How is the representation of a visual item compared with the representations of items in the memory set? Predominant theories would propose a role for visual working memory (VWM) either as the site of the comparison or as a conduit between visual and memory systems. In seven experiments, we loaded VWM in different ways and found little or no effect on hybrid search performance. However, the presence of a hybrid search task did reduce the measured capacity of VWM by a constant amount regardless of the size of the memory or visual sets. These data are broadly consistent with an account in which VWM must dedicate a fixed amount of its capacity to passing visual representations to long-term memory for comparison to the items in the memory set. The data cast doubt on models in which the search template resides in VWM or where memory set item representations are moved from LTM through VWM to earlier areas for comparison to visual items.

Foundations of children's numerical and mathematical skills: the roles of symbolic and nonsymbolic representations of numerical magnitude.

PubMed

Lyons, Ian M; Ansari, Daniel

2015-01-01

Numerical and mathematical skills are critical predictors of academic success. The last three decades have seen a substantial growth in our understanding of how the human mind and brain represent and process numbers. In particular, research has shown that we share with animals the ability to represent numerical magnitude (the total number of items in a set) and that preverbal infants can process numerical magnitude. Further research has shown that similar processing signatures characterize numerical magnitude processing across species and developmental time. These findings suggest that an approximate system for nonsymbolic (e.g., dot arrays) numerical magnitude representation serves as the basis for the acquisition of cultural, symbolic (e.g., Arabic numerals) representations of numerical magnitude. This chapter explores this hypothesis by reviewing studies that have examined the relation between individual differences in nonsymbolic numerical magnitude processing and symbolic math abilities (e.g., arithmetic). Furthermore, we examine the extent to which the available literature provides strong evidence for a link between symbolic and nonsymbolic representations of numerical magnitude at the behavioral and neural levels of analysis. We conclude that claims that symbolic number abilities are grounded in the approximate system for the nonsymbolic representation of numerical magnitude are not strongly supported by the available evidence. Alternative models and future research directions are discussed. © 2015 Elsevier Inc. All rights reserved.

MedRapid--medical community & business intelligence system.

PubMed

Finkeissen, E; Fuchs, H; Jakob, T; Wetter, T

2002-01-01

currently, it takes at least 6 months for researchers to communicate their results. This delay is caused (a) by partial lacks of machine support for both representation as well as communication and (b) by media breaks during the communication process. To make an integrated communication between researchers and practitioners possible, a general structure for medical content representation has been set up. The procedure for data entry and quality management has been generalized and implemented in a web-based authoring system. The MedRapid-system supports the medical experts in entering their knowledge into a database. Here, the level of detail is still below that of current medical guidelines representation. However, the symmetric structure for an area-wide medical knowledge representation is highly retrievable and thus can quickly be communicated into daily routine for the improvement of the treatment quality. In addition, other sources like journal articles and medical guidelines can be references within the MedRapid-system and thus be communicated into daily routine. The fundamental system for the representation of medical reference knowledge (from reference works/books) itself is not sufficient for the friction-less communication amongst medical staff. Rather, the process of (a) representing medical knowledge, (b) refereeing the represented knowledge, (c) communicating the represented knowledge, and (d) retrieving the represented knowledge has to be unified. MedRapid will soon support the whole process on one server system.

Progress with modeling activity landscapes in drug discovery.

PubMed

Vogt, Martin

2018-04-19

Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.

Where are my hands? Influence of limb posture on tactile extinction.

PubMed

Auclair, Laurent; Barra, Julien; Raibaut, Patrick

2012-05-01

Tactile localization on the skin involves both a somatotopic and a postural schema (body-schema) representation. The present study determines the extent to which body posture influences tactile perception in right-brain-damaged patients. In a first set of experiments, patients were asked to detect single tactile stimulation delivered to their left or right hands or to both hands simultaneously (double stimulation) in different arm postures. Only patients who had no difficulty localizing single and double tactile stimulations when their hands were placed in anatomic position were tested. Participant's hands were crossed, one over the other, and the tactile stimuli were delivered either to the hand (beyond the crossing point, Experiment 1) or to the forearm (before the crossing point, Experiment 2). In Experiment 3, the left hand was placed in the right hemispace and the right hand in the left hemispace without crossing over (opposite condition). In a second set of experiments, patients were asked to detect stimulation delivered to the forefinger. The fingers were crossed, one over the other at the level of the middle phalanx, and stimuli were delivered either beyond or before the crossing point. In all experimental conditions, control participants performed at ceiling. We observed a left-hand tactile extinction on double stimulation in the crossed condition. These results suggest that tactile stimuli can be encoded based on multiple specific body-part representations rather than on an integrated body-schema representation.

The Emergence of a Novel Representation from Action: Evidence from Preschoolers

ERIC Educational Resources Information Center

Boncoddo, Rebecca; Dixon, James A.; Kelley, Elizabeth

2010-01-01

Recent work in embodied cognition has proposed that representations and actions are inextricably linked. The current study examines a developmental account of this relationship. Specifically, we propose that children's actions are foundational for novel representations. Thirty-two preschoolers, aged 3.4 to 5.7 years, were asked to solve a set of…

A "Natural Experiment" in Childrearing Ecologies and Adolescents' Attachment and Separation Representations.

ERIC Educational Resources Information Center

Scharf, Miri

2001-01-01

Explored long-term effects of different childrearing contexts on attachment and separation representations of Israeli 16- to 18-year-olds. Found that adolescents raised in a kibbutz communal setting showed higher incidence of nonautonomous attachment representations and less competent coping with imagined separations than adolescents raised in a…

Kohn-Sham potentials from electron densities using a matrix representation within finite atomic orbital basis sets

NASA Astrophysics Data System (ADS)

Zhang, Xing; Carter, Emily A.

2018-01-01

We revisit the static response function-based Kohn-Sham (KS) inversion procedure for determining the KS effective potential that corresponds to a given target electron density within finite atomic orbital basis sets. Instead of expanding the potential in an auxiliary basis set, we directly update the potential in its matrix representation. Through numerical examples, we show that the reconstructed density rapidly converges to the target density. Preliminary results are presented to illustrate the possibility of obtaining a local potential in real space from the optimized potential in its matrix representation. We have further applied this matrix-based KS inversion approach to density functional embedding theory. A proof-of-concept study of a solvated proton transfer reaction demonstrates the method's promise.

Multigrid one shot methods for optimal control problems: Infinite dimensional control

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

The multigrid one shot method for optimal control problems, governed by elliptic systems, is introduced for the infinite dimensional control space. ln this case, the control variable is a function whose discrete representation involves_an increasing number of variables with grid refinement. The minimization algorithm uses Lagrange multipliers to calculate sensitivity gradients. A preconditioned gradient descent algorithm is accelerated by a set of coarse grids. It optimizes for different scales in the representation of the control variable on different discretization levels. An analysis which reduces the problem to the boundary is introduced. It is used to approximate the two level asymptotic convergence rate, to determine the amplitude of the minimization steps, and the choice of a high pass filter to be used when necessary. The effectiveness of the method is demonstrated on a series of test problems. The new method enables the solutions of optimal control problems at the same cost of solving the corresponding analysis problems just a few times.

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares

PubMed Central

Jozwik, Kamila M.; Kriegeskorte, Nikolaus; Mur, Marieke

2016-01-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as “human”, “mammal”, and “animal”). The feature-based model includes both object parts (such as “eye”, “tail”, and “handle”) and other descriptive features (such as “circular”, “green”, and “stubbly”). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation. Similarity judgments contain additional categorical variance that is not explained by visual features, reflecting a higher-level more purely semantic representation. PMID:26493748

Visual features as stepping stones toward semantics: Explaining object similarity in IT and perception with non-negative least squares.

PubMed

Jozwik, Kamila M; Kriegeskorte, Nikolaus; Mur, Marieke

2016-03-01

Object similarity, in brain representations and conscious perception, must reflect a combination of the visual appearance of the objects on the one hand and the categories the objects belong to on the other. Indeed, visual object features and category membership have each been shown to contribute to the object representation in human inferior temporal (IT) cortex, as well as to object-similarity judgments. However, the explanatory power of features and categories has not been directly compared. Here, we investigate whether the IT object representation and similarity judgments are best explained by a categorical or a feature-based model. We use rich models (>100 dimensions) generated by human observers for a set of 96 real-world object images. The categorical model consists of a hierarchically nested set of category labels (such as "human", "mammal", and "animal"). The feature-based model includes both object parts (such as "eye", "tail", and "handle") and other descriptive features (such as "circular", "green", and "stubbly"). We used non-negative least squares to fit the models to the brain representations (estimated from functional magnetic resonance imaging data) and to similarity judgments. Model performance was estimated on held-out images not used in fitting. Both models explained significant variance in IT and the amounts explained were not significantly different. The combined model did not explain significant additional IT variance, suggesting that it is the shared model variance (features correlated with categories, categories correlated with features) that best explains IT. The similarity judgments were almost fully explained by the categorical model, which explained significantly more variance than the feature-based model. The combined model did not explain significant additional variance in the similarity judgments. Our findings suggest that IT uses features that help to distinguish categories as stepping stones toward a semantic representation. Similarity judgments contain additional categorical variance that is not explained by visual features, reflecting a higher-level more purely semantic representation. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

What do we mean by prediction in language comprehension?

PubMed Central

Kuperberg, Gina R.; Jaeger, T. Florian

2016-01-01

We consider several key aspects of prediction in language comprehension: its computational nature, the representational level(s) at which we predict, whether we use higher level representations to predictively pre-activate lower level representations, and whether we ‘commit’ in any way to our predictions, beyond pre-activation. We argue that the bulk of behavioral and neural evidence suggests that we predict probabilistically and at multiple levels and grains of representation. We also argue that we can, in principle, use higher level inferences to predictively pre-activate information at multiple lower representational levels. We also suggest that the degree and level of predictive pre-activation might be a function of the expected utility of prediction, which, in turn, may depend on comprehenders’ goals and their estimates of the relative reliability of their prior knowledge and the bottom-up input. Finally, we argue that all these properties of language understanding can be naturally explained and productively explored within a multi-representational hierarchical actively generative architecture whose goal is to infer the message intended by the producer, and in which predictions play a crucial role in explaining the bottom-up input. PMID:27135040

Vessel Segmentation and Blood Flow Simulation Using Level-Sets and Embedded Boundary Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Deschamps, T; Schwartz, P; Trebotich, D

In this article we address the problem of blood flow simulation in realistic vascular objects. The anatomical surfaces are extracted by means of Level-Sets methods that accurately model the complex and varying surfaces of pathological objects such as aneurysms and stenoses. The surfaces obtained are defined at the sub-pixel level where they intersect the Cartesian grid of the image domain. It is therefore straightforward to construct embedded boundary representations of these objects on the same grid, for which recent work has enabled discretization of the Navier-Stokes equations for incompressible fluids. While most classical techniques require construction of a structured meshmore » that approximates the surface in order to extrapolate a 3D finite-element gridding of the whole volume, our method directly simulates the blood-flow inside the extracted surface without losing any complicated details and without building additional grids.« less

A multi-level solution algorithm for steady-state Markov chains

NASA Technical Reports Server (NTRS)

Horton, Graham; Leutenegger, Scott T.

1993-01-01

A new iterative algorithm, the multi-level algorithm, for the numerical solution of steady state Markov chains is presented. The method utilizes a set of recursively coarsened representations of the original system to achieve accelerated convergence. It is motivated by multigrid methods, which are widely used for fast solution of partial differential equations. Initial results of numerical experiments are reported, showing significant reductions in computation time, often an order of magnitude or more, relative to the Gauss-Seidel and optimal SOR algorithms for a variety of test problems. The multi-level method is compared and contrasted with the iterative aggregation-disaggregation algorithm of Takahashi.

Learning in Stochastic Bit Stream Neural Networks.

PubMed

van Daalen, Max; Shawe-Taylor, John; Zhao, Jieyu

1996-08-01

This paper presents learning techniques for a novel feedforward stochastic neural network. The model uses stochastic weights and the "bit stream" data representation. It has a clean analysable functionality and is very attractive with its great potential to be implemented in hardware using standard digital VLSI technology. The design allows simulation at three different levels and learning techniques are described for each level. The lowest level corresponds to on-chip learning. Simulation results on three benchmark MONK's problems and handwritten digit recognition with a clean set of 500 16 x 16 pixel digits demonstrate that the new model is powerful enough for the real world applications. Copyright 1996 Elsevier Science Ltd

Characterizing representational learning: A combined simulation and tutorial on perturbation theory

NASA Astrophysics Data System (ADS)

Kohnle, Antje; Passante, Gina

2017-12-01

Analyzing, constructing, and translating between graphical, pictorial, and mathematical representations of physics ideas and reasoning flexibly through them ("representational competence") is a key characteristic of expertise in physics but is a challenge for learners to develop. Interactive computer simulations and University of Washington style tutorials both have affordances to support representational learning. This article describes work to characterize students' spontaneous use of representations before and after working with a combined simulation and tutorial on first-order energy corrections in the context of quantum-mechanical time-independent perturbation theory. Data were collected from two institutions using pre-, mid-, and post-tests to assess short- and long-term gains. A representational competence level framework was adapted to devise level descriptors for the assessment items. The results indicate an increase in the number of representations used by students and the consistency between them following the combined simulation tutorial. The distributions of representational competence levels suggest a shift from perceptual to semantic use of representations based on their underlying meaning. In terms of activity design, this study illustrates the need to support students in making sense of the representations shown in a simulation and in learning to choose the most appropriate representation for a given task. In terms of characterizing representational abilities, this study illustrates the usefulness of a framework focusing on perceptual, syntactic, and semantic use of representations.

Fractals, Fuzzy Sets And Image Representation

NASA Astrophysics Data System (ADS)

Dodds, D. R.

1988-10-01

This paper addresses some uses of fractals, fuzzy sets and image representation as it pertains to robotic grip planning and autonomous vehicle navigation AVN. The robot/vehicle is assumed to be equipped with multimodal sensors including ultrashort pulse imaging laser rangefinder. With a temporal resolution of 50 femtoseconds a time of flight laser rangefinder can resolve distances within approximately half an inch or 1.25 centimeters. (Fujimoto88)

Visualization of a Large Set of Hydrogen Atomic Orbital Contours Using New and Expanded Sets of Parametric Equations

ERIC Educational Resources Information Center

Rhile, Ian J.

2014-01-01

Atomic orbitals are a theme throughout the undergraduate chemistry curriculum, and visualizing them has been a theme in this journal. Contour plots as isosurfaces or contour lines in a plane are the most familiar representations of the hydrogen wave functions. In these representations, a surface of a fixed value of the wave function ? is plotted…

75 FR 16843 - Prohibited Transaction Exemptions Grant of Individual Exemptions Involving: 2010-09, Ivy Asset...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-02

... Composite International Fund, Ltd. (the DE Shaw Fund), a hedge fund organized outside the United States, to... applicant has requested a change in representation 1, as set forth in the SFR on page 58997, column 2, lines... in the third paragraph of representation 3, as set forth in the SFR on page 58997, column 3, lines 7...

Enhancing biomedical text summarization using semantic relation extraction.

PubMed

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization.

77 FR 59995 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-01

... fair representation of its members in the selection of its directors and administration of its affairs... boards thus are sometimes referred to as ``fair representation directors.'' NYSE Arca Rule 3.2 sets forth.... 78f(b)(3). The Exchange proposes to expand the eligibility for fair representation directors to...

Calculus Students' Representation Use in Group-Work and Individual Settings

ERIC Educational Resources Information Center

Zazkis, Dov

2013-01-01

The study of student representation use and specifically the distinction between analytic and visual representations has fueled a long line of mathematics education literature that began more than 35 years ago. This literature can be partitioned into two bodies of work, one that is primarily cognitive and one that is primarily social. In spite of…

A survey on the design of multiprocessing systems for artificial intelligence applications

NASA Technical Reports Server (NTRS)

Wah, Benjamin W.; Li, Guo Jie

1989-01-01

Some issues in designing computers for artificial intelligence (AI) processing are discussed. These issues are divided into three levels: the representation level, the control level, and the processor level. The representation level deals with the knowledge and methods used to solve the problem and the means to represent it. The control level is concerned with the detection of dependencies and parallelism in the algorithmic and program representations of the problem, and with the synchronization and sheduling of concurrent tasks. The processor level addresses the hardware and architectural components needed to evaluate the algorithmic and program representations. Solutions for the problems of each level are illustrated by a number of representative systems. Design decisions in existing projects on AI computers are classed into top-down, bottom-up, and middle-out approaches.

Neural Representation. A Survey-Based Analysis of the Notion

PubMed Central

Vilarroya, Oscar

2017-01-01

The word representation (as in “neural representation”), and many of its related terms, such as to represent, representational and the like, play a central explanatory role in neuroscience literature. For instance, in “place cell” literature, place cells are extensively associated with their role in “the representation of space.” In spite of its extended use, we still lack a clear, universal and widely accepted view on what it means for a nervous system to represent something, on what makes a neural activity a representation, and on what is re-presented. The lack of a theoretical foundation and definition of the notion has not hindered actual research. My aim here is to identify how active scientists use the notion of neural representation, and eventually to list a set of criteria, based on actual use, that can help in distinguishing between genuine or non-genuine neural-representation candidates. In order to attain this objective, I present first the results of a survey of authors within two domains, place-cell and multivariate pattern analysis (MVPA) research. Based on the authors’ replies, and on a review of neuroscientific research, I outline a set of common properties that an account of neural representation seems to require. I then apply these properties to assess the use of the notion in two domains of the survey, place-cell and MVPA studies. I conclude by exploring a shift in the notion of representation suggested by recent literature. PMID:28900406

Two-tier tissue decomposition for histopathological image representation and classification.

PubMed

Gultekin, Tunc; Koyuncu, Can Fahrettin; Sokmensuer, Cenk; Gunduz-Demir, Cigdem

2015-01-01

In digital pathology, devising effective image representations is crucial to design robust automated diagnosis systems. To this end, many studies have proposed to develop object-based representations, instead of directly using image pixels, since a histopathological image may contain a considerable amount of noise typically at the pixel-level. These previous studies mostly employ color information to define their objects, which approximately represent histological tissue components in an image, and then use the spatial distribution of these objects for image representation and classification. Thus, object definition has a direct effect on the way of representing the image, which in turn affects classification accuracies. In this paper, our aim is to design a classification system for histopathological images. Towards this end, we present a new model for effective representation of these images that will be used by the classification system. The contributions of this model are twofold. First, it introduces a new two-tier tissue decomposition method for defining a set of multityped objects in an image. Different than the previous studies, these objects are defined combining texture, shape, and size information and they may correspond to individual histological tissue components as well as local tissue subregions of different characteristics. As its second contribution, it defines a new metric, which we call dominant blob scale, to characterize the shape and size of an object with a single scalar value. Our experiments on colon tissue images reveal that this new object definition and characterization provides distinguishing representation of normal and cancerous histopathological images, which is effective to obtain more accurate classification results compared to its counterparts.

Nursing Minimum Data Set Based on EHR Archetypes Approach.

PubMed

Spigolon, Dandara N; Moro, Cláudia M C

2012-01-01

The establishment of a Nursing Minimum Data Set (NMDS) can facilitate the use of health information systems. The adoption of these sets and represent them based on archetypes are a way of developing and support health systems. The objective of this paper is to describe the definition of a minimum data set for nursing in endometriosis represent with archetypes. The study was divided into two steps: Defining the Nursing Minimum Data Set to endometriosis, and Development archetypes related to the NMDS. The nursing data set to endometriosis was represented in the form of archetype, using the whole perception of the evaluation item, organs and senses. This form of representation is an important tool for semantic interoperability and knowledge representation for health information systems.

Nursing Minimum Data Set Based on EHR Archetypes Approach

PubMed Central

Spigolon, Dandara N.; Moro, Cláudia M.C.

2012-01-01

The establishment of a Nursing Minimum Data Set (NMDS) can facilitate the use of health information systems. The adoption of these sets and represent them based on archetypes are a way of developing and support health systems. The objective of this paper is to describe the definition of a minimum data set for nursing in endometriosis represent with archetypes. The study was divided into two steps: Defining the Nursing Minimum Data Set to endometriosis, and Development archetypes related to the NMDS. The nursing data set to endometriosis was represented in the form of archetype, using the whole perception of the evaluation item, organs and senses. This form of representation is an important tool for semantic interoperability and knowledge representation for health information systems. PMID:24199126

Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods.

PubMed

Qu, Kaiyang; Han, Ke; Wu, Song; Wang, Guohua; Wei, Leyi

2017-09-22

DNA-binding proteins play vital roles in cellular processes, such as DNA packaging, replication, transcription, regulation, and other DNA-associated activities. The current main prediction method is based on machine learning, and its accuracy mainly depends on the features extraction method. Therefore, using an efficient feature representation method is important to enhance the classification accuracy. However, existing feature representation methods cannot efficiently distinguish DNA-binding proteins from non-DNA-binding proteins. In this paper, a multi-feature representation method, which combines three feature representation methods, namely, K-Skip-N-Grams, Information theory, and Sequential and structural features (SSF), is used to represent the protein sequences and improve feature representation ability. In addition, the classifier is a support vector machine. The mixed-feature representation method is evaluated using 10-fold cross-validation and a test set. Feature vectors, which are obtained from a combination of three feature extractions, show the best performance in 10-fold cross-validation both under non-dimensional reduction and dimensional reduction by max-relevance-max-distance. Moreover, the reduced mixed feature method performs better than the non-reduced mixed feature technique. The feature vectors, which are a combination of SSF and K-Skip-N-Grams, show the best performance in the test set. Among these methods, mixed features exhibit superiority over the single features.

Ab Initio and Analytic Intermolecular Potentials for Ar-CF₄

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vayner, Grigoriy; Alexeev, Yuri; Wang, Jiangping

2006-03-09

Ab initio calculations at the CCSD(T) level of theory are performed to characterize the Ar + CF ₄ intermolecular potential. Extensive calculations, with and without a correction for basis set superposition error (BSSE), are performed with the cc-pVTZ basis set. Additional calculations are performed with other correlation consistent (cc) basis sets to extrapolate the Ar---CF₄potential energy minimum to the complete basis set (CBS) limit. Both the size of the basis set and BSSE have substantial effects on the Ar + CF₄ potential. Calculations with the cc-pVTZ basis set and without a BSSE correction, appear to give a good representation ofmore » the potential at the CBS limit and with a BSSE correction. In addition, MP2 theory is found to give potential energies in very good agreement with those determined by the much higher level CCSD(T) theory. Two analytic potential energy functions were determined for Ar + CF₄by fitting the cc-pVTZ calculations both with and without a BSSE correction. These analytic functions were written as a sum of two body potentials and excellent fits to the ab initio potentials were obtained by representing each two body interaction as a Buckingham potential.« less

On the detection of pornographic digital images

NASA Astrophysics Data System (ADS)

Schettini, Raimondo; Brambilla, Carla; Cusano, Claudio; Ciocca, Gianluigi

2003-06-01

The paper addresses the problem of distinguishing between pornographic and non-pornographic photographs, for the design of semantic filters for the web. Both, decision forests of trees built according to CART (Classification And Regression Trees) methodology and Support Vectors Machines (SVM), have been used to perform the classification. The photographs are described by a set of low-level features, features that can be automatically computed simply on gray-level and color representation of the image. The database used in our experiments contained 1500 photographs, 750 of which labeled as pornographic on the basis of the independent judgement of several viewers.

The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.

PubMed

Djurfeldt, Mikael

2012-07-01

The connection-set algebra (CSA) is a novel and general formalism for the description of connectivity in neuronal network models, from small-scale to large-scale structure. The algebra provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. CSA is expressive enough to describe a wide range of connection patterns, including multiple types of random and/or geometrically dependent connectivity, and can serve as a concise notation for network structure in scientific writing. CSA implementations allow for scalable and efficient representation of connectivity in parallel neuronal network simulators and could even allow for avoiding explicit representation of connections in computer memory. The expressiveness of CSA makes prototyping of network structure easy. A C+ + version of the algebra has been implemented and used in a large-scale neuronal network simulation (Djurfeldt et al., IBM J Res Dev 52(1/2):31-42, 2008b) and an implementation in Python has been publicly released.

Learning object-to-class kernels for scene classification.

PubMed

Zhang, Lei; Zhen, Xiantong; Shao, Ling

2014-08-01

High-level image representations have drawn increasing attention in visual recognition, e.g., scene classification, since the invention of the object bank. The object bank represents an image as a response map of a large number of pretrained object detectors and has achieved superior performance for visual recognition. In this paper, based on the object bank representation, we propose the object-to-class (O2C) distances to model scene images. In particular, four variants of O2C distances are presented, and with the O2C distances, we can represent the images using the object bank by lower-dimensional but more discriminative spaces, called distance spaces, which are spanned by the O2C distances. Due to the explicit computation of O2C distances based on the object bank, the obtained representations can possess more semantic meanings. To combine the discriminant ability of the O2C distances to all scene classes, we further propose to kernalize the distance representation for the final classification. We have conducted extensive experiments on four benchmark data sets, UIUC-Sports, Scene-15, MIT Indoor, and Caltech-101, which demonstrate that the proposed approaches can significantly improve the original object bank approach and achieve the state-of-the-art performance.

Character recognition using a neural network model with fuzzy representation

NASA Technical Reports Server (NTRS)

Tavakoli, Nassrin; Seniw, David

1992-01-01

The degree to which digital images are recognized correctly by computerized algorithms is highly dependent upon the representation and the classification processes. Fuzzy techniques play an important role in both processes. In this paper, the role of fuzzy representation and classification on the recognition of digital characters is investigated. An experimental Neural Network model with application to character recognition was developed. Through a set of experiments, the effect of fuzzy representation on the recognition accuracy of this model is presented.

An Analysis of Different Representations for Vectors and Planes in R[superscript 3]: Learning Challenges

ERIC Educational Resources Information Center

Sandoval, Ivonne; Possani, Edgar

2016-01-01

The purpose of this paper is to present an analysis of the difficulties faced by students when working with different representations of vectors, planes and their intersections in R[superscript 3]. Duval's theoretical framework on semiotic representations is used to design a set of evaluating activities, and later to analyze student work. The…

Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection.

PubMed

Wang, Haoran; Yuan, Chunfeng; Hu, Weiming; Ling, Haibin; Yang, Wankou; Sun, Changyin

2014-02-01

In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach.

Learning Midlevel Auditory Codes from Natural Sound Statistics.

PubMed

Młynarski, Wiktor; McDermott, Josh H

2018-03-01

Interaction with the world requires an organism to transform sensory signals into representations in which behaviorally meaningful properties of the environment are made explicit. These representations are derived through cascades of neuronal processing stages in which neurons at each stage recode the output of preceding stages. Explanations of sensory coding may thus involve understanding how low-level patterns are combined into more complex structures. To gain insight into such midlevel representations for sound, we designed a hierarchical generative model of natural sounds that learns combinations of spectrotemporal features from natural stimulus statistics. In the first layer, the model forms a sparse convolutional code of spectrograms using a dictionary of learned spectrotemporal kernels. To generalize from specific kernel activation patterns, the second layer encodes patterns of time-varying magnitude of multiple first-layer coefficients. When trained on corpora of speech and environmental sounds, some second-layer units learned to group similar spectrotemporal features. Others instantiate opponency between distinct sets of features. Such groupings might be instantiated by neurons in the auditory cortex, providing a hypothesis for midlevel neuronal computation.

Electrophysiological evidence for size invariance in masked picture repetition priming

PubMed Central

Eddy, Marianna D.; Holcomb, Phillip J.

2009-01-01

This experiment examined invariance in object representations through measuring event-related potentials (ERPs) to pictures in a masked repetition priming paradigm. Pairs of pictures were presented where the prime was either the same size or half the size of the target object and the target was either presented in a normal orientation or was a normal sized mirror reflection of the prime object. Previous masked repetition priming studies have found a cascade of priming effect sensitive to perceptual (N190/P190) and semantic (N400) properties of the stimulus. This experiment found that both early (N190/P190 effects) and later effects (N400) were invariant to size, whereas only the N190/P190 effect was invariant to mirror reflection. The combination of a small prime and a mirror reflected target led to no significant priming effects. Taken together, the results of this set of experiments suggests that object recognition, more specifically, activating an object representation, occurs in a hierarchical fashion where overlapping perceptual information between the prime and target is necessary, although not always sufficient, to activate a higher level semantic representation. PMID:19560248

The temporal evolution of conceptual object representations revealed through models of behavior, semantics and deep neural networks.

PubMed

Bankson, B B; Hebart, M N; Groen, I I A; Baker, C I

2018-05-17

Visual object representations are commonly thought to emerge rapidly, yet it has remained unclear to what extent early brain responses reflect purely low-level visual features of these objects and how strongly those features contribute to later categorical or conceptual representations. Here, we aimed to estimate a lower temporal bound for the emergence of conceptual representations by defining two criteria that characterize such representations: 1) conceptual object representations should generalize across different exemplars of the same object, and 2) these representations should reflect high-level behavioral judgments. To test these criteria, we compared magnetoencephalography (MEG) recordings between two groups of participants (n = 16 per group) exposed to different exemplar images of the same object concepts. Further, we disentangled low-level from high-level MEG responses by estimating the unique and shared contribution of models of behavioral judgments, semantics, and different layers of deep neural networks of visual object processing. We find that 1) both generalization across exemplars as well as generalization of object-related signals across time increase after 150 ms, peaking around 230 ms; 2) representations specific to behavioral judgments emerged rapidly, peaking around 160 ms. Collectively, these results suggest a lower bound for the emergence of conceptual object representations around 150 ms following stimulus onset. Copyright © 2018 Elsevier Inc. All rights reserved.

Shared neural circuits for mentalizing about the self and others.

PubMed

Lombardo, Michael V; Chakrabarti, Bhismadev; Bullmore, Edward T; Wheelwright, Sally J; Sadek, Susan A; Suckling, John; Baron-Cohen, Simon

2010-07-01

Although many examples exist for shared neural representations of self and other, it is unknown how such shared representations interact with the rest of the brain. Furthermore, do high-level inference-based shared mentalizing representations interact with lower level embodied/simulation-based shared representations? We used functional neuroimaging (fMRI) and a functional connectivity approach to assess these questions during high-level inference-based mentalizing. Shared mentalizing representations in ventromedial prefrontal cortex, posterior cingulate/precuneus, and temporo-parietal junction (TPJ) all exhibited identical functional connectivity patterns during mentalizing of both self and other. Connectivity patterns were distributed across low-level embodied neural systems such as the frontal operculum/ventral premotor cortex, the anterior insula, the primary sensorimotor cortex, and the presupplementary motor area. These results demonstrate that identical neural circuits are implementing processes involved in mentalizing of both self and other and that the nature of such processes may be the integration of low-level embodied processes within higher level inference-based mentalizing.

Meaning of life, representation of death, and their association with psychological distress.

PubMed

Testoni, Ines; Sansonetto, Giulia; Ronconi, Lucia; Rodelli, Maddalena; Baracco, Gloria; Grassi, Luigi

2017-08-09

This paper presents a two-phase cross-sectional study aimed at examining the possible mitigating role of perceived meaning of life and representation of death on psychological distress, anxiety, and depression. The first phase involved 219 healthy participants, while the second encompassed 30 cancer patients. Each participant completed the Personal Meaning Profile (PMP), the Testoni Death Representation Scale (TDRS), the Hospital Anxiety and Depression Scale (HADS), and the Distress Thermometer (DT). The primary analyses comprised (1) correlation analyses between the overall scores of each of the instruments and (2) path analysis to assess the indirect effect of the PMP on DT score through anxiety and depression as determined by the HADS. The path analysis showed that the PMP was inversely correlated with depression and anxiety, which, in turn, mediated the effect on distress. Inverse correlations were found between several dimensions of the PMP, the DT, and the HADS-Anxiety and HADS-Depression subscales, in both healthy participants and cancer patients. Religious orientation (faith in God) was related to a stronger sense of meaning in life and the ontological representation of death as a passage, rather than annihilation. Our findings support the hypothesis that participants who represent death as a passage and have a strong perception of the meaning of life tend to report lower levels of distress, anxiety, and depression. We recommend that perceived meaning of life and representation of death be more specifically examined in the cancer and palliative care settings.

One, two, three, four, nothing more: an investigation of the conceptual sources of the verbal counting principles.

PubMed

Le Corre, Mathieu; Carey, Susan

2007-11-01

Since the publication of [Gelman, R., & Gallistel, C. R. (1978). The child's understanding of number. Cambridge, MA: Harvard University Press.] seminal work on the development of verbal counting as a representation of number, the nature of the ontogenetic sources of the verbal counting principles has been intensely debated. The present experiments explore proposals according to which the verbal counting principles are acquired by mapping numerals in the count list onto systems of numerical representation for which there is evidence in infancy, namely, analog magnitudes, parallel individuation, and set-based quantification. By asking 3- and 4-year-olds to estimate the number of elements in sets without counting, we investigate whether the numerals that are assigned cardinal meaning as part of the acquisition process display the signatures of what we call "enriched parallel individuation" (which combines properties of parallel individuation and of set-based quantification) or analog magnitudes. Two experiments demonstrate that while "one" to "four" are mapped onto core representations of small sets prior to the acquisition of the counting principles, numerals beyond "four" are only mapped onto analog magnitudes about six months after the acquisition of the counting principles. Moreover, we show that children's numerical estimates of sets from 1 to 4 elements fail to show the signature of numeral use based on analog magnitudes - namely, scalar variability. We conclude that, while representations of small sets provided by parallel individuation, enriched by the resources of set-based quantification are recruited in the acquisition process to provide the first numerical meanings for "one" to "four", analog magnitudes play no role in this process.

Capuchin monkeys (Cebus apella) treat small and large numbers of items similarly during a relative quantity judgment task.

PubMed

Beran, Michael J; Parrish, Audrey E

2016-08-01

A key issue in understanding the evolutionary and developmental emergence of numerical cognition is to learn what mechanism(s) support perception and representation of quantitative information. Two such systems have been proposed, one for dealing with approximate representation of sets of items across an extended numerical range and another for highly precise representation of only small numbers of items. Evidence for the first system is abundant across species and in many tests with human adults and children, whereas the second system is primarily evident in research with children and in some tests with non-human animals. A recent paper (Choo & Franconeri, Psychonomic Bulletin & Review, 21, 93-99, 2014) with adult humans also reported "superprecise" representation of small sets of items in comparison to large sets of items, which would provide more support for the presence of a second system in human adults. We first presented capuchin monkeys with a test similar to that of Choo and Franconeri in which small or large sets with the same ratios had to be discriminated. We then presented the same monkeys with an expanded range of comparisons in the small number range (all comparisons of 1-9 items) and the large number range (all comparisons of 10-90 items in 10-item increments). Capuchin monkeys showed no increased precision for small over large sets in making these discriminations in either experiment. These data indicate a difference in the performance of monkeys to that of adult humans, and specifically that monkeys do not show improved discrimination performance for small sets relative to large sets when the relative numerical differences are held constant.

Learning semantic histopathological representation for basal cell carcinoma classification

NASA Astrophysics Data System (ADS)

Gutiérrez, Ricardo; Rueda, Andrea; Romero, Eduardo

2013-03-01

Diagnosis of a histopathology glass slide is a complex process that involves accurate recognition of several structures, their function in the tissue and their relation with other structures. The way in which the pathologist represents the image content and the relations between those objects yields a better and accurate diagnoses. Therefore, an appropriate semantic representation of the image content will be useful in several analysis tasks such as cancer classification, tissue retrieval and histopahological image analysis, among others. Nevertheless, to automatically recognize those structures and extract their inner semantic meaning are still very challenging tasks. In this paper we introduce a new semantic representation that allows to describe histopathological concepts suitable for classification. The approach herein identify local concepts using a dictionary learning approach, i.e., the algorithm learns the most representative atoms from a set of random sampled patches, and then models the spatial relations among them by counting the co-occurrence between atoms, while penalizing the spatial distance. The proposed approach was compared with a bag-of-features representation in a tissue classification task. For this purpose, 240 histological microscopical fields of view, 24 per tissue class, were collected. Those images fed a Support Vector Machine classifier per class, using 120 images as train set and the remaining ones for testing, maintaining the same proportion of each concept in the train and test sets. The obtained classification results, averaged from 100 random partitions of training and test sets, shows that our approach is more sensitive in average than the bag-of-features representation in almost 6%.

Operator algebra as an application of logarithmic representation of infinitesimal generators

NASA Astrophysics Data System (ADS)

Iwata, Yoritaka

2018-02-01

The operator algebra is introduced based on the framework of logarithmic representation of infinitesimal generators. In conclusion a set of generally-unbounded infinitesimal generators is characterized as a module over the Banach algebra.

A depictive neural model for the representation of motion verbs.

PubMed

Rao, Sunil; Aleksander, Igor

2011-11-01

In this paper, we present a depictive neural model for the representation of motion verb semantics in neural models of visual awareness. The problem of modelling motion verb representation is shown to be one of function application, mapping a set of given input variables defining the moving object and the path of motion to a defined output outcome in the motion recognition context. The particular function-applicative implementation and consequent recognition model design presented are seen as arising from a noun-adjective recognition model enabling the recognition of colour adjectives as applied to a set of shapes representing objects to be recognised. The presence of such a function application scheme and a separately implemented position identification and path labelling scheme are accordingly shown to be the primitives required to enable the design and construction of a composite depictive motion verb recognition scheme. Extensions to the presented design to enable the representation of transitive verbs are also discussed.

Communication: Multiple-property-based diabatization for open-shell van der Waals molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karman, Tijs; Avoird, Ad van der; Groenenboom, Gerrit C., E-mail: gerritg@theochem.ru.nl

2016-03-28

We derive a new multiple-property-based diabatization algorithm. The transformation between adiabatic and diabatic representations is determined by requiring a set of properties in both representations to be related by a similarity transformation. This set of properties is determined in the adiabatic representation by rigorous electronic structure calculations. In the diabatic representation, the same properties are determined using model diabatic states defined as products of undistorted monomer wave functions. This diabatic model is generally applicable to van der Waals molecules in arbitrary electronic states. Application to locating seams of conical intersections and collisional transfer of electronic excitation energy is demonstrated formore » O{sub 2} − O{sub 2} in low-lying excited states. Property-based diabatization for this test system included all components of the electric quadrupole tensor, orbital angular momentum, and spin-orbit coupling.« less

A polygon soup representation for free viewpoint video

NASA Astrophysics Data System (ADS)

Colleu, T.; Pateux, S.; Morin, L.; Labit, C.

2010-02-01

This paper presents a polygon soup representation for multiview data. Starting from a sequence of multi-view video plus depth (MVD) data, the proposed representation takes into account, in a unified manner, different issues such as compactness, compression, and intermediate view synthesis. The representation is built in two steps. First, a set of 3D quads is extracted using a quadtree decomposition of the depth maps. Second, a selective elimination of the quads is performed in order to reduce inter-view redundancies and thus provide a compact representation. Moreover, the proposed methodology for extracting the representation allows to reduce ghosting artifacts. Finally, an adapted compression technique is proposed that limits coding artifacts. The results presented on two real sequences show that the proposed representation provides a good trade-off between rendering quality and data compactness.

Analysis of the ST-T complex of the electrocardiogram using the Karhunen--Loeve transform: adaptive monitoring and alternans detection

NASA Technical Reports Server (NTRS)

Laguna, P.; Moody, G. B.; Garcia, J.; Goldberger, A. L.; Mark, R. G.

1999-01-01

The Karhunen-Loeve transform (KLT) is applied to study the ventricular repolarisation period as reflected in the ST-T complex of the surface ECG. The KLT coefficients provide a sensitive means of quantitating ST-T shapes. A training set of ST-T complexes is used to derive a set of KLT basis vectors that permits representation of 90% of the signal energy using four KLT coefficients. As a truncated KLT expansion tends to favor representation of the signal over any additive noise, a time series of KLT coefficients obtained from successive ST-T complexes is better suited for representation of both medium-term variations (such as ischemic changes) and short-term variations (such as ST-T alternans) than discrete parameters such as the ST level or other local indices. For analysis of ischemic changes, an adaptive filter is described that can be used to estimate the KLT coefficient, yielding an increase in the signal-to-noise ratio of 10 dB (u = 0.1), with a convergence time of about three beats. A beat spectrum of the unfiltered KLT coefficient series is used for detection of ST-T alterans. These methods are illustrated with examples from the European ST-T Database. About 20% of records revealed quasi-periodic salvos of ischemic ST-T change episodes and another 20% exhibit repetitive, but not clearly periodic patterns of ST-T change episodes. About 5% of ischemic episodes were associated with ST-T alterans.

Pertinent Factors that Affect the Representation of Women and Minorities in Scientific, Engineering, and Technical Careers

DTIC Science & Technology

1990-07-01

Upon the Supply of Minority and Women Scientists, Engineers , and Technologists (SETs) for Defense Industries and Installations." The purpose of the...the causes of the underrepresentation of minorities and women in scientific, engineering , and technolog- ical (SET) careers, and to establish a...DT ?copy- ARI Research Note 90-80 AD-A231 827 Pertinent Factors that Affect the Representation of Women and Minorities in Scientific, Engineering

Distinctive signatures of recursion.

PubMed

Martins, Maurício Dias

2012-07-19

Although recursion has been hypothesized to be a necessary capacity for the evolution of language, the multiplicity of definitions being used has undermined the broader interpretation of empirical results. I propose that only a definition focused on representational abilities allows the prediction of specific behavioural traits that enable us to distinguish recursion from non-recursive iteration and from hierarchical embedding: only subjects able to represent recursion, i.e. to represent different hierarchical dependencies (related by parenthood) with the same set of rules, are able to generalize and produce new levels of embedding beyond those specified a priori (in the algorithm or in the input). The ability to use such representations may be advantageous in several domains: action sequencing, problem-solving, spatial navigation, social navigation and for the emergence of conventionalized communication systems. The ability to represent contiguous hierarchical levels with the same rules may lead subjects to expect unknown levels and constituents to behave similarly, and this prior knowledge may bias learning positively. Finally, a new paradigm to test for recursion is presented. Preliminary results suggest that the ability to represent recursion in the spatial domain recruits both visual and verbal resources. Implications regarding language evolution are discussed.

A systematization of spectral data on the methanol molecule

NASA Astrophysics Data System (ADS)

Akhlyostin, A. Yu.; Voronina, S. S.; Lavrentiev, N. A.; Privezentsev, A. I.; Rodimova, O. B.; Fazliev, A. Z.

2015-11-01

Problems underlying a systematization of spectral data on the methanol molecule are formulated. Data on the energy levels and vacuum wavenumbers acquired from the published literature are presented in the form of information sources imported into the W@DIS information system. Sets of quantum numbers and labels used to describe the CH3OH molecular states are analyzed. The set of labels is different from universally accepted sets. A system of importing the data sources into W@DIS is outlined. The structure of databases characterizing transitions in an isolated CH3OH molecule is introduced and a digital library of the relevant published literature is discussed. A brief description is given of an imported data quality analysis and representation of the results obtained in the form of ontologies for subsequent computer processing.

Vision and the representation of the surroundings in spatial memory

PubMed Central

Tatler, Benjamin W.; Land, Michael F.

2011-01-01

One of the paradoxes of vision is that the world as it appears to us and the image on the retina at any moment are not much like each other. The visual world seems to be extensive and continuous across time. However, the manner in which we sample the visual environment is neither extensive nor continuous. How does the brain reconcile these differences? Here, we consider existing evidence from both static and dynamic viewing paradigms together with the logical requirements of any representational scheme that would be able to support active behaviour. While static scene viewing paradigms favour extensive, but perhaps abstracted, memory representations, dynamic settings suggest sparser and task-selective representation. We suggest that in dynamic settings where movement within extended environments is required to complete a task, the combination of visual input, egocentric and allocentric representations work together to allow efficient behaviour. The egocentric model serves as a coding scheme in which actions can be planned, but also offers a potential means of providing the perceptual stability that we experience. PMID:21242146

Representation of molecular structure using quantum topology with inductive logic programming in structure-activity relationships.

PubMed

Buttingsrud, Bård; Ryeng, Einar; King, Ross D; Alsberg, Bjørn K

2006-06-01

The requirement of aligning each individual molecule in a data set severely limits the type of molecules which can be analysed with traditional structure activity relationship (SAR) methods. A method which solves this problem by using relations between objects is inductive logic programming (ILP). Another advantage of this methodology is its ability to include background knowledge as 1st-order logic. However, previous molecular ILP representations have not been effective in describing the electronic structure of molecules. We present a more unified and comprehensive representation based on Richard Bader's quantum topological atoms in molecules (AIM) theory where critical points in the electron density are connected through a network. AIM theory provides a wealth of chemical information about individual atoms and their bond connections enabling a more flexible and chemically relevant representation. To obtain even more relevant rules with higher coverage, we apply manual postprocessing and interpretation of ILP rules. We have tested the usefulness of the new representation in SAR modelling on classifying compounds of low/high mutagenicity and on a set of factor Xa inhibitors of high and low affinity.

Public Higher Education Performance Accountability Framework Report: Goal--Access and Affordability. Measure: Percentage of Racial Representation in Systems of Higher Education Compared to Racial Representation in the State. Commission Report 07-20

ERIC Educational Resources Information Center

California Postsecondary Education Commission, 2007

2007-01-01

Despite segmental efforts to increase diversity in higher education, African American and Latino students are not achieving levels of representation in California public universities that are equivalent to their levels of representation in the overall State population. Using data for the years 1997 through 2006, the California Postsecondary…

Multiscale 3-D shape representation and segmentation using spherical wavelets.

PubMed

Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen

2007-04-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details.

Multiscale 3-D Shape Representation and Segmentation Using Spherical Wavelets

PubMed Central

Nain, Delphine; Haker, Steven; Bobick, Aaron

2013-01-01

This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of our multiscale prior and 2) a segmentation task. In the reconstruction task, our results show that for a given training set size, our algorithm significantly improves the approximation of shapes in a testing set over the Point Distribution Model, which tends to oversmooth data. In the segmentation task, our validation shows our algorithm is computationally efficient and outperforms the Active Shape Model algorithm, by capturing finer shape details. PMID:17427745

Quantity judgments of sequentially presented food items by capuchin monkeys (Cebus apella).

PubMed

Evans, Theodore A; Beran, Michael J; Harris, Emily H; Rice, Daniel F

2009-01-01

Recent assessments have shown that capuchin monkeys, like chimpanzees and other Old World primate species, are sensitive to quantitative differences between sets of visible stimuli. In the present study, we examined capuchins' performance in a more sophisticated quantity judgment task that required the ability to form representations of food quantities while viewing the quantities only one piece at a time. In three experiments, we presented monkeys with the choice between two sets of discrete homogeneous food items and allowed the monkeys to consume the set of their choice. In Experiments 1 and 2, monkeys compared an entirely visible food set to a second set, presented item-by-item into an opaque container. All monkeys exhibited high accuracy in choosing the larger set, even when the entirely visible set was presented last, preventing the use of one-to-one item correspondence to compare quantities. In Experiment 3, monkeys compared two sets that were each presented item-by-item into opaque containers, but at different rates to control for temporal cues. Some monkeys performed well in this experiment, though others exhibited near-chance performance, suggesting that this species' ability to form representations of food quantities may be limited compared to previously tested species such as chimpanzees. Overall, these findings support the analog magnitude model of quantity representation as an explanation for capuchin monkeys' quantification of sequentially presented food items.

Water-level representation by men and women as a function of rod-and-frame test proficiency and visual and postural information.

PubMed

Robert, M; Ohlmann, T

1994-01-01

In the water-level task, it has been repeatedly shown that, compared with men, women more often fail to represent the surface of a liquid as horizontal regardless of the tilt of the container. An attempt was made to reduce this robust gender gap through the manipulation of relevant upright references conveyed both by the position of the stimuli and the posture of the subject. It was reasoned that bringing the women to focus on such gravitational references through postural adjustment might help their performance equal that of men, thus shedding some light on the nature of the difficulty they experience in the standard setting. A lesser effect was anticipated among men. However, the results showed that, even after controlling for proficiency in the correlated visuospatial situation of the rod-and-frame test, the performance of men always surpassed that of women. Irrespective of gender, water-level representation on vertical sheets was unaffected by the subject's posture, whereas it improved when horizontal sheets were coupled with the most unstable posture. Whereas the persistence of the yet-unaccounted-for gender difference was underscored, the contributions of visual and postural cues issued at arm and full-body levels were discussed.

Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

PubMed Central

Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

2014-01-01

The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations. PMID:25538637

An embedded system for face classification in infrared video using sparse representation

NASA Astrophysics Data System (ADS)

Saavedra M., Antonio; Pezoa, Jorge E.; Zarkesh-Ha, Payman; Figueroa, Miguel

2017-09-01

We propose a platform for robust face recognition in Infrared (IR) images using Compressive Sensing (CS). In line with CS theory, the classification problem is solved using a sparse representation framework, where test images are modeled by means of a linear combination of the training set. Because the training set constitutes an over-complete dictionary, we identify new images by finding their sparsest representation based on the training set, using standard l1-minimization algorithms. Unlike conventional face-recognition algorithms, we feature extraction is performed using random projections with a precomputed binary matrix, as proposed in the CS literature. This random sampling reduces the effects of noise and occlusions such as facial hair, eyeglasses, and disguises, which are notoriously challenging in IR images. Thus, the performance of our framework is robust to these noise and occlusion factors, achieving an average accuracy of approximately 90% when the UCHThermalFace database is used for training and testing purposes. We implemented our framework on a high-performance embedded digital system, where the computation of the sparse representation of IR images was performed by a dedicated hardware using a deeply pipelined architecture on an Field-Programmable Gate Array (FPGA).

From phase space to integrable representations and level-rank duality

NASA Astrophysics Data System (ADS)

Chattopadhyay, Arghya; Dutta, Parikshit; Dutta, Suvankar

2018-05-01

We explicitly find representations for different large N phases of Chern-Simons matter theory on S 2 × S 1. These representations are characterised by Young diagrams. We show that no-gap and lower-gap phase of Chern-Simons-matter theory correspond to integrable representations of SU( N) k affine Lie algebra, where as upper-cap phase corresponds to integrable representations of SU( k - N) k affine Lie algebra. We use phase space description of [1] to obtain these representations and argue how putting a cap on eigenvalue distribution forces corresponding representations to be integrable. We also prove that the Young diagrams corresponding to lower-gap and upper-cap representations are related to each other by transposition under level-rank duality. Finally we draw phase space droplets for these phases and show how information about eigenvalue and Young diagram descriptions can be captured in topologies of these droplets in a unified way.

Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning

NASA Astrophysics Data System (ADS)

Shi, Bibo; Hou, Rui; Mazurowski, Maciej A.; Grimm, Lars J.; Ren, Yinhao; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2018-02-01

Purpose: To determine whether domain transfer learning can improve the performance of deep features extracted from digital mammograms using a pre-trained deep convolutional neural network (CNN) in the prediction of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy. Method: In this study, we collected digital mammography magnification views for 140 patients with DCIS at biopsy, 35 of which were subsequently upstaged to invasive cancer. We utilized a deep CNN model that was pre-trained on two natural image data sets (ImageNet and DTD) and one mammographic data set (INbreast) as the feature extractor, hypothesizing that these data sets are increasingly more similar to our target task and will lead to better representations of deep features to describe DCIS lesions. Through a statistical pooling strategy, three sets of deep features were extracted using the CNNs at different levels of convolutional layers from the lesion areas. A logistic regression classifier was then trained to predict which tumors contain occult invasive disease. The generalization performance was assessed and compared using repeated random sub-sampling validation and receiver operating characteristic (ROC) curve analysis. Result: The best performance of deep features was from CNN model pre-trained on INbreast, and the proposed classifier using this set of deep features was able to achieve a median classification performance of ROC-AUC equal to 0.75, which is significantly better (p<=0.05) than the performance of deep features extracted using ImageNet data set (ROCAUC = 0.68). Conclusion: Transfer learning is helpful for learning a better representation of deep features, and improves the prediction of occult invasive disease in DCIS.

Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

PubMed

Sadeghi, Zahra

2016-09-01

In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

Tracing the footsteps of Sherlock Holmes: cognitive representations of hypothesis testing.

PubMed

Van Wallendael, L R; Hastie, R

1990-05-01

A well-documented phenomenon in opinion-revision literature is subjects' failure to revise probability estimates for an exhaustive set of mutually exclusive hypotheses in a complementary manner. However, prior research has not addressed the question of whether such behavior simply represents a misunderstanding of mathematical rules, or whether it is a consequence of a cognitive representation of hypotheses that is at odds with the Bayesian notion of a set relationship. Two alternatives to the Bayesian representation, a belief system (Shafer, 1976) and a system of independent hypotheses, were proposed, and three experiments were conducted to examine cognitive representations of hypothesis sets in the testing of multiple competing hypotheses. Subjects were given brief murder mysteries to solve and allowed to request various types of information about the suspects; after having received each new piece of information, subjects rated each suspect's probability of being the murderer. Presence and timing of suspect eliminations were varied in the first two experiments; the final experiment involved the varying of percentages of clues that referred to more than one suspect (for example, all of the female suspects). The noncomplementarity of opinion revisions remained a strong phenomenon in all conditions. Information-search data refuted the idea that subjects represented hypotheses as a Bayesian set; further study of the independent hypotheses theory and Shaferian belief functions as descriptive models is encouraged.

Visual Memories Bypass Normalization.

PubMed

Bloem, Ilona M; Watanabe, Yurika L; Kibbe, Melissa M; Ling, Sam

2018-05-01

How distinct are visual memory representations from visual perception? Although evidence suggests that briefly remembered stimuli are represented within early visual cortices, the degree to which these memory traces resemble true visual representations remains something of a mystery. Here, we tested whether both visual memory and perception succumb to a seemingly ubiquitous neural computation: normalization. Observers were asked to remember the contrast of visual stimuli, which were pitted against each other to promote normalization either in perception or in visual memory. Our results revealed robust normalization between visual representations in perception, yet no signature of normalization occurring between working memory stores-neither between representations in memory nor between memory representations and visual inputs. These results provide unique insight into the nature of visual memory representations, illustrating that visual memory representations follow a different set of computational rules, bypassing normalization, a canonical visual computation.

Visual Memories Bypass Normalization

PubMed Central

Bloem, Ilona M.; Watanabe, Yurika L.; Kibbe, Melissa M.; Ling, Sam

2018-01-01

How distinct are visual memory representations from visual perception? Although evidence suggests that briefly remembered stimuli are represented within early visual cortices, the degree to which these memory traces resemble true visual representations remains something of a mystery. Here, we tested whether both visual memory and perception succumb to a seemingly ubiquitous neural computation: normalization. Observers were asked to remember the contrast of visual stimuli, which were pitted against each other to promote normalization either in perception or in visual memory. Our results revealed robust normalization between visual representations in perception, yet no signature of normalization occurring between working memory stores—neither between representations in memory nor between memory representations and visual inputs. These results provide unique insight into the nature of visual memory representations, illustrating that visual memory representations follow a different set of computational rules, bypassing normalization, a canonical visual computation. PMID:29596038

Fuzzy-Arden-Syntax-based, Vendor-agnostic, Scalable Clinical Decision Support and Monitoring Platform.

PubMed

Adlassnig, Klaus-Peter; Fehre, Karsten; Rappelsberger, Andrea

2015-01-01

This study's objective is to develop and use a scalable genuine technology platform for clinical decision support based on Arden Syntax, which was extended by fuzzy set theory and fuzzy logic. Arden Syntax is a widely recognized formal language for representing clinical and scientific knowledge in an executable format, and is maintained by Health Level Seven (HL7) International and approved by the American National Standards Institute (ANSI). Fuzzy set theory and logic permit the representation of knowledge and automated reasoning under linguistic and propositional uncertainty. These forms of uncertainty are a common feature of patients' medical data, the body of medical knowledge, and deductive clinical reasoning.

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

Impact of action primes on implicit processing of thematic and functional similarity relations: evidence from eye-tracking.

PubMed

Pluciennicka, Ewa; Wamain, Yannick; Coello, Yann; Kalénine, Solène

2016-07-01

The aim of this study was to specify the role of action representations in thematic and functional similarity relations between manipulable artifact objects. Recent behavioral and neurophysiological evidence indicates that while they are all relevant for manipulable artifact concepts, semantic relations based on thematic (e.g., saw-wood), specific function similarity (e.g., saw-axe), and general function similarity (e.g., saw-knife) are differently processed, and may relate to different levels of action representation. Point-light displays of object-related actions previously encoded at the gesture level (e.g., "sawing") or at the higher level of action representation (e.g., "cutting") were used as primes before participants identified target objects (e.g., saw) among semantically related and unrelated distractors (e.g., wood, feather, piano). Analysis of eye movements on the different objects during target identification informed about the amplitude and the timing of implicit activation of the different semantic relations. Results showed that action prime encoding impacted the processing of thematic relations, but not that of functional similarity relations. Semantic competition with thematic distractors was greater and earlier following action primes encoded at the gesture level compared to action primes encoded at higher level. As a whole, these findings highlight the direct influence of action representations on thematic relation processing, and suggest that thematic relations involve gesture-level representations rather than intention-level representations.

Analytic representation of FK/Fπ in two loop chiral perturbation theory

NASA Astrophysics Data System (ADS)

Ananthanarayan, B.; Bijnens, Johan; Friot, Samuel; Ghosh, Shayan

2018-05-01

We present an analytic representation of FK/Fπ as calculated in three-flavor two-loop chiral perturbation theory, which involves expressing three mass scale sunsets in terms of Kampé de Fériet series. We demonstrate how approximations may be made to obtain relatively compact analytic representations. An illustrative set of fits using lattice data is also presented, which shows good agreement with existing fits.

Text-to-phonemic transcription and parsing into mono-syllables of English text

NASA Astrophysics Data System (ADS)

Jusgir Mullick, Yugal; Agrawal, S. S.; Tayal, Smita; Goswami, Manisha

2004-05-01

The present paper describes a program that converts the English text (entered through the normal computer keyboard) into its phonemic representation and then parses it into mono-syllables. For every letter a set of context based rules is defined in lexical order. A default rule is also defined separately for each letter. Beginning from the first letter of the word the rules are checked and the most appropriate rule is applied on the letter to find its actual orthographic representation. If no matching rule is found, then the default rule is applied. Current rule sets the next position to be analyzed. Proceeding in the same manner orthographic representation for each word can be found. For example, ``reading'' is represented as ``rEdiNX'' by applying the following rules: r-->r move 1 position ahead ead-->Ed move 3 position ahead i-->i move 1 position ahead ng-->NX move 2 position ahead, i.e., end of word. The phonemic representations obtained from the above procedure are parsed to get mono-syllabic representation for various combinations such as CVC, CVCC, CV, CVCVC, etc. For example, the above phonemic representation will be parsed as rEdiNX---> /rE/ /diNX/. This study is a part of developing TTS for Indian English.

Community representation in hospital decision making: a literature review.

PubMed

Murray, Zoë

2015-06-01

Advancing quality in health services requires structures and processes that are informed by consumer input. Although this agenda is well recognised, few researchers have focussed on the establishment and maintenance of customer input throughout the structures and processes used to produce high-quality, safe care. We present an analysis of literature outlining the barriers and enablers involved in community representation in hospital governance. The review aimed to explore how community representation in hospital governance is achieved. Studies spanning 1997-2012 were analysed using Donabedian' s model of quality systems as a guide for categories of interest: structure, in relation to administration of quality; process, which is particularly concerned with cooperation and culture; and outcome, considered, in this case, to be the achievement of effective community representation on quality of care. There are limited published studies on community representation in hospital governance in Australia. What can be gleaned from the literature is: 1) quality subcommittees set up to assist Hospital Boards are a key structure for involving community representation in decision making around quality of care, and 2) there are a number of challenges to effectively developing the process of community representation in hospital governance: ambiguity and the potential for escalated indecision; inadequate value and consideration given to it by decision makers resulting in a lack of time and resources needed to support the community engagement strategy (time, facilitation, budgets); poor support and attitude amongst staff; and consumer issues, such as feeling isolated and intimidated by expert opinion. The analysis indicates that: quality subcommittees set up to assist boards are a key structure for involving community representation in decision making around quality of care. There are clearly a number of challenges to effectively developing the process of community representation in hospital governance, associated with ambiguity, organisational and consumer issues. For an inclusive agenda to real life, work must be done on understanding the representatives' role and the decision making process, adequately supporting the representational process, and developing organisational cooperation and culture regarding community representation.

Dysfunctional representation of expected value is associated with reinforcement-based decision-making deficits in adolescents with conduct problems.

PubMed

White, Stuart F; Tyler, Patrick M; Erway, Anna K; Botkin, Mary L; Kolli, Venkata; Meffert, Harma; Pope, Kayla; Blair, James R

2016-08-01

Previous work has shown that patients with conduct problems (CP) show impairments in reinforcement-based decision-making. However, studies with patients have not previously demonstrated any relationships between impairment in any of the neurocomputations underpinning reinforcement-based decision-making and specific symptom sets [e.g. level of CP and/or callous-unemotional (CU) traits]. Seventy-two youths [20 female, mean age = 13.81 (SD = 2.14), mean IQ = 102.34 (SD = 10.99)] from a residential treatment program and the community completed a passive avoidance task while undergoing functional MRI. Greater levels of CP were associated with poorer task performance. Reduced representation of expected values (EV) when making avoidance responses within bilateral anterior insula cortex/inferior frontal gyrus (AIC/iFG) and striatum was associated with greater levels of CP but not CU traits. The current data indicate that difficulties in the use of value information to motivate decisions to avoid suboptimal choices are associated with increased levels of CP (though not severity of CU traits). Moreover, they account for the behavioral deficits observed during reinforcement-based decision-making in youth with CP. In short, an individual's relative failure to utilize value information within AIC/iFG to avoid bad choices is associated with elevated levels of CP. © 2016 Association for Child and Adolescent Mental Health.

Representation of Time-Relevant Common Data Elements in the Cancer Data Standards Repository: Statistical Evaluation of an Ontological Approach

PubMed Central

Chen, Henry W; Du, Jingcheng; Song, Hsing-Yi; Liu, Xiangyu; Jiang, Guoqian

2018-01-01

Background Today, there is an increasing need to centralize and standardize electronic health data within clinical research as the volume of data continues to balloon. Domain-specific common data elements (CDEs) are emerging as a standard approach to clinical research data capturing and reporting. Recent efforts to standardize clinical study CDEs have been of great benefit in facilitating data integration and data sharing. The importance of the temporal dimension of clinical research studies has been well recognized; however, very few studies have focused on the formal representation of temporal constraints and temporal relationships within clinical research data in the biomedical research community. In particular, temporal information can be extremely powerful to enable high-quality cancer research. Objective The objective of the study was to develop and evaluate an ontological approach to represent the temporal aspects of cancer study CDEs. Methods We used CDEs recorded in the National Cancer Institute (NCI) Cancer Data Standards Repository (caDSR) and created a CDE parser to extract time-relevant CDEs from the caDSR. Using the Web Ontology Language (OWL)–based Time Event Ontology (TEO), we manually derived representative patterns to semantically model the temporal components of the CDEs using an observing set of randomly selected time-related CDEs (n=600) to create a set of TEO ontological representation patterns. In evaluating TEO’s ability to represent the temporal components of the CDEs, this set of representation patterns was tested against two test sets of randomly selected time-related CDEs (n=425). Results It was found that 94.2% (801/850) of the CDEs in the test sets could be represented by the TEO representation patterns. Conclusions In conclusion, TEO is a good ontological model for representing the temporal components of the CDEs recorded in caDSR. Our representative model can harness the Semantic Web reasoning and inferencing functionalities and present a means for temporal CDEs to be machine-readable, streamlining meaningful searches. PMID:29472179

A Non-destructive Terahertz Spectroscopy-Based Method for Transgenic Rice Seed Discrimination via Sparse Representation

NASA Astrophysics Data System (ADS)

Hu, Xiaohua; Lang, Wenhui; Liu, Wei; Xu, Xue; Yang, Jianbo; Zheng, Lei

2017-08-01

Terahertz (THz) spectroscopy technique has been researched and developed for rapid and non-destructive detection of food safety and quality due to its low-energy and non-ionizing characteristics. The objective of this study was to develop a flexible identification model to discriminate transgenic and non-transgenic rice seeds based on terahertz (THz) spectroscopy. To extract THz spectral features and reduce the feature dimension, sparse representation (SR) is employed in this work. A sufficient sparsity level is selected to train the sparse coding of the THz data, and the random forest (RF) method is then applied to obtain a discrimination model. The results show that there exist differences between transgenic and non-transgenic rice seeds in THz spectral band and, comparing with Least squares support vector machines (LS-SVM) method, SR-RF is a better model for discrimination (accuracy is 95% in prediction set, 100% in calibration set, respectively). The conclusion is that SR may be more useful in the application of THz spectroscopy to reduce dimension and the SR-RF provides a new, effective, and flexible method for detection and identification of transgenic and non-transgenic rice seeds with THz spectral system.

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

PubMed Central

Shang, Yue; Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

2011-01-01

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from multiple documents based on semantic relation extraction. Our approach includes three stages: 1) We extract semantic relations in each sentence using the semantic knowledge representation tool SemRep. 2) We develop a relation-level retrieval method to select the relations most relevant to each query concept and visualize them in a graphic representation. 3) For relations in the relevant set, we extract informative sentences that can interpret them from the document collection to generate text summary using an information retrieval based method. Our major focus in this work is to investigate the contribution of semantic relation extraction to the task of biomedical text summarization. The experimental results on summarization for a set of diseases show that the introduction of semantic knowledge improves the performance and our results are better than the MEAD system, a well-known tool for text summarization. PMID:21887336

The categorical structure of semantic memory for famous people: a new approach using release from proactive interference.

PubMed

Darling, Stephen; Valentine, Tim

2005-05-01

Memory for familiar people is essential to understand their identity and guide social interaction. Nevertheless, we know surprisingly little about the structure of such memory. Previous research has assumed that semantic memory for people has a categorical structure, but recently it was proposed that memory for people consists only of associations and lacks any categorical structure. Four experiments are reported that use a novel approach by adapting the 'release from proactive interference' (RPI) methodology for use with lists of famous names. Proactive interference occurs when items presented on successive trials are drawn from the same category. Recall can improve following a change to a different category. Sets of names were selected relating to aspects previously demonstrated, on the basis of reaction time data, to form a category (occupation) and a property (nationality) of celebrities (Johnston & Bruce, 1990). RPI was observed for a change at both levels of representation but was only present without explicitly cueing the change of set when the stimuli differed at the category level. At the property level, RPI was only evident when change of set was explicitly cued. RPI was absent at the set change in a novel, ad hoc distinction suggesting that the effect reflected the underlying memory structure.

Generic decoding of seen and imagined objects using hierarchical visual features.

PubMed

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-05-22

Object recognition is a key function in both human and machine vision. While brain decoding of seen and imagined objects has been achieved, the prediction is limited to training examples. We present a decoding approach for arbitrary objects using the machine vision principle that an object category is represented by a set of features rendered invariant through hierarchical processing. We show that visual features, including those derived from a deep convolutional neural network, can be predicted from fMRI patterns, and that greater accuracy is achieved for low-/high-level features with lower-/higher-level visual areas, respectively. Predicted features are used to identify seen/imagined object categories (extending beyond decoder training) from a set of computed features for numerous object images. Furthermore, decoding of imagined objects reveals progressive recruitment of higher-to-lower visual representations. Our results demonstrate a homology between human and machine vision and its utility for brain-based information retrieval.

Bayesian learning of visual chunks by human observers

PubMed Central

Orbán, Gergő; Fiser, József; Aslin, Richard N.; Lengyel, Máté

2008-01-01

Efficient and versatile processing of any hierarchically structured information requires a learning mechanism that combines lower-level features into higher-level chunks. We investigated this chunking mechanism in humans with a visual pattern-learning paradigm. We developed an ideal learner based on Bayesian model comparison that extracts and stores only those chunks of information that are minimally sufficient to encode a set of visual scenes. Our ideal Bayesian chunk learner not only reproduced the results of a large set of previous empirical findings in the domain of human pattern learning but also made a key prediction that we confirmed experimentally. In accordance with Bayesian learning but contrary to associative learning, human performance was well above chance when pair-wise statistics in the exemplars contained no relevant information. Thus, humans extract chunks from complex visual patterns by generating accurate yet economical representations and not by encoding the full correlational structure of the input. PMID:18268353

Students' understandings of electrochemistry

NASA Astrophysics Data System (ADS)

O'Grady-Morris, Kathryn

Electrochemistry is considered by students to be a difficult topic in chemistry. This research was a mixed methods study guided by the research question: At the end of a unit of study, what are students' understandings of electrochemistry? The framework of analysis used for the qualitative and quantitative data collected in this study was comprised of three categories: types of knowledge used in problem solving, levels of representation of knowledge in chemistry (macroscopic, symbolic, and particulate), and alternative conceptions. Although individually each of the three categories has been reported in previous studies, the contribution of this study is the inter-relationships among them. Semi-structured, task-based interviews were conducted while students were setting up and operating electrochemical cells in the laboratory, and a two-tiered, multiple-choice diagnostic instrument was designed to identify alternative conceptions that students held at the end of the unit. For familiar problems, those involving routine voltaic cells, students used a working-forwards problem-solving strategy, two or three levels of representation of knowledge during explanations, scored higher on both procedural and conceptual knowledge questions in the diagnostic instrument, and held fewer alternative conceptions related to the operation of these cells. For less familiar problems, those involving non-routine voltaic cells and electrolytic cells, students approached problem-solving with procedural knowledge, used only one level of representation of knowledge when explaining the operation of these cells, scored higher on procedural knowledge than conceptual knowledge questions in the diagnostic instrument, and held a greater number of alternative conceptions. Decision routines that involved memorized formulas and procedures were used to solve both quantitative and qualitative problems and the main source of alternative conceptions in this study was the overgeneralization of theory related to the particulate level of representation of knowledge. The findings from this study may contribute further to our understanding of students' conceptions in electrochemistry. Furthermore, understanding the influence of the three categories in the framework of analysis and their inter-relationships on how students make sense of this field may result in a better understanding of classroom practice that could promote the acquisition of conceptual knowledge --- knowledge that is "rich in relationships".

An Integrated Planning Representation Using Macros, Abstractions, and Cases

NASA Technical Reports Server (NTRS)

Baltes, Jacky; MacDonald, Bruce

1992-01-01

Planning will be an essential part of future autonomous robots and integrated intelligent systems. This paper focuses on learning problem solving knowledge in planning systems. The system is based on a common representation for macros, abstractions, and cases. Therefore, it is able to exploit both classical and case based techniques. The general operators in a successful plan derivation would be assessed for their potential usefulness, and some stored. The feasibility of this approach was studied through the implementation of a learning system for abstraction. New macros are motivated by trying to improve the operatorset. One heuristic used to improve the operator set is generating operators with more general preconditions than existing ones. This heuristic leads naturally to abstraction hierarchies. This investigation showed promising results on the towers of Hanoi problem. The paper concludes by describing methods for learning other problem solving knowledge. This knowledge can be represented by allowing operators at different levels of abstraction in a refinement.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liakh, Dmitry I

While the formalism of multiresolution analysis (MRA), based on wavelets and adaptive integral representations of operators, is actively progressing in electronic structure theory (mostly on the independent-particle level and, recently, second-order perturbation theory), the concepts of multiresolution and adaptivity can also be utilized within the traditional formulation of correlated (many-particle) theory which is based on second quantization and the corresponding (generally nonorthogonal) tensor algebra. In this paper, we present a formalism called scale-adaptive tensor algebra (SATA) which exploits an adaptive representation of tensors of many-body operators via the local adjustment of the basis set quality. Given a series of locallymore » supported fragment bases of a progressively lower quality, we formulate the explicit rules for tensor algebra operations dealing with adaptively resolved tensor operands. The formalism suggested is expected to enhance the applicability and reliability of local correlated many-body methods of electronic structure theory, especially those directly based on atomic orbitals (or any other localized basis functions).« less

Superradiant effects on pulse propagation in resonant media. [atomic excitations/coherent radiation - operators (mathematics)/matrices (mathematics)

NASA Technical Reports Server (NTRS)

Lee, C.

1975-01-01

Adopting the so-called genealogical construction, the eigenstates of collective operators can be expressed corresponding to a specified mode for an N-atom system in terms of those for an (N-1)-atom system. Matrix element of a collective operator of an arbitrary mode is presented which can be written as the product of an m-dependent factor and an m-independent reduced matrix element (RME). A set of recursion formulas for the RME was obtained. A graphical representation of the RME on the branching diagram for binary irreducible representations of permutation groups was then introduced. This gave a simple and systematic way of calculating the RME. Results show explicitly the geometry dependence of superradiance and the relative importance of r-conserving and r-nonconserving processes and clears up the chief difficulty encounted in the problem of N two-level atoms, spread over large regions, interacting with a multimode radiation field.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

PubMed

Chaudhri, Vinay K; Elenius, Daniel; Goldenkranz, Andrew; Gong, Allison; Martone, Maryann E; Webb, William; Yorke-Smith, Neil

2014-01-01

Using knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms? Our existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important. With some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels.

Robust kernel collaborative representation for face recognition

NASA Astrophysics Data System (ADS)

Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

2015-05-01

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

Using Multiple Representations to Resolve Conflict in Student Conceptual Understanding of Chemistry

NASA Astrophysics Data System (ADS)

Daubenmire, Paul L.

Much like a practiced linguist, expert chemists utilize the power and elegance of chemical symbols to understand what is happening at the atomic level and to manipulate atoms and molecules to effect an observable change at the macroscopic level. Unfortunately, beginning chemistry is often taught in a way that emphasizes memorizing the symbolic representations of equations and reactions without much opportunity to meaningfully connect the observable macroscopic phenomena with an understanding of the chemistry taking place at the atomic level. The compartmentalized manner of chemistry instruction in most chemistry classrooms further nullifies the efficacy of the triplet relationship to connect between macroscopic observations, symbolic representations, and atomic scale views. If symbolic representations are presented as the goal of instruction, rather than as the means to gain understanding, then students will be impaired in developing a coherent understanding of chemical principles. This dissertation describes the development and implementation of an interview study to examine how undergraduate students interpreted multiple representations of a chemical equilibrium. To establish a baseline of ideas, students first were coached to verbally generate successive representations. They were then cued to think about the chemistry occurring between atoms and ions at the molecular level. Next, an experiment involving a change in states of matter and color was performed which paralleled the symbolic representations. Through self-explanations and verbalizing of conjectures, students were encouraged to explore, interpret, and refine their understanding of the observations related to the chemical symbols presented to them. Finally, with the goal of fostering a deeper understanding of the process of equilibrium, a dynamic visualization of the molecular level was introduced as a tool for helping students connect these multiple representations. This study revealed that one way in which students develop conceptual understanding and resolve conflicts between different representations of the same phenomena is by verbalizing their ideas as a conjecture (as a verbal explanation to advance towards a hypothesis). Thus, it is proposed that symbolic representations are most effective viewed not as an end goal but as a bridge for connecting macroscopic, visible phenomena with what is occurring at the molecular, invisible level. When the focus on merely memorizing chemical equations and symbols is removed, students can gain a coherent understanding of the meaning available when multiple representations are viewed together.

Bayesian analogy with relational transformations.

PubMed

Lu, Hongjing; Chen, Dawn; Holyoak, Keith J

2012-07-01

How can humans acquire relational representations that enable analogical inference and other forms of high-level reasoning? Using comparative relations as a model domain, we explore the possibility that bottom-up learning mechanisms applied to objects coded as feature vectors can yield representations of relations sufficient to solve analogy problems. We introduce Bayesian analogy with relational transformations (BART) and apply the model to the task of learning first-order comparative relations (e.g., larger, smaller, fiercer, meeker) from a set of animal pairs. Inputs are coded by vectors of continuous-valued features, based either on human magnitude ratings, normed feature ratings (De Deyne et al., 2008), or outputs of the topics model (Griffiths, Steyvers, & Tenenbaum, 2007). Bootstrapping from empirical priors, the model is able to induce first-order relations represented as probabilistic weight distributions, even when given positive examples only. These learned representations allow classification of novel instantiations of the relations and yield a symbolic distance effect of the sort obtained with both humans and other primates. BART then transforms its learned weight distributions by importance-guided mapping, thereby placing distinct dimensions into correspondence. These transformed representations allow BART to reliably solve 4-term analogies (e.g., larger:smaller::fiercer:meeker), a type of reasoning that is arguably specific to humans. Our results provide a proof-of-concept that structured analogies can be solved with representations induced from unstructured feature vectors by mechanisms that operate in a largely bottom-up fashion. We discuss potential implications for algorithmic and neural models of relational thinking, as well as for the evolution of abstract thought. Copyright 2012 APA, all rights reserved.

Set of Frequent Word Item sets as Feature Representation for Text with Indonesian Slang

NASA Astrophysics Data System (ADS)

Sa'adillah Maylawati, Dian; Putri Saptawati, G. A.

2017-01-01

Indonesian slang are commonly used in social media. Due to their unstructured syntax, it is difficult to extract their features based on Indonesian grammar for text mining. To do so, we propose Set of Frequent Word Item sets (SFWI) as text representation which is considered match for Indonesian slang. Besides, SFWI is able to keep the meaning of Indonesian slang with regard to the order of appearance sentence. We use FP-Growth algorithm with adding separation sentence function into the algorithm to extract the feature of SFWI. The experiments is done with text data from social media such as Facebook, Twitter, and personal website. The result of experiments shows that Indonesian slang were more correctly interpreted based on SFWI.

Set processing in a network environment. [data bases and magnetic disks and tapes

NASA Technical Reports Server (NTRS)

Hardgrave, W. T.

1975-01-01

A combination of a local network, a mass storage system, and an autonomous set processor serving as a data/storage management machine is described. Its characteristics include: content-accessible data bases usable from all connected devices; efficient storage/access of large data bases; simple and direct programming with data manipulation and storage management handled by the set processor; simple data base design and entry from source representation to set processor representation with no predefinition necessary; capability available for user sort/order specification; significant reduction in tape/disk pack storage and mounts; flexible environment that allows upgrading hardware/software configuration without causing major interruptions in service; minimal traffic on data communications network; and improved central memory usage on large processors.

Dissimilarity representations in lung parenchyma classification

NASA Astrophysics Data System (ADS)

Sørensen, Lauge; de Bruijne, Marleen

2009-02-01

A good problem representation is important for a pattern recognition system to be successful. The traditional approach to statistical pattern recognition is feature representation. More specifically, objects are represented by a number of features in a feature vector space, and classifiers are built in this representation. This is also the general trend in lung parenchyma classification in computed tomography (CT) images, where the features often are measures on feature histograms. Instead, we propose to build normal density based classifiers in dissimilarity representations for lung parenchyma classification. This allows for the classifiers to work on dissimilarities between objects, which might be a more natural way of representing lung parenchyma. In this context, dissimilarity is defined between CT regions of interest (ROI)s. ROIs are represented by their CT attenuation histogram and ROI dissimilarity is defined as a histogram dissimilarity measure between the attenuation histograms. In this setting, the full histograms are utilized according to the chosen histogram dissimilarity measure. We apply this idea to classification of different emphysema patterns as well as normal, healthy tissue. Two dissimilarity representation approaches as well as different histogram dissimilarity measures are considered. The approaches are evaluated on a set of 168 CT ROIs using normal density based classifiers all showing good performance. Compared to using histogram dissimilarity directly as distance in a emph{k} nearest neighbor classifier, which achieves a classification accuracy of 92.9%, the best dissimilarity representation based classifier is significantly better with a classification accuracy of 97.0% (text{emph{p" border="0" class="imgtopleft"> = 0.046).

Can Children Read Evolutionary Trees?

ERIC Educational Resources Information Center

Ainsworth, Shaaron; Saffer, Jessica

2013-01-01

Representations of the "tree of life" such as cladograms show the history of lineages and their relationships. They are increasingly found in formal and informal learning settings. Unfortunately, there is evidence that these representations can be challenging to interpret correctly. This study explored the question of whether children…

Neural Representations of Physics Concepts.

PubMed

Mason, Robert A; Just, Marcel Adam

2016-06-01

We used functional MRI (fMRI) to assess neural representations of physics concepts (momentum, energy, etc.) in juniors, seniors, and graduate students majoring in physics or engineering. Our goal was to identify the underlying neural dimensions of these representations. Using factor analysis to reduce the number of dimensions of activation, we obtained four physics-related factors that were mapped to sets of voxels. The four factors were interpretable as causal motion visualization, periodicity, algebraic form, and energy flow. The individual concepts were identifiable from their fMRI signatures with a mean rank accuracy of .75 using a machine-learning (multivoxel) classifier. Furthermore, there was commonality in participants' neural representation of physics; a classifier trained on data from all but one participant identified the concepts in the left-out participant (mean accuracy = .71 across all nine participant samples). The findings indicate that abstract scientific concepts acquired in an educational setting evoke activation patterns that are identifiable and common, indicating that science education builds abstract knowledge using inherent, repurposed brain systems. © The Author(s) 2016.

The Action Execution Process Implemented in Different Cognitive Architectures: A Review

NASA Astrophysics Data System (ADS)

Dong, Daqi; Franklin, Stan

2014-12-01

An agent achieves its goals by interacting with its environment, cyclically choosing and executing suitable actions. An action execution process is a reasonable and critical part of an entire cognitive architecture, because the process of generating executable motor commands is not only driven by low-level environmental information, but is also initiated and affected by the agent's high-level mental processes. This review focuses on cognitive models of action, or more specifically, of the action execution process, as implemented in a set of popular cognitive architectures. We examine the representations and procedures inside the action execution process, as well as the cooperation between action execution and other high-level cognitive modules. We finally conclude with some general observations regarding the nature of action execution.

[Shared decision-making and individualized goal setting - a pilot trial using PRISM (Pictorial Representation of Illness and Self Measure) in psychiatric inpatients].

PubMed

Büchi, S; Straub, S; Schwager, U

2010-12-01

Although there is much talk about shared decision making and individualized goal setting, there is a lack of knowledge and knowhow in their realization in daily clinical practice. There is a lack in tools for easy applicable tools to ameliorate person-centred individualized goal setting processes. In three selected psychiatric inpatients the semistructured, theory driven use of PRISM (Pictorial Representation of Illness and Self Measure) in patients with complex psychiatric problems is presented and discussed. PRISM sustains a person-centred individualized process of goal setting and treatment and reinforces the active participation of patients. The process of visualisation and synchronous documentation is validated positively by patients and clinicians. The visual goal setting requires 30 to 45 minutes. In patients with complex psychiatric illness PRISM was used successfully to ameliorate individual goal setting. Specific effects of PRISM-visualisation are actually evaluated in a randomized controlled trial.

Single and Multiple Object Tracking Using a Multi-Feature Joint Sparse Representation.

PubMed

Hu, Weiming; Li, Wei; Zhang, Xiaoqin; Maybank, Stephen

2015-04-01

In this paper, we propose a tracking algorithm based on a multi-feature joint sparse representation. The templates for the sparse representation can include pixel values, textures, and edges. In the multi-feature joint optimization, noise or occlusion is dealt with using a set of trivial templates. A sparse weight constraint is introduced to dynamically select the relevant templates from the full set of templates. A variance ratio measure is adopted to adaptively adjust the weights of different features. The multi-feature template set is updated adaptively. We further propose an algorithm for tracking multi-objects with occlusion handling based on the multi-feature joint sparse reconstruction. The observation model based on sparse reconstruction automatically focuses on the visible parts of an occluded object by using the information in the trivial templates. The multi-object tracking is simplified into a joint Bayesian inference. The experimental results show the superiority of our algorithm over several state-of-the-art tracking algorithms.

Historical evidence for nature disconnection in a 70-year time series of Disney animated films.

PubMed

Prévot-Julliard, Anne-Caroline; Julliard, Romain; Clayton, Susan

2015-08-01

The assumed ongoing disconnection between humans and nature in Western societies represents a profoundly challenging conservation issue. Here, we demonstrate one manifestation of this nature disconnection, via an examination of the representation of natural settings in a 70-year time series of Disney animated films. We found that natural settings are increasingly less present as a representation of outdoor environments in these films. Moreover, these drawn natural settings tend to be more and more human controlled and are less and less complex in terms of the biodiversity they depict. These results demonstrate the increasing nature disconnection of the filmmaking teams, which we consider as a proxy of the Western relation to nature. Additionally, because nature experience of children is partly based on movies, the depleted representation of biodiversity in outdoor environments of Disney films may amplify the current disconnection from nature for children. This reduction in exposure to nature may hinder the implementation of biodiversity conservation measures. © The Author(s) 2014.

Intercomparison and Uncertainty Assessment of Nine Evapotranspiration Estimates Over South America

NASA Astrophysics Data System (ADS)

Sörensson, Anna A.; Ruscica, Romina C.

2018-04-01

This study examines the uncertainties and the representations of anomalies of a set of evapotranspiration products over climatologically distinct regions of South America. The products, coming from land surface models, reanalysis, and remote sensing, are chosen from sources that are readily available to the community of users. The results show that the spatial patterns of maximum uncertainty differ among metrics, with dry regions showing maximum relative uncertainties of annual mean evapotranspiration, while energy-limited regions present maximum uncertainties in the representation of the annual cycle and monsoon regions in the representation of anomalous conditions. Furthermore, it is found that land surface models driven by observed atmospheric fields detect meteorological and agricultural droughts in dry regions unequivocally. The remote sensing products employed do not distinguish all agricultural droughts and this could be attributed to the forcing net radiation. The study also highlights important characteristics of individual data sets and recommends users to include assessments of sensitivity to evapotranspiration data sets in their studies, depending on region and nature of study to be conducted.

Demazure Modules, Fusion Products and Q-Systems

NASA Astrophysics Data System (ADS)

Chari, Vyjayanthi; Venkatesh, R.

2015-01-01

In this paper, we introduce a family of indecomposable finite-dimensional graded modules for the current algebra associated to a simple Lie algebra. These modules are indexed by an -tuple of partitions , where α varies over a set of positive roots of and we assume that they satisfy a natural compatibility condition. In the case when the are all rectangular, for instance, we prove that these modules are Demazure modules in various levels. As a consequence, we see that the defining relations of Demazure modules can be greatly simplified. We use this simplified presentation to relate our results to the fusion products, defined in (Feigin and Loktev in Am Math Soc Transl Ser (2) 194:61-79, 1999), of representations of the current algebra. We prove that the Q-system of (Hatayama et al. in Contemporary Mathematics, vol. 248, pp. 243-291. American Mathematical Society, Providence, 1998) extends to a canonical short exact sequence of fusion products of representations associated to certain special partitions .Finally, in the last section we deal with the case of and prove that the modules we define are just fusion products of irreducible representations of the associated current algebra and give monomial bases for these modules.

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit

2015-03-01

A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.

Reconciling conflicting electrophysiological findings on the guidance of attention by working memory.

PubMed

Carlisle, Nancy B; Woodman, Geoffrey F

2013-10-01

Maintaining a representation in working memory has been proposed to be sufficient for the execution of top-down attentional control. Two recent electrophysiological studies that recorded event-related potentials (ERPs) during similar paradigms have tested this proposal, but have reported contradictory findings. The goal of the present study was to reconcile these previous reports. To this end, we used the stimuli from one study (Kumar, Soto, & Humphreys, 2009) combined with the task manipulations from the other (Carlisle & Woodman, 2011b). We found that when an item matching a working memory representation was presented in a visual search array, we could use ERPs to quantify the size of the covert attention effect. When the working memory matches were consistently task-irrelevant, we observed a weak attentional bias to these items. However, when the same item indicated the location of the search target, we found that the covert attention effect was approximately four times larger. This shows that simply maintaining a representation in working memory is not equivalent to having a top-down attentional set for that item. Our findings indicate that high-level goals mediate the relationship between the contents of working memory and perceptual attention.

The 'morbid anatomy' of the human genome: tracing the observational and representational approaches of postwar genetics and biomedicine the William Bynum Prize Essay.

PubMed

Hogan, Andrew J

2014-07-01

This paper explores evolving conceptions and depictions of the human genome among human and medical geneticists during the postwar period. Historians of science and medicine have shown significant interest in the use of informational approaches in postwar genetics, which treat the genome as an expansive digital data set composed of three billion DNA nucleotides. Since the 1950s, however, geneticists have largely interacted with the human genome at the microscopically visible level of chromosomes. Mindful of this, I examine the observational and representational approaches of postwar human and medical genetics. During the 1970s and 1980s, the genome increasingly came to be understood as, at once, a discrete part of the human anatomy and a standardised scientific object. This paper explores the role of influential medical geneticists in recasting the human genome as being a visible, tangible, and legible entity, which was highly relevant to traditional medical thinking and practice. I demonstrate how the human genome was established as an object amenable to laboratory and clinical research, and argue that the observational and representational approaches of postwar medical genetics reflect, more broadly, the interdisciplinary efforts underlying the development of contemporary biomedicine.

Complex fuzzy soft expert sets

NASA Astrophysics Data System (ADS)

Selvachandran, Ganeshsree; Hafeed, Nisren A.; Salleh, Abdul Razak

2017-04-01

Complex fuzzy sets and its accompanying theory although at its infancy, has proven to be superior to classical type-1 fuzzy sets, due its ability in representing time-periodic problem parameters and capturing the seasonality of the fuzziness that exists in the elements of a set. These are important characteristics that are pervasive in most real world problems. However, there are two major problems that are inherent in complex fuzzy sets: it lacks a sufficient parameterization tool and it does not have a mechanism to validate the values assigned to the membership functions of the elements in a set. To overcome these problems, we propose the notion of complex fuzzy soft expert sets which is a hybrid model of complex fuzzy sets and soft expert sets. This model incorporates the advantages of complex fuzzy sets and soft sets, besides having the added advantage of allowing the users to know the opinion of all the experts in a single model without the need for any additional cumbersome operations. As such, this model effectively improves the accuracy of representation of problem parameters that are periodic in nature, besides having a higher level of computational efficiency compared to similar models in literature.

Neglecting the Left Side of a City Square but Not the Left Side of Its Clock: Prevalence and Characteristics of Representational Neglect

PubMed Central

Guariglia, Cecilia; Palermo, Liana; Piccardi, Laura; Iaria, Giuseppe; Incoccia, Chiara

2013-01-01

Representational neglect, which is characterized by the failure to report left-sided details of a mental image from memory, can occur after a right hemisphere lesion. In this study, we set out to verify the hypothesis that two distinct forms of representational neglect exist, one involving object representation and the other environmental representation. As representational neglect is considered rare, we also evaluated the prevalence and frequency of its association with perceptual neglect. We submitted a group of 96 unselected, consecutive, chronic, right brain-damaged patients to an extensive neuropsychological evaluation that included two representational neglect tests: the Familiar Square Description Test and the O'Clock Test. Representational neglect, as well as perceptual neglect, was present in about one-third of the sample. Most patients neglected the left side of imagined familiar squares but not the left side of imagined clocks. The present data show that representational neglect is not a rare disorder and also support the hypothesis that two different types of mental representations (i.e. topological and non-topological images) may be selectively damaged in representational neglect. PMID:23874416

Commonalities between Perception and Cognition.

PubMed

Tacca, Michela C

2011-01-01

Perception and cognition are highly interrelated. Given the influence that these systems exert on one another, it is important to explain how perceptual representations and cognitive representations interact. In this paper, I analyze the similarities between visual perceptual representations and cognitive representations in terms of their structural properties and content. Specifically, I argue that the spatial structure underlying visual object representation displays systematicity - a property that is considered to be characteristic of propositional cognitive representations. To this end, I propose a logical characterization of visual feature binding as described by Treisman's Feature Integration Theory and argue that systematicity is not only a property of language-like representations, but also of spatially organized visual representations. Furthermore, I argue that if systematicity is taken to be a criterion to distinguish between conceptual and non-conceptual representations, then visual representations, that display systematicity, might count as an early type of conceptual representations. Showing these analogies between visual perception and cognition is an important step toward understanding the interface between the two systems. The ideas here presented might also set the stage for new empirical studies that directly compare binding (and other relational operations) in visual perception and higher cognition.

Commonalities between Perception and Cognition

PubMed Central

Tacca, Michela C.

2011-01-01

Perception and cognition are highly interrelated. Given the influence that these systems exert on one another, it is important to explain how perceptual representations and cognitive representations interact. In this paper, I analyze the similarities between visual perceptual representations and cognitive representations in terms of their structural properties and content. Specifically, I argue that the spatial structure underlying visual object representation displays systematicity – a property that is considered to be characteristic of propositional cognitive representations. To this end, I propose a logical characterization of visual feature binding as described by Treisman’s Feature Integration Theory and argue that systematicity is not only a property of language-like representations, but also of spatially organized visual representations. Furthermore, I argue that if systematicity is taken to be a criterion to distinguish between conceptual and non-conceptual representations, then visual representations, that display systematicity, might count as an early type of conceptual representations. Showing these analogies between visual perception and cognition is an important step toward understanding the interface between the two systems. The ideas here presented might also set the stage for new empirical studies that directly compare binding (and other relational operations) in visual perception and higher cognition. PMID:22144974

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.

Experience-Dependent Enhancement of Linguistic Pitch Representation in the Brainstem Is Not Specific to a Speech Context

ERIC Educational Resources Information Center

Krishnan, Ananthanarayan; Swaminathan, Jayaganesh; Gandour, Jackson T.

2009-01-01

Neural representation of pitch is influenced by lifelong experiences with music and language at both cortical and subcortical levels of processing. The aim of this article is to determine whether neural plasticity for pitch representation at the level of the brainstem is dependent upon specific "dimensions" of pitch contours that commonly occur as…

From action representation to action execution: exploring the links between cognitive and biomechanical levels of motor control

PubMed Central

Land, William M.; Volchenkov, Dima; Bläsing, Bettina E.; Schack, Thomas

2013-01-01

Along with superior performance, research indicates that expertise is associated with a number of mediating cognitive adaptations. To this extent, extensive practice is associated with the development of general and task-specific mental representations, which play an important role in the organization and control of action. Recently, new experimental methods have been developed, which allow for investigating the organization and structure of these representations, along with the functional structure of the movement kinematics. In the current article, we present a new approach for examining the overlap between skill representations and motor output. In doing so, we first present an architecture model, which addresses links between biomechanical and cognitive levels of motor control. Next, we review the state of the art in assessing memory structures underlying complex action. Following we present a new spatio-temporal decomposition method for illuminating the functional structure of movement kinematics, and finally, we apply these methods to investigate the overlap between the structure of motor representations in memory and their corresponding kinematic structures. Our aim is to understand the extent to which the output at a kinematic level is governed by representations at a cognitive level of motor control. PMID:24065915

Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance

NASA Astrophysics Data System (ADS)

Land, Walker H., Jr.; Anderson, Frances; Smith, Tom; Fahlbusch, Stephen; Choma, Robert; Wong, Lut

2005-04-01

Achieving consistent and correct database cases is crucial to the correct evaluation of any computer-assisted diagnostic (CAD) paradigm. This paper describes the application of artificial intelligence (AI), knowledge engineering (KE) and knowledge representation (KR) to a data set of ~2500 cases from six separate hospitals, with the objective of removing/reducing inconsistent outlier data. Several support vector machine (SVM) kernels were used to measure diagnostic performance of the original and a "cleaned" data set. Specifically, KE and ER principles were applied to the two data sets which were re-examined with respect to the environment and agents. One data set was found to contain 25 non-characterizable sets. The other data set contained 180 non-characterizable sets. CAD system performance was measured with both the original and "cleaned" data sets using two SVM kernels as well as a multivariate probabilistic neural network (PNN). Results demonstrated: (i) a 10% average improvement in overall Az and (ii) approximately a 50% average improvement in partial Az.

Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation.

PubMed

Yang, Jian-Yi; Peng, Zhen-Ling; Yu, Zu-Guo; Zhang, Rui-Jie; Anh, Vo; Wang, Desheng

2009-04-21

In this paper, we intend to predict protein structural classes (alpha, beta, alpha+beta, or alpha/beta) for low-homology data sets. Two data sets were used widely, 1189 (containing 1092 proteins) and 25PDB (containing 1673 proteins) with sequence homology being 40% and 25%, respectively. We propose to decompose the chaos game representation of proteins into two kinds of time series. Then, a novel and powerful nonlinear analysis technique, recurrence quantification analysis (RQA), is applied to analyze these time series. For a given protein sequence, a total of 16 characteristic parameters can be calculated with RQA, which are treated as feature representation of protein sequences. Based on such feature representation, the structural class for each protein is predicted with Fisher's linear discriminant algorithm. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies with step-by-step procedure are 65.8% and 64.2% for 1189 and 25PDB data sets, respectively. With one-against-others procedure used widely, we compare our method with five other existing methods. Especially, the overall accuracies of our method are 6.3% and 4.1% higher for the two data sets, respectively. Furthermore, only 16 parameters are used in our method, which is less than that used by other methods. This suggests that the current method may play a complementary role to the existing methods and is promising to perform the prediction of protein structural classes.

Classification of forensic autopsy reports through conceptual graph-based document representation model.

PubMed

Mujtaba, Ghulam; Shuib, Liyana; Raj, Ram Gopal; Rajandram, Retnagowri; Shaikh, Khairunisa; Al-Garadi, Mohammed Ali

2018-06-01

Text categorization has been used extensively in recent years to classify plain-text clinical reports. This study employs text categorization techniques for the classification of open narrative forensic autopsy reports. One of the key steps in text classification is document representation. In document representation, a clinical report is transformed into a format that is suitable for classification. The traditional document representation technique for text categorization is the bag-of-words (BoW) technique. In this study, the traditional BoW technique is ineffective in classifying forensic autopsy reports because it merely extracts frequent but discriminative features from clinical reports. Moreover, this technique fails to capture word inversion, as well as word-level synonymy and polysemy, when classifying autopsy reports. Hence, the BoW technique suffers from low accuracy and low robustness unless it is improved with contextual and application-specific information. To overcome the aforementioned limitations of the BoW technique, this research aims to develop an effective conceptual graph-based document representation (CGDR) technique to classify 1500 forensic autopsy reports from four (4) manners of death (MoD) and sixteen (16) causes of death (CoD). Term-based and Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT) based conceptual features were extracted and represented through graphs. These features were then used to train a two-level text classifier. The first level classifier was responsible for predicting MoD. In addition, the second level classifier was responsible for predicting CoD using the proposed conceptual graph-based document representation technique. To demonstrate the significance of the proposed technique, its results were compared with those of six (6) state-of-the-art document representation techniques. Lastly, this study compared the effects of one-level classification and two-level classification on the experimental results. The experimental results indicated that the CGDR technique achieved 12% to 15% improvement in accuracy compared with fully automated document representation baseline techniques. Moreover, two-level classification obtained better results compared with one-level classification. The promising results of the proposed conceptual graph-based document representation technique suggest that pathologists can adopt the proposed system as their basis for second opinion, thereby supporting them in effectively determining CoD. Copyright © 2018 Elsevier Inc. All rights reserved.

Theoretical foundations of spatially-variant mathematical morphology part ii: gray-level images.

PubMed

Bouaynaya, Nidhal; Schonfeld, Dan

2008-05-01

In this paper, we develop a spatially-variant (SV) mathematical morphology theory for gray-level signals and images in the Euclidean space. The proposed theory preserves the geometrical concept of the structuring function, which provides the foundation of classical morphology and is essential in signal and image processing applications. We define the basic SV gray-level morphological operators (i.e., SV gray-level erosion, dilation, opening, and closing) and investigate their properties. We demonstrate the ubiquity of SV gray-level morphological systems by deriving a kernel representation for a large class of systems, called V-systems, in terms of the basic SV graylevel morphological operators. A V-system is defined to be a gray-level operator, which is invariant under gray-level (vertical) translations. Particular attention is focused on the class of SV flat gray-level operators. The kernel representation for increasing V-systems is a generalization of Maragos' kernel representation for increasing and translation-invariant function-processing systems. A representation of V-systems in terms of their kernel elements is established for increasing and upper-semi-continuous V-systems. This representation unifies a large class of spatially-variant linear and non-linear systems under the same mathematical framework. Finally, simulation results show the potential power of the general theory of gray-level spatially-variant mathematical morphology in several image analysis and computer vision applications.

Impact of parameterization choices on the restitution of ozone deposition over vegetation

NASA Astrophysics Data System (ADS)

Le Morvan-Quéméner, Aurélie; Coll, Isabelle; Kammer, Julien; Lamaud, Eric; Loubet, Benjamin; Personne, Erwan; Stella, Patrick

2018-04-01

Ozone is a potentially phyto-toxic air pollutant, which can cause leaf damage and drastically alter crop yields, causing serious economic losses around the world. The VULNOZ (VULNerability to OZone in Anthropised Ecosystems) project is a biology and modeling project that aims to understand how plants respond to the stress of high ozone concentrations, then use a set of models to (i) predict the impact of ozone on plant growth, (ii) represent ozone deposition fluxes to vegetation, and finally (iii) estimate the economic consequences of an increasing ozone background the future. In this work, as part of the VULNOZ project, an innovative representation of ozone deposition to vegetation was developed and implemented in the CHIMERE regional chemistry-transport model. This type of model calculates the average amount of ozone deposited on a parcel each hour, as well as the integrated amount of ozone deposited to the surface at the regional or country level. Our new approach was based on a refinement of the representation of crop types in the model and the use of empirical parameters specific to each crop category. The results obtained were compared with a conventional ozone deposition modeling approach, and evaluated against observations from several agricultural areas in France. They showed that a better representation of the distribution between stomatal and non-stomatal ozone fluxes was obtained in the empirical approach, and they allowed us to produce a new estimate of the total amount of ozone deposited on the subtypes of vegetation at the national level.

Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation

PubMed Central

Veloz, Tomas; Desjardins, Sylvie

2015-01-01

Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations. PMID:26617556

Unitary Transformations in the Quantum Model for Conceptual Conjunctions and Its Application to Data Representation.

PubMed

Veloz, Tomas; Desjardins, Sylvie

2015-01-01

Quantum models of concept combinations have been successful in representing various experimental situations that cannot be accommodated by traditional models based on classical probability or fuzzy set theory. In many cases, the focus has been on producing a representation that fits experimental results to validate quantum models. However, these representations are not always consistent with the cognitive modeling principles. Moreover, some important issues related to the representation of concepts such as the dimensionality of the realization space, the uniqueness of solutions, and the compatibility of measurements, have been overlooked. In this paper, we provide a dimensional analysis of the realization space for the two-sector Fock space model for conjunction of concepts focusing on the first and second sectors separately. We then introduce various representation of concepts that arise from the use of unitary operators in the realization space. In these concrete representations, a pair of concepts and their combination are modeled by a single conceptual state, and by a collection of exemplar-dependent operators. Therefore, they are consistent with cognitive modeling principles. This framework not only provides a uniform approach to model an entire data set, but, because all measurement operators are expressed in the same basis, allows us to address the question of compatibility of measurements. In particular, we present evidence that it may be possible to predict non-commutative effects from partial measurements of conceptual combinations.

Profile of Students’ Mental Model Change on Law Concepts Archimedes as Impact of Multi-Representation Approach

NASA Astrophysics Data System (ADS)

Taher, M.; Hamidah, I.; Suwarma, I. R.

2017-09-01

This paper outlined the results of an experimental study on the effects of multi-representation approach in learning Archimedes Law on students’ mental model improvement. The multi-representation techniques implemented in the study were verbal, pictorial, mathematical, and graphical representations. Students’ mental model was classified into three levels, i.e. scientific, synthetic, and initial levels, based on the students’ level of understanding. The present study employed the pre-experimental methodology, using one group pretest-posttest design. The subject of the study was 32 eleventh grade students in a Public Senior High School in Riau Province. The research instrument included model mental test on hydrostatic pressure concept, in the form of essay test judged by experts. The findings showed that there was positive change in students’ mental model, indicating that multi-representation approach was effective to improve students’ mental model.

Modeling salt-mediated electrostatics of macromolecules: the discrete surface charge optimization algorithm and its application to the nucleosome.

PubMed

Beard, D A; Schlick, T

2001-01-01

Much progress has been achieved on quantitative assessment of electrostatic interactions on the all-atom level by molecular mechanics and dynamics, as well as on the macroscopic level by models of continuum solvation. Bridging of the two representations-an area of active research-is necessary for studying integrated functions of large systems of biological importance. Following perspectives of both discrete (N-body) interaction and continuum solvation, we present a new algorithm, DiSCO (Discrete Surface Charge Optimization), for economically describing the electrostatic field predicted by Poisson-Boltzmann theory using a discrete set of Debye-Hückel charges distributed on a virtual surface enclosing the macromolecule. The procedure in DiSCO relies on the linear behavior of the Poisson-Boltzmann equation in the far zone; thus contributions from a number of molecules may be superimposed, and the electrostatic potential, or equivalently the electrostatic field, may be quickly and efficiently approximated by the summation of contributions from the set of charges. The desired accuracy of this approximation is achieved by minimizing the difference between the Poisson-Boltzmann electrostatic field and that produced by the linearized Debye-Hückel approximation using our truncated Newton optimization package. DiSCO is applied here to describe the salt-dependent electrostatic environment of the nucleosome core particle in terms of several hundred surface charges. This representation forms the basis for modeling-by dynamic simulations (or Monte Carlo)-the folding of chromatin. DiSCO can be applied more generally to many macromolecular systems whose size and complexity warrant a model resolution between the all-atom and macroscopic levels. Copyright 2000 John Wiley & Sons, Inc.

Plane representations of graphs and visibility between parallel segments

NASA Astrophysics Data System (ADS)

Tamassia, R.; Tollis, I. G.

1985-04-01

Several layout compaction strategies for VLSI are based on the concept of visibility between parallel segments, where we say that two parallel segments of a given set are visible if they can be joined by a segment orthogonal to them, which does not intersect any other segment. This paper studies visibility representations of graphs, which are constructed by mapping vertices to horizontal segments, and edges to vertical segments drawn between visible vertex-segments. Clearly, every graph that admits such a representation must be a planar. The authors consider three types of visibility representations, and give complete characterizations of the classes of graphs that admit them. Furthermore, they present linear time algorithms for testing the existence of and constructing visibility representations of planar graphs.

View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Freiwald, Winrich A.; Anselmi, Fabio; Poggio, Tomaso

2017-01-01

SUMMARY The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations like depth-rotations [1, 2]. Current computational models of object recognition, including recent deep learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3, 4, 5, 6]. Here we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here we demonstrate that one specific biologically-plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli like faces at intermediate levels of the architecture and show why it does so. Thus the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. PMID:27916522

Deep Restricted Kernel Machines Using Conjugate Feature Duality.

PubMed

Suykens, Johan A K

2017-08-01

The aim of this letter is to propose a theory of deep restricted kernel machines offering new foundations for deep learning with kernel machines. From the viewpoint of deep learning, it is partially related to restricted Boltzmann machines, which are characterized by visible and hidden units in a bipartite graph without hidden-to-hidden connections and deep learning extensions as deep belief networks and deep Boltzmann machines. From the viewpoint of kernel machines, it includes least squares support vector machines for classification and regression, kernel principal component analysis (PCA), matrix singular value decomposition, and Parzen-type models. A key element is to first characterize these kernel machines in terms of so-called conjugate feature duality, yielding a representation with visible and hidden units. It is shown how this is related to the energy form in restricted Boltzmann machines, with continuous variables in a nonprobabilistic setting. In this new framework of so-called restricted kernel machine (RKM) representations, the dual variables correspond to hidden features. Deep RKM are obtained by coupling the RKMs. The method is illustrated for deep RKM, consisting of three levels with a least squares support vector machine regression level and two kernel PCA levels. In its primal form also deep feedforward neural networks can be trained within this framework.

Evaluating Common Item Block Options When Faced with Practical Constraints

ERIC Educational Resources Information Center

Wolkowitz, Amanda; Davis-Becker, Susan

2015-01-01

This study evaluates the impact of common item characteristics on the outcome of equating in credentialing examinations when traditionally recommended representation is not possible. This research used real data sets from several credentialing exams to test the impact of content representation, item statistics, and number of common items on…

The Graphic Representation of Structure in Similarity/Dissimilarity Matrices: Alternative Methods.

ERIC Educational Resources Information Center

Rudnitsky, Alan N.

Three approaches to the graphic representation of similarity and dissimilarity matrices are compared and contrasted. Specifically, Kruskal's multidimensional scaling, Johnson's hierarchical clustering, and Waern's graphing techniques are employed to depict, in two dimensions, data representing the structure of a set of botanical concepts. Each of…

Students' Construction of External Representations in Design-Based Learning Situations

ERIC Educational Resources Information Center

de Vries, Erica

2006-01-01

This article develops a theoretical framework for the study of students' construction of mixed multiple external representations in design-based learning situations involving an adaptation of professional tasks and tools to a classroom setting. The framework draws on research on professional design processes and on learning with multiple external…

Visual Representation of Rational Belief Revision: Another Look at the Sleeping Beauty Problem

DTIC Science & Technology

2014-10-29

Retamero and Cokely , 2013). Visual representation is thought to facilitate performance by externalizing the set-subset relations among observa- tional... Cokely , E. T. (2013). Communicating health risks with visual aids. Curr. Dir. Psychol. Sci. 22, 392–399. doi: 10.1177/0963721413491570 Horgan, T. (2004

Shaping Relations: Exploiting Relational Features for Visuospatial Priming

ERIC Educational Resources Information Center

Livins, Katherine A.; Doumas, Leonidas A. A.; Spivey, Michael J.

2016-01-01

Although relational reasoning has been described as a process at the heart of human cognition, the exact character of relational representations remains an open debate. Symbolic-connectionist models of relational cognition suggest that relations are structured representations, but that they are ultimately grounded in feature sets; thus, they…

Content Analysis of Science Teacher Representations in Google Images

ERIC Educational Resources Information Center

Bergman, Daniel

2017-01-01

Teacher images can impact numerous perceptions in educational settings, as well as through popular media. The portrayal of effective science teaching is especially challenging to specify, given the complex nature of science inquiry and other standards-based practices. The present study examined the litany of representations of science teachers…

Systematic Representation of Knowledge of Ecology: Concepts and Relationships.

ERIC Educational Resources Information Center

Garb, Yaakov; And Others

This study describes efforts to apply principles of systematic knowledge representation (concept mapping and computer-based semantic networking techniques) to the domain of ecology. A set of 24 relationships and modifiers is presented that seem sufficient for describing all ecological relationships discussed in an introductory course. Many of…

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Improved water-level forecasting for the Northwest European Shelf and North Sea through direct modelling of tide, surge and non-linear interaction

NASA Astrophysics Data System (ADS)

Zijl, Firmijn; Verlaan, Martin; Gerritsen, Herman

2013-07-01

In real-time operational coastal forecasting systems for the northwest European shelf, the representation accuracy of tide-surge models commonly suffers from insufficiently accurate tidal representation, especially in shallow near-shore areas with complex bathymetry and geometry. Therefore, in conventional operational systems, the surge component from numerical model simulations is used, while the harmonically predicted tide, accurately known from harmonic analysis of tide gauge measurements, is added to forecast the full water-level signal at tide gauge locations. Although there are errors associated with this so-called astronomical correction (e.g. because of the assumption of linearity of tide and surge), for current operational models, astronomical correction has nevertheless been shown to increase the representation accuracy of the full water-level signal. The simulated modulation of the surge through non-linear tide-surge interaction is affected by the poor representation of the tide signal in the tide-surge model, which astronomical correction does not improve. Furthermore, astronomical correction can only be applied to locations where the astronomic tide is known through a harmonic analysis of in situ measurements at tide gauge stations. This provides a strong motivation to improve both tide and surge representation of numerical models used in forecasting. In the present paper, we propose a new generation tide-surge model for the northwest European Shelf (DCSMv6). This is the first application on this scale in which the tidal representation is such that astronomical correction no longer improves the accuracy of the total water-level representation and where, consequently, the straightforward direct model forecasting of total water levels is better. The methodology applied to improve both tide and surge representation of the model is discussed, with emphasis on the use of satellite altimeter data and data assimilation techniques for reducing parameter uncertainty. Historic DCSMv6 model simulations are compared against shelf wide observations for a full calendar year. For a selection of stations, these results are compared to those with astronomical correction, which confirms that the tide representation in coastal regions has sufficient accuracy, and that forecasting total water levels directly yields superior results.

Nondimensional Representations for Occulter Design and Performance Evaluation

NASA Technical Reports Server (NTRS)

Cady, Eric

2011-01-01

An occulter is a spacecraft with a precisely-shaped optical edges which ies in formation with a telescope, blocking light from a star while leaving light from nearby planets una ected. Using linear optimization, occulters can be designed for use with telescopes over a wide range of telescope aperture sizes, science bands, and starlight suppression levels. It can be shown that this optimization depends primarily on a small number of independent nondimensional parameters, which correspond to Fresnel numbers and physical scales and enter the optimization only as constraints. We show how these can be used to span the parameter space of possible optimized occulters; this data set can then be mined to determine occulter sizes for various mission scenarios and sets of engineering constraints.

Quantum cognition based on an ambiguous representation derived from a rough set approximation.

PubMed

Gunji, Yukio-Pegio; Sonoda, Kohei; Basios, Vasileios

2016-03-01

Over the last years, in a series papers by Arecchi and others, a model for the cognitive processes involved in decision making has been proposed and investigated. The key element of this model is the expression of apprehension and judgment, basic cognitive process of decision making, as an inverse Bayes inference classifying the information content of neuron spike trains. It has been shown that for successive plural stimuli this inference, equipped with basic non-algorithmic jumps, is affected by quantum-like characteristics. We show here that such a decision making process is related consistently with an ambiguous representation by an observer within a universe of discourse. In our work the ambiguous representation of an object or a stimuli is defined as a pair of maps from objects of a set to their representations, where these two maps are interrelated in a particular structure. The a priori and a posteriori hypotheses in Bayes inference are replaced by the upper and lower approximations, correspondingly, for the initial data sets that are derived with respect to each map. Upper and lower approximations herein are defined in the context of "rough set" analysis. The inverse Bayes inference is implemented by the lower approximations with respect to the one map and for the upper approximation with respect to the other map for a given data set. We show further that, due to the particular structural relation between the two maps, the logical structure of such combined approximations can only be expressed as an orthomodular lattice and therefore can be represented by a quantum rather than a Boolean logic. To our knowledge, this is the first investigation aiming to reveal the concrete logic structure of inverse Bayes inference in cognitive processes. Copyright © 2016. Published by Elsevier Ireland Ltd.

LBM-EP: Lattice-Boltzmann method for fast cardiac electrophysiology simulation from 3D images.

PubMed

Rapaka, S; Mansi, T; Georgescu, B; Pop, M; Wright, G A; Kamen, A; Comaniciu, Dorin

2012-01-01

Current treatments of heart rhythm troubles require careful planning and guidance for optimal outcomes. Computational models of cardiac electrophysiology are being proposed for therapy planning but current approaches are either too simplified or too computationally intensive for patient-specific simulations in clinical practice. This paper presents a novel approach, LBM-EP, to solve any type of mono-domain cardiac electrophysiology models at near real-time that is especially tailored for patient-specific simulations. The domain is discretized on a Cartesian grid with a level-set representation of patient's heart geometry, previously estimated from images automatically. The cell model is calculated node-wise, while the transmembrane potential is diffused using Lattice-Boltzmann method within the domain defined by the level-set. Experiments on synthetic cases, on a data set from CESC'10 and on one patient with myocardium scar showed that LBM-EP provides results comparable to an FEM implementation, while being 10 - 45 times faster. Fast, accurate, scalable and requiring no specific meshing, LBM-EP paves the way to efficient and detailed models of cardiac electrophysiology for therapy planning.

Completing the physical representation of quantum algorithms provides a retrocausal explanation of the speedup

NASA Astrophysics Data System (ADS)

Castagnoli, Giuseppe

2017-05-01

The usual representation of quantum algorithms, limited to the process of solving the problem, is physically incomplete as it lacks the initial measurement. We extend it to the process of setting the problem. An initial measurement selects a problem setting at random, and a unitary transformation sends it into the desired setting. The extended representation must be with respect to Bob, the problem setter, and any external observer. It cannot be with respect to Alice, the problem solver. It would tell her the problem setting and thus the solution of the problem implicit in it. In the representation to Alice, the projection of the quantum state due to the initial measurement should be postponed until the end of the quantum algorithm. In either representation, there is a unitary transformation between the initial and final measurement outcomes. As a consequence, the final measurement of any ℛ-th part of the solution could select back in time a corresponding part of the random outcome of the initial measurement; the associated projection of the quantum state should be advanced by the inverse of that unitary transformation. This, in the representation to Alice, would tell her, before she begins her problem solving action, that part of the solution. The quantum algorithm should be seen as a sum over classical histories in each of which Alice knows in advance one of the possible ℛ-th parts of the solution and performs the oracle queries still needed to find it - this for the value of ℛ that explains the algorithm's speedup. We have a relation between retrocausality ℛ and the number of oracle queries needed to solve an oracle problem quantumly. All the oracle problems examined can be solved with any value of ℛ up to an upper bound attained by the optimal quantum algorithm. This bound is always in the vicinity of 1/2 . Moreover, ℛ =1/2 always provides the order of magnitude of the number of queries needed to solve the problem in an optimal quantum way. If this were true for any oracle problem, as plausible, it would solve the quantum query complexity problem.

Task alters category representations in prefrontal but not high-level visual cortex.

PubMed

Bugatus, Lior; Weiner, Kevin S; Grill-Spector, Kalanit

2017-07-15

A central question in neuroscience is how cognitive tasks affect category representations across the human brain. Regions in lateral occipito-temporal cortex (LOTC), ventral temporal cortex (VTC), and ventro-lateral prefrontal cortex (VLFPC) constitute the extended "what" pathway, which is considered instrumental for visual category processing. However, it is unknown (1) whether distributed responses across LOTC, VTC, and VLPFC explicitly represent category, task, or some combination of both, and (2) in what way representations across these subdivisions of the extended 'what' pathway may differ. To fill these gaps in knowledge, we scanned 12 participants using fMRI to test the effect of category and task on distributed responses across LOTC, VTC, and VLPFC. Results reveal that task and category modulate responses in both high-level visual regions, as well as prefrontal cortex. However, we found fundamentally different types of representations across the brain. Distributed responses in high-level visual regions are more strongly driven by category than task, and exhibit task-independent category representations. In contrast, distributed responses in prefrontal cortex are more strongly driven by task than category, and contain task-dependent category representations. Together, these findings of differential representations across the brain support a new idea that LOTC and VTC maintain stable category representations allowing efficient processing of visual information, while prefrontal cortex contains flexible representations in which category information may emerge only when relevant to the task. Copyright © 2017 Elsevier Inc. All rights reserved.

Mesh Oriented datABase

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tautges, Timothy J.

MOAB is a component for representing and evaluating mesh data. MOAB can store stuctured and unstructured mesh, consisting of elements in the finite element "zoo". The functional interface to MOAB is simple yet powerful, allowing the representation of many types of metadata commonly found on the mesh. MOAB is optimized for efficiency in space and time, based on access to mesh in chunks rather than through individual entities, while also versatile enough to support individual entity access. The MOAB data model consists of a mesh interface instance, mesh entities (vertices and elements), sets, and tags. Entities are addressed through handlesmore » rather than pointers, to allow the underlying representation of an entity to change without changing the handle to that entity. Sets are arbitrary groupings of mesh entities and other sets. Sets also support parent/child relationships as a relation distinct from sets containing other sets. The directed-graph provided by set parent/child relationships is useful for modeling topological relations from a geometric model or other metadata. Tags are named data which can be assigned to the mesh as a whole, individual entities, or sets. Tags are a mechanism for attaching data to individual entities and sets are a mechanism for describing relations between entities; the combination of these two mechanisms isa powerful yet simple interface for representing metadata or application-specific data. For example, sets and tags can be used together to describe geometric topology, boundary condition, and inter-processor interface groupings in a mesh. MOAB is used in several ways in various applications. MOAB serves as the underlying mesh data representation in the VERDE mesh verification code. MOAB can also be used as a mesh input mechanism, using mesh readers induded with MOAB, or as a t’anslator between mesh formats, using readers and writers included with MOAB.« less

Simulation-based planning for theater air warfare

NASA Astrophysics Data System (ADS)

Popken, Douglas A.; Cox, Louis A., Jr.

2004-08-01

Planning for Theatre Air Warfare can be represented as a hierarchy of decisions. At the top level, surviving airframes must be assigned to roles (e.g., Air Defense, Counter Air, Close Air Support, and AAF Suppression) in each time period in response to changing enemy air defense capabilities, remaining targets, and roles of opposing aircraft. At the middle level, aircraft are allocated to specific targets to support their assigned roles. At the lowest level, routing and engagement decisions are made for individual missions. The decisions at each level form a set of time-sequenced Courses of Action taken by opposing forces. This paper introduces a set of simulation-based optimization heuristics operating within this planning hierarchy to optimize allocations of aircraft. The algorithms estimate distributions for stochastic outcomes of the pairs of Red/Blue decisions. Rather than using traditional stochastic dynamic programming to determine optimal strategies, we use an innovative combination of heuristics, simulation-optimization, and mathematical programming. Blue decisions are guided by a stochastic hill-climbing search algorithm while Red decisions are found by optimizing over a continuous representation of the decision space. Stochastic outcomes are then provided by fast, Lanchester-type attrition simulations. This paper summarizes preliminary results from top and middle level models.

Attachment security representations in institutionalized children and children living with their families: links to problem behaviour.

PubMed

Torres, Nuno; Maia, Joana; Veríssimo, Manuela; Fernandes, Marilia; Silva, Filipa

2012-01-01

The present work analyses differences in the attachment representations of institutionalized children as compared with children from low and high educational level living with their natural families. Participants were 91 Portuguese children, 52% girls, aged 48-96 months. There were three different groups: 19 institutionalized children, 16 low educational level families' children and 56 from high educational level families'. Attachment representations were assessed for Security of the narratives of the Attachment Story Completion Task (ASCT). Psychopathological symptoms were assessed using the Child Behaviour Checklist for parents and caretakers. Verbal skills were assessed using the Wechsler Preschool and Primary Scale of Intelligence--Revised. Results show that institutionalized children have significantly lower security of attachment representations, less verbal skills and higher aggressive behaviour than the other two groups. Attachment representations were associated with social/withdrawal and aggression, independently of age, verbal skills and parents' education. The main effect of institutionalization on externalizing aggressive behaviour was completely mediated by the security of attachment representations.  Copyright © 2010 John Wiley & Sons, Ltd.

Detecting Edges in Images by Use of Fuzzy Reasoning

NASA Technical Reports Server (NTRS)

Dominguez, Jesus A.; Klinko, Steve

2003-01-01

A method of processing digital image data to detect edges includes the use of fuzzy reasoning. The method is completely adaptive and does not require any advance knowledge of an image. During initial processing of image data at a low level of abstraction, the nature of the data is indeterminate. Fuzzy reasoning is used in the present method because it affords an ability to construct useful abstractions from approximate, incomplete, and otherwise imperfect sets of data. Humans are able to make some sense of even unfamiliar objects that have imperfect high-level representations. It appears that to perceive unfamiliar objects or to perceive familiar objects in imperfect images, humans apply heuristic algorithms to understand the images

Importance of Kier-Hall topological indices in the QSAR of anticancer drug design.

PubMed

Nandi, Sisir; Bagchi, Manish C

2012-06-01

An important area of theoretical drug design research is quantitative structure activity relationship (QSAR) using structural invariants. The impetus for this research trend comes from various directions. Researchers in chemical documentation have searched for a set of invariants which will be more convenient than the adjacency matrix (or connection table) for the storage and comparison of chemical structures. Molecular structure can be looked upon as the representation of the relationship among its various constituents. The term molecular structure represents a set of nonequivalent and probably disjoint concepts. There is no reason to believe that when we discuss diverse topics (e.g. chemical synthesis, reaction rates, spectroscopic transitions, reaction mechanisms, and ab initio calculations) using the notion of molecular structure, the different meanings we attach to the single term molecular structure originate from the same fundamental concept. On the contrary, there is a theoretical and philosophical basis for the non-homogeneity of concepts covered by the term molecular structure. In the context of molecular science, the various concepts of molecular structure (e.g. classical valence bond representations, various chemical graph-theoretic representations, ball and spoke model of a molecule, representation of a molecule by minimum energy conformation, semi symbolic contour map of a molecule, or symbolic representation of chemical species by Hamiltonian operators) are model objects derived through different abstractions of the same chemical reality. In each instance, the equivalence class (concept or model of molecular structure) is generated by selecting certain aspects while ignoring some unique properties of those actual events. This explains the plurality of the concept of molecular structure and their autonomous nature, the word autonomous being used in the same sense that one concept is not logically derived from the other. At the most fundamental level, the structural model of an assembled entity (e.g. a molecule consisting of atoms) may be defined as the pattern of relationship among its parts as distinct from the values associated with them. Constitutional formulae of molecules are graphs where vertices represent the set of atoms and edges represent chemical bonds. The pattern of connectedness of atoms in a molecule is preserved by constitutional graphs. A graph (more correctly a non-directed graph) G = [V, E] consists of a finite non-empty set V of points together with a prescribed set E of unordered pairs of distinct points of V. Thus the mathematical characterization of structures represents structural invariants having successful applications in chemical documentation, characterization of molecular branching, enumeration of molecular constitutional associated with a particular empirical formula, calculation of quantum chemical parameters for the generation of quantitative structure-property-activity correlations. Kier developed a number of structural invariants which are now-a-days called as topological indices with wide range of practical applications for QSAR and drug design. The present paper is restricted to the review of Kier-Hall topological indices for QSAR and anticancer drug design for 2,5-bis(1-aziridinyl) 1,4-benzoquinone (BABQ), pyridopyrimidine, 4-anilinoquinazoline and 2-Phenylindoles compounds utilizing various statistical multivariate regression analyses.

Identity-level representations affect unfamiliar face matching performance in sequential but not simultaneous tasks.

PubMed

Menon, Nadia; White, David; Kemp, Richard I

2015-01-01

According to cognitive and neurological models of the face-processing system, faces are represented at two levels of abstraction. First, image-based pictorial representations code a particular instance of a face and include information that is unrelated to identity-such as lighting, pose, and expression. Second, at a more abstract level, identity-specific representations combine information from various encounters with a single face. Here we tested whether identity-level representations mediate unfamiliar face matching performance. Across three experiments we manipulated identity attributions to pairs of target images and measured the effect on subsequent identification decisions. Participants were instructed that target images were either two photos of the same person (1ID condition) or photos of two different people (2ID condition). This manipulation consistently affected performance in sequential matching: 1ID instructions improved accuracy on "match" trials and caused participants to adopt a more liberal response bias than the 2ID condition. However, this manipulation did not affect performance in simultaneous matching. We conclude that identity-level representations, generated in working memory, influence the amount of variation tolerated between images, when making identity judgements in sequential face matching.

Towards a full representation of tropical cyclones in a global reanalysis of extreme sea levels

NASA Astrophysics Data System (ADS)

Muis, S.; Verlaan, M.; Lin, N.; Winsemius, H.; Vatvani, D.; Ward, P.; Aerts, J.

2016-12-01

Tropical cyclones (TCs), including hurricanes and typhoons, are characterised by high wind speeds and low pressure, and cause dangerous storm surges in coastal areas. Recent disasters like the flooding of New Orleans in 2005 due to Hurricane Katrina and of New York in 2012 due to Hurricane Sandy exemplify the significant TC risk in the United States. In this contribution, we present a new framework to model TC storm surges and probabilities at the Atlantic basin- and, ultimately, global scales. This works builds on the work of Muis et al. (2016), which presented the first dynamically-derived reanalysis dataset of storm surges that covers the entire world's coastline (GTSR dataset). Surge levels for the period 1979-2014 were simulated by forcing the Global Surge and Tide Model (GTSM) with wind speed and atmospheric pressure from the ERA-Interim reanalysis. There is generally a good agreement between simulated and observed sea level extremes in extra-tropical regions; however for areas prone to TCs there is a severe underestimation of extremes. For example, the maximum surge levels during Hurricane Katrina in New Orleans exceeded 8 m, whilst the GTSM surge levels in that area do not exceed 2-3 m. Hence, due to the coarse grid resolution, the strong intensities of TCs are not fully captured in ERA-Interim. Furthermore, the length of ERA-Interim data set, like other reanalysis datasets, is too short to estimate the probabilities of extreme TC events in a reliable way. For accurate risk assessments it is essential to improve the representation of TCs in these global reanalysis of extreme sea levels. First, we need a higher resolution of meteorological forcing, which can be modelled with input from the observed best track data. Second, we need to statistically extend the observed record to many thousands of years. We will present the first results of these steps for the east coast of the United States. We will validate the GTSM model forced with best track data using recent extreme events like Katrina and Sandy. We will investigate how the statistics of the extreme sea level will change due to improved representation of TCs.

Invisibility and Ownership of Language: Problems of Representation in Russian Language Textbooks

ERIC Educational Resources Information Center

Azimova, Nigora; Johnston, Bill

2012-01-01

Using the 2 theoretical lenses of representation (Barthes, 1977) and ownership of language (Higgins, 2003), this article offers a critical analysis of representations of Russian speakers in 9 widely used Russian language textbooks aimed at university-level learners. Particular attention is paid to representations of Russian speakers other than…

Back in the USSR: Path Dependence Effects in Student Representation in Russia

ERIC Educational Resources Information Center

Chirikov, Igor; Gruzdev, Ivan

2014-01-01

This paper analyses the current state of student representation in Russia as deeply rooted in the institutional structure of the Soviet higher education system. The study traces the origins of existing institutional arrangements for student representation at the level of university governance and analyses how representation practices have been…

Young Children's Representations of Groups of Objects: The Relationship between Abstraction and Representation.

ERIC Educational Resources Information Center

Kato, Yasuhiko; Kamii, Constance; Ozaki, Kyoko; Nagahiro, Mariko

2002-01-01

Interviews 60 Japanese children between the ages of 3 and 7 years to investigate the relationship between levels of abstraction and representation. Indicates that abstraction and representation are closely related. Implies that educators need to focus more on the mental relationships children make because the meaning children can give to…

Geometric representation methods for multi-type self-defining remote sensing data sets

NASA Technical Reports Server (NTRS)

Anuta, P. E.

1980-01-01

Efficient and convenient representation of remote sensing data is highly important for an effective utilization. The task of merging different data types is currently dealt with by treating each case as an individual problem. A description is provided of work which is carried out to standardize the multidata merging process. The basic concept of the new approach is that of the self-defining data set (SDDS). The creation of a standard is proposed. This standard would be such that data which may be of interest in a large number of earth resources remote sensing applications would be in a format which allows convenient and automatic merging. Attention is given to details regarding the multidata merging problem, a geometric description of multitype data sets, image reconstruction from track-type data, a data set generation system, and an example multitype data set.

The effect of training methodology on knowledge representation in categorization.

PubMed

Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W

2017-01-01

Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.

The effect of training methodology on knowledge representation in categorization

PubMed Central

Shamloo, Farzin; Ell, Shawn W.

2017-01-01

Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule–based (RB) category structures thought to promote between–category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between–category representations whereas concept training resulted in a bias toward within–category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within–category representations. With II structures, there was a bias toward within–category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within–category representations could support generalization during the test phase. These data suggest that within–category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization. PMID:28846732

Representational geometry: integrating cognition, computation, and the brain

PubMed Central

Kriegeskorte, Nikolaus; Kievit, Rogier A.

2013-01-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. PMID:23876494

Mental disability and discriminatory practices: effects of social representations of the Mexican population.

PubMed

Mariana, Espinola-Nadurille; Guadalupe, Delgado

2009-05-01

The prevalence of mental disorders in Mexico is 26.1%. This shows that an important percentage of the population suffers from mental disability. Despite this the country's healthcare system does not provide the least acceptable standard of care for the mentally disabled. The aim of this study was to describe the general population's social representations of the disabled and analyze their relationship with the discriminatory practices from the state towards the mentally ill with respect to their right to health. This study was a secondary analysis of the First National Survey on Discrimination in Mexico. In the survey 1,437 effective interviews that comprised a representative sample, were obtained from people aged 18 to 60 living in rural and urban settings. The response rate was 76.5%. The assessment tool was a self-administered questionnaire that yielded perceptions, attitudes, values and social representations about discrimination towards groups of people that supposedly were targets of discrimination by the general population. In the survey the mentally ill were included under disability. As a secondary analysis of the survey for the purpose of this study, we selected a subset of questions that provided important information about social representations of the general Mexican population towards persons with disabilities. The general population's social representations of the disabled were analyzed. The disabled are the second group after the elderly perceived as the most discriminated and neglected and bearing more suffering. A whole set of negative representations concerning the disabled, such as lack of acceptance and respect, low self-confidence, mistreatment, incomprehension, isolation, intolerance, indifference and bad attitudes from others, were elicited. Social representations are social correspondents of the discriminatory practices that the state exerts toward the mentally ill with respect to their right to health. These representations serve to maintain, naturalize and legitimize these practices. All sectors of society should make an effort to change the negative social representations towards this vulnerable section of society.

Level-set techniques for facies identification in reservoir modeling

NASA Astrophysics Data System (ADS)

Iglesias, Marco A.; McLaughlin, Dennis

2011-03-01

In this paper we investigate the application of level-set techniques for facies identification in reservoir models. The identification of facies is a geometrical inverse ill-posed problem that we formulate in terms of shape optimization. The goal is to find a region (a geologic facies) that minimizes the misfit between predicted and measured data from an oil-water reservoir. In order to address the shape optimization problem, we present a novel application of the level-set iterative framework developed by Burger in (2002 Interfaces Free Bound. 5 301-29 2004 Inverse Problems 20 259-82) for inverse obstacle problems. The optimization is constrained by (the reservoir model) a nonlinear large-scale system of PDEs that describes the reservoir dynamics. We reformulate this reservoir model in a weak (integral) form whose shape derivative can be formally computed from standard results of shape calculus. At each iteration of the scheme, the current estimate of the shape derivative is utilized to define a velocity in the level-set equation. The proper selection of this velocity ensures that the new shape decreases the cost functional. We present results of facies identification where the velocity is computed with the gradient-based (GB) approach of Burger (2002) and the Levenberg-Marquardt (LM) technique of Burger (2004). While an adjoint formulation allows the straightforward application of the GB approach, the LM technique requires the computation of the large-scale Karush-Kuhn-Tucker system that arises at each iteration of the scheme. We efficiently solve this system by means of the representer method. We present some synthetic experiments to show and compare the capabilities and limitations of the proposed implementations of level-set techniques for the identification of geologic facies.

GraDit: graph-based data repair algorithm for multiple data edits rule violations

NASA Astrophysics Data System (ADS)

Ode Zuhayeni Madjida, Wa; Gusti Bagus Baskara Nugraha, I.

2018-03-01

Constraint-based data cleaning captures data violation to a set of rule called data quality rules. The rules consist of integrity constraint and data edits. Structurally, they are similar, where the rule contain left hand side and right hand side. Previous research proposed a data repair algorithm for integrity constraint violation. The algorithm uses undirected hypergraph as rule violation representation. Nevertheless, this algorithm can not be applied for data edits because of different rule characteristics. This study proposed GraDit, a repair algorithm for data edits rule. First, we use bipartite-directed hypergraph as model representation of overall defined rules. These representation is used for getting interaction between violation rules and clean rules. On the other hand, we proposed undirected graph as violation representation. Our experimental study showed that algorithm with undirected graph as violation representation model gave better data quality than algorithm with undirected hypergraph as representation model.

From needs to goals and representations: Foundations for a unified theory of motivation, personality, and development.

PubMed

Dweck, Carol S

2017-11-01

Drawing on both classic and current approaches, I propose a theory that integrates motivation, personality, and development within one framework, using a common set of principles and mechanisms. The theory begins by specifying basic needs and by suggesting how, as people pursue need-fulfilling goals, they build mental representations of their experiences (beliefs, representations of emotions, and representations of action tendencies). I then show how these needs, goals, and representations can serve as the basis of both motivation and personality, and can help to integrate disparate views of personality. The article builds on this framework to provide a new perspective on development, particularly on the forces that propel development and the roles of nature and nurture. I argue throughout that the focus on representations provides an important entry point for change and growth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Phillips, Lawrence A.; Shaffer, Kyle J.; Arendt, Dustin L.

Language in social media is a dynamic system, constantly evolving and adapting, with words and concepts rapidly emerging, disappearing, and changing their meaning. These changes can be estimated using word representations in context, over time and across locations. A number of methods have been proposed to track these spatiotemporal changes but no general method exists to evaluate the quality of these representations. Previous work largely focused on qualitative evaluation, which we improve by proposing a set of visualizations that highlight changes in text representation over both space and time. We demonstrate usefulness of novel spatiotemporal representations to explore and characterizemore » specific aspects of the corpus of tweets collected from European countries over a two-week period centered around the terrorist attacks in Brussels in March 2016. In addition, we quantitatively evaluate spatiotemporal representations by feeding them into a downstream classification task – event type prediction. Thus, our work is the first to provide both intrinsic (qualitative) and extrinsic (quantitative) evaluation of text representations for spatiotemporal trends.« less

A Task-Dependent Causal Role for Low-Level Visual Processes in Spoken Word Comprehension

ERIC Educational Resources Information Center

Ostarek, Markus; Huettig, Falk

2017-01-01

It is well established that the comprehension of spoken words referring to object concepts relies on high-level visual areas in the ventral stream that build increasingly abstract representations. It is much less clear whether basic low-level visual representations are also involved. Here we asked in what task situations low-level visual…

The Neural Dynamics of Attentional Selection in Natural Scenes.

PubMed

Kaiser, Daniel; Oosterhof, Nikolaas N; Peelen, Marius V

2016-10-12

The human visual system can only represent a small subset of the many objects present in cluttered scenes at any given time, such that objects compete for representation. Despite these processing limitations, the detection of object categories in cluttered natural scenes is remarkably rapid. How does the brain efficiently select goal-relevant objects from cluttered scenes? In the present study, we used multivariate decoding of magneto-encephalography (MEG) data to track the neural representation of within-scene objects as a function of top-down attentional set. Participants detected categorical targets (cars or people) in natural scenes. The presence of these categories within a scene was decoded from MEG sensor patterns by training linear classifiers on differentiating cars and people in isolation and testing these classifiers on scenes containing one of the two categories. The presence of a specific category in a scene could be reliably decoded from MEG response patterns as early as 160 ms, despite substantial scene clutter and variation in the visual appearance of each category. Strikingly, we find that these early categorical representations fully depend on the match between visual input and top-down attentional set: only objects that matched the current attentional set were processed to the category level within the first 200 ms after scene onset. A sensor-space searchlight analysis revealed that this early attention bias was localized to lateral occipitotemporal cortex, reflecting top-down modulation of visual processing. These results show that attention quickly resolves competition between objects in cluttered natural scenes, allowing for the rapid neural representation of goal-relevant objects. Efficient attentional selection is crucial in many everyday situations. For example, when driving a car, we need to quickly detect obstacles, such as pedestrians crossing the street, while ignoring irrelevant objects. How can humans efficiently perform such tasks, given the multitude of objects contained in real-world scenes? Here we used multivariate decoding of magnetoencephalogaphy data to characterize the neural underpinnings of attentional selection in natural scenes with high temporal precision. We show that brain activity quickly tracks the presence of objects in scenes, but crucially only for those objects that were immediately relevant for the participant. These results provide evidence for fast and efficient attentional selection that mediates the rapid detection of goal-relevant objects in real-world environments. Copyright © 2016 the authors 0270-6474/16/3610522-07$15.00/0.

Multiple Sparse Representations Classification

PubMed Central

Plenge, Esben; Klein, Stefan S.; Niessen, Wiro J.; Meijering, Erik

2015-01-01

Sparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In this empirical study we propose to further leverage the redundancy of the learned dictionaries to achieve a more accurate classifier. In conventional SRC, each image pixel is associated with a small patch surrounding it. Using these patches, a dictionary is trained for each class in a supervised fashion. Commonly, redundant/overcomplete dictionaries are trained and image patches are sparsely represented by a linear combination of only a few of the dictionary elements. Given a set of trained dictionaries, a new patch is sparse coded using each of them, and subsequently assigned to the class whose dictionary yields the minimum residual energy. We propose a generalization of this scheme. The method, which we call multiple sparse representations classification (mSRC), is based on the observation that an overcomplete, class specific dictionary is capable of generating multiple accurate and independent estimates of a patch belonging to the class. So instead of finding a single sparse representation of a patch for each dictionary, we find multiple, and the corresponding residual energies provides an enhanced statistic which is used to improve classification. We demonstrate the efficacy of mSRC for three example applications: pixelwise classification of texture images, lumen segmentation in carotid artery magnetic resonance imaging (MRI), and bifurcation point detection in carotid artery MRI. We compare our method with conventional SRC, K-nearest neighbor, and support vector machine classifiers. The results show that mSRC outperforms SRC and the other reference methods. In addition, we present an extensive evaluation of the effect of the main mSRC parameters: patch size, dictionary size, and sparsity level. PMID:26177106

A conceptual framework of computations in mid-level vision

PubMed Central

Kubilius, Jonas; Wagemans, Johan; Op de Beeck, Hans P.

2014-01-01

If a picture is worth a thousand words, as an English idiom goes, what should those words—or, rather, descriptors—capture? What format of image representation would be sufficiently rich if we were to reconstruct the essence of images from their descriptors? In this paper, we set out to develop a conceptual framework that would be: (i) biologically plausible in order to provide a better mechanistic understanding of our visual system; (ii) sufficiently robust to apply in practice on realistic images; and (iii) able to tap into underlying structure of our visual world. We bring forward three key ideas. First, we argue that surface-based representations are constructed based on feature inference from the input in the intermediate processing layers of the visual system. Such representations are computed in a largely pre-semantic (prior to categorization) and pre-attentive manner using multiple cues (orientation, color, polarity, variation in orientation, and so on), and explicitly retain configural relations between features. The constructed surfaces may be partially overlapping to compensate for occlusions and are ordered in depth (figure-ground organization). Second, we propose that such intermediate representations could be formed by a hierarchical computation of similarity between features in local image patches and pooling of highly-similar units, and reestimated via recurrent loops according to the task demands. Finally, we suggest to use datasets composed of realistically rendered artificial objects and surfaces in order to better understand a model's behavior and its limitations. PMID:25566044

A conceptual framework of computations in mid-level vision.

PubMed

Kubilius, Jonas; Wagemans, Johan; Op de Beeck, Hans P

2014-01-01

If a picture is worth a thousand words, as an English idiom goes, what should those words-or, rather, descriptors-capture? What format of image representation would be sufficiently rich if we were to reconstruct the essence of images from their descriptors? In this paper, we set out to develop a conceptual framework that would be: (i) biologically plausible in order to provide a better mechanistic understanding of our visual system; (ii) sufficiently robust to apply in practice on realistic images; and (iii) able to tap into underlying structure of our visual world. We bring forward three key ideas. First, we argue that surface-based representations are constructed based on feature inference from the input in the intermediate processing layers of the visual system. Such representations are computed in a largely pre-semantic (prior to categorization) and pre-attentive manner using multiple cues (orientation, color, polarity, variation in orientation, and so on), and explicitly retain configural relations between features. The constructed surfaces may be partially overlapping to compensate for occlusions and are ordered in depth (figure-ground organization). Second, we propose that such intermediate representations could be formed by a hierarchical computation of similarity between features in local image patches and pooling of highly-similar units, and reestimated via recurrent loops according to the task demands. Finally, we suggest to use datasets composed of realistically rendered artificial objects and surfaces in order to better understand a model's behavior and its limitations.

A spatiotemporal decomposition strategy for personal home video management

NASA Astrophysics Data System (ADS)

Yi, Haoran; Kozintsev, Igor; Polito, Marzia; Wu, Yi; Bouguet, Jean-Yves; Nefian, Ara; Dulong, Carole

2007-01-01

With the advent and proliferation of low cost and high performance digital video recorder devices, an increasing number of personal home video clips are recorded and stored by the consumers. Compared to image data, video data is lager in size and richer in multimedia content. Efficient access to video content is expected to be more challenging than image mining. Previously, we have developed a content-based image retrieval system and the benchmarking framework for personal images. In this paper, we extend our personal image retrieval system to include personal home video clips. A possible initial solution to video mining is to represent video clips by a set of key frames extracted from them thus converting the problem into an image search one. Here we report that a careful selection of key frames may improve the retrieval accuracy. However, because video also has temporal dimension, its key frame representation is inherently limited. The use of temporal information can give us better representation for video content at semantic object and concept levels than image-only based representation. In this paper we propose a bottom-up framework to combine interest point tracking, image segmentation and motion-shape factorization to decompose the video into spatiotemporal regions. We show an example application of activity concept detection using the trajectories extracted from the spatio-temporal regions. The proposed approach shows good potential for concise representation and indexing of objects and their motion in real-life consumer video.

Evaluating and Evolving Metadata in Multiple Dialects

NASA Astrophysics Data System (ADS)

Kozimor, J.; Habermann, T.; Powers, L. A.; Gordon, S.

2016-12-01

Despite many long-term homogenization efforts, communities continue to develop focused metadata standards along with related recommendations and (typically) XML representations (aka dialects) for sharing metadata content. Different representations easily become obstacles to sharing information because each representation generally requires a set of tools and skills that are designed, built, and maintained specifically for that representation. In contrast, community recommendations are generally described, at least initially, at a more conceptual level and are more easily shared. For example, most communities agree that dataset titles should be included in metadata records although they write the titles in different ways. This situation has led to the development of metadata repositories that can ingest and output metadata in multiple dialects. As an operational example, the NASA Common Metadata Repository (CMR) includes three different metadata dialects (DIF, ECHO, and ISO 19115-2). These systems raise a new question for metadata providers: if I have a choice of metadata dialects, which should I use and how do I make that decision? We have developed a collection of metadata evaluation tools that can be used to evaluate metadata records in many dialects for completeness with respect to recommendations from many organizations and communities. We have applied these tools to over 8000 collection and granule metadata records in four different dialects. This large collection of identical content in multiple dialects enables us to address questions about metadata and dialect evolution and to answer those questions quantitatively. We will describe those tools and results from evaluating the NASA CMR metadata collection.

Parental representations and dimensions of personality: empirical relations and assessment implications.

PubMed

Pincus, A L; Ruiz, M A

1997-04-01

Research on the relations between parental representations, personality traits, and psychopathology was discussed with reference to their integration for clinical personality assessment. Empirical results linking parental representations assessed by the Structural Analysis of Social Behavior and the Five-Factor Model of personality traits in a young adult population supported the position that parental representations significantly relate to adult personality. Individuals whose parental representations were generally affiliative described themselves as less prone to emotional distress (lower neuroticism); more interpersonally oriented and experiencing of positive emotions (higher extraversion); more peaceable and trustworthy (higher agreeableness); and more dutiful, resourceful, and dependable (higher conscientiousness). Parental representations colored by autonomy granting and autonomy taking were related to higher levels of openness to experience but lower levels of conscientiousness and extraversion in self-descriptions. Assessment implications and an integrative assessment strategy were presented along with a clinical case example.

Ethnic variations regarding clinical profiles and symptom representation in prisoners with psychotic disorders.

PubMed

Denzel, A Dorina; Harte, Joke M; van den Bergh, Mattis; Scherder, Erik J A

2018-01-01

Black and minority ethnic (BME) groups are known to have higher prevalences of psychotic disorders and are over-represented in western penitentiaries and forensic psychiatric institutions. Research from regular mental healthcare settings suggests that they could show different and more severe psychotic symptoms. Aims To explore ethnic variations in severity of symptomatology of BME and non-BME detainees with psychotic disorders. In this study, 824 patients with psychotic disorders from seven different ethnic groups, imprisoned in a penitentiary psychiatric centre in the Netherlands, were compared on symptom severity and symptom representation using the BPRS-E clinical interview. Data were analysed by means of a multilevel analysis. BME patients with psychotic disorders are over-represented in forensic psychiatry, and symptom profiles of prisoners with psychotic disorders vary by ethnicity. Additionally, severity levels of overall psychopathology differ between ethnic groups: patients with an ethnic majority status show more severe levels of psychopathology compared with BME patients. There are differences in symptom severity and symptom profiles between BME patients and non-BME patients. Disregarding these differences could have an adverse effect on the outcome of the treatment. Possible explanations and clinical impact are discussed. Declaration of interest None.

Quantum probability ranking principle for ligand-based virtual screening.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening

NASA Astrophysics Data System (ADS)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Detailed Vibration Analysis of Pinion Gear with Time-Frequency Methods

NASA Technical Reports Server (NTRS)

Mosher, Marianne; Pryor, Anna H.; Lewicki, David G.

2003-01-01

In this paper, the authors show a detailed analysis of the vibration signal from the destructive testing of a spiral bevel gear and pinion pair containing seeded faults. The vibration signal is analyzed in the time domain, frequency domain and with four time-frequency transforms: the Short Time Frequency Transform (STFT), the Wigner-Ville Distribution with the Choi-Williams kernel (WV-CW), the Continuous Wavelet' Transform (CWT) and the Discrete Wavelet Transform (DWT). Vibration data of bevel gear tooth fatigue cracks, under a variety of operating load levels and damage conditions, are analyzed using these methods. A new metric for automatic anomaly detection is developed and can be produced from any systematic numerical representation of the vibration signals. This new metric reveals indications of gear damage with all of the time-frequency transforms, as well as time and frequency representations, on this data set. Analysis with the CWT detects changes in the signal at low torque levels not found with the other transforms. The WV-CW and CWT use considerably more resources than the STFT and the DWT. More testing of the new metric is needed to determine its value for automatic anomaly detection and to develop fault detection methods for the metric.

Neurocognitive mechanisms of statistical-sequential learning: what do event-related potentials tell us?

PubMed Central

Daltrozzo, Jerome; Conway, Christopher M.

2014-01-01

Statistical-sequential learning (SL) is the ability to process patterns of environmental stimuli, such as spoken language, music, or one’s motor actions, that unfold in time. The underlying neurocognitive mechanisms of SL and the associated cognitive representations are still not well understood as reflected by the heterogeneity of the reviewed cognitive models. The purpose of this review is: (1) to provide a general overview of the primary models and theories of SL, (2) to describe the empirical research – with a focus on the event-related potential (ERP) literature – in support of these models while also highlighting the current limitations of this research, and (3) to present a set of new lines of ERP research to overcome these limitations. The review is articulated around three descriptive dimensions in relation to SL: the level of abstractness of the representations learned through SL, the effect of the level of attention and consciousness on SL, and the developmental trajectory of SL across the life-span. We conclude with a new tentative model that takes into account these three dimensions and also point to several promising new lines of SL research. PMID:24994975

Graphic Display of Linguistic Information in English as a Foreign Language Reading

ERIC Educational Resources Information Center

Suzuki, Akio; Sato, Takeshi; Awazu, Shunji

2008-01-01

Two studies investigated the advantage and instructional effectiveness of the spatial graphic representation of an English sentence with coordinators over a linear sentential representation in English as a foreign language (EFL) reading settings. Experiment 1, Study 1, examined whether readers studying EFL could better comprehend the sentence--in…

A Unified Graphical Representation of Chemical Thermodynamics and Equilibrium

ERIC Educational Resources Information Center

Hanson, Robert M.

2012-01-01

During the years 1873-1879, J. Willard Gibbs published his now-famous set of articles that form the basis of the current perspective on chemical thermodynamics. The second article of this series, "A Method of Geometrical Representation of the Thermodynamic Properties of Substances by Means of Surfaces," published in 1873, is particularly notable…

The Council Estate: Representation, Space and the Potential for Performance

ERIC Educational Resources Information Center

Beswick, Katie

2011-01-01

The image of the archetypal housing estate is often used in popular representation, from documentary and television to music video, to symbolise the urban "grit" of contemporary inner-city life. In the theatre, urban political and "working-class" drama has been set on or around estates in attempts to deconstruct or expose the…

Creating the spatial framework for National Aquatic Resource Surveys (NARS): Melding National Aquatic Data Sets with Survey Requirements

EPA Science Inventory

The U.S. EPA’s National Aquatic Resource Surveys (NARS) require a consistent spatial representation of the resource target populations being monitored (i.e., rivers and streams, lakes, coastal waters, and wetlands). A sample frame is the GIS representation of this target popula...

A 2.5-D Representation of the Human Hand

ERIC Educational Resources Information Center

Longo, Matthew R.; Haggard, Patrick

2012-01-01

Primary somatosensory maps in the brain represent the body as a discontinuous, fragmented set of two-dimensional (2-D) skin regions. We nevertheless experience our body as a coherent three-dimensional (3-D) volumetric object. The links between these different aspects of body representation, however, remain poorly understood. Perceiving the body's…

Unitary vs Multiple Semantics: PET Studies of Word and Picture Processing

ERIC Educational Resources Information Center

Bright, P.; Moss, H.; Tyler, L. K.

2004-01-01

In this paper we examine a central issue in cognitive neuroscience: are there separate conceptual representations associated with different input modalities (e.g., Paivio, 1971, 1986; Warrington & Shallice, 1984) or do inputs from different modalities converge on to the same set of representations (e.g., Caramazza, Hillis, Rapp, & Romani, 1990;…

Differential equations for loop integrals in Baikov representation

NASA Astrophysics Data System (ADS)

Bosma, Jorrit; Larsen, Kasper J.; Zhang, Yang

2018-05-01

We present a proof that differential equations for Feynman loop integrals can always be derived in Baikov representation without involving dimension-shift identities. We moreover show that in a large class of two- and three-loop diagrams it is possible to avoid squared propagators in the intermediate steps of setting up the differential equations.

48 CFR 52.227-15 - Representation of Limited Rights Data and Restricted Computer Software.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Rights Data and Restricted Computer Software. 52.227-15 Section 52.227-15 Federal Acquisition Regulations... Computer Software. As prescribed in 27.409(c), insert the following provision: Representation of Limited Rights Data and Restricted Computer Software (DEC 2007) (a) This solicitation sets forth the Government's...

48 CFR 52.227-15 - Representation of Limited Rights Data and Restricted Computer Software.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Rights Data and Restricted Computer Software. 52.227-15 Section 52.227-15 Federal Acquisition Regulations... Computer Software. As prescribed in 27.409(c), insert the following provision: Representation of Limited Rights Data and Restricted Computer Software (DEC 2007) (a) This solicitation sets forth the Government's...

48 CFR 52.227-15 - Representation of Limited Rights Data and Restricted Computer Software.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Rights Data and Restricted Computer Software. 52.227-15 Section 52.227-15 Federal Acquisition Regulations... Computer Software. As prescribed in 27.409(c), insert the following provision: Representation of Limited Rights Data and Restricted Computer Software (DEC 2007) (a) This solicitation sets forth the Government's...

48 CFR 52.227-15 - Representation of Limited Rights Data and Restricted Computer Software.

Code of Federal Regulations, 2010 CFR

2010-10-01

... Rights Data and Restricted Computer Software. 52.227-15 Section 52.227-15 Federal Acquisition Regulations... Computer Software. As prescribed in 27.409(c), insert the following provision: Representation of Limited Rights Data and Restricted Computer Software (DEC 2007) (a) This solicitation sets forth the Government's...

48 CFR 52.227-15 - Representation of Limited Rights Data and Restricted Computer Software.

Code of Federal Regulations, 2011 CFR

2011-10-01

... Rights Data and Restricted Computer Software. 52.227-15 Section 52.227-15 Federal Acquisition Regulations... Computer Software. As prescribed in 27.409(c), insert the following provision: Representation of Limited Rights Data and Restricted Computer Software (DEC 2007) (a) This solicitation sets forth the Government's...

On the Psychological Reality of Underlying Phonological Representations.

ERIC Educational Resources Information Center

Trammell, Robert L.

In "The Sound Pattern of English," Chomsky and Halle maintain that the phonetic representation of most words can be generated from underlying forms and a small set of rules. Since these underlying forms are frequently close to the traditional spelling, we may hypothesize that literate native speakers share comparable internalized rules which…

Sensitivity to musical structure in the human brain

PubMed Central

McDermott, Josh H.; Norman-Haignere, Sam; Kanwisher, Nancy

2012-01-01

Evidence from brain-damaged patients suggests that regions in the temporal lobes, distinct from those engaged in lower-level auditory analysis, process the pitch and rhythmic structure in music. In contrast, neuroimaging studies targeting the representation of music structure have primarily implicated regions in the inferior frontal cortices. Combining individual-subject fMRI analyses with a scrambling method that manipulated musical structure, we provide evidence of brain regions sensitive to musical structure bilaterally in the temporal lobes, thus reconciling the neuroimaging and patient findings. We further show that these regions are sensitive to the scrambling of both pitch and rhythmic structure but are insensitive to high-level linguistic structure. Our results suggest the existence of brain regions with representations of musical structure that are distinct from high-level linguistic representations and lower-level acoustic representations. These regions provide targets for future research investigating possible neural specialization for music or its associated mental processes. PMID:23019005

Representations and evolutionary operators for the scheduling of pump operations in water distribution networks.

PubMed

López-Ibáñez, Manuel; Prasad, T Devi; Paechter, Ben

2011-01-01

Reducing the energy consumption of water distribution networks has never had more significance. The greatest energy savings can be obtained by carefully scheduling the operations of pumps. Schedules can be defined either implicitly, in terms of other elements of the network such as tank levels; or explicitly, by specifying the time during which each pump is on/off. The traditional representation of explicit schedules is a string of binary values with each bit representing pump on/off status during a particular time interval. In this paper, we formally define and analyze two new explicit representations based on time-controlled triggers, where the maximum number of pump switches is established beforehand and the schedule may contain fewer than the maximum number of switches. In these representations, a pump schedule is divided into a series of integers with each integer representing the number of hours for which a pump is active/inactive. This reduces the number of potential schedules compared to the binary representation, and allows the algorithm to operate on the feasible region of the search space. We propose evolutionary operators for these two new representations. The new representations and their corresponding operations are compared with the two most-used representations in pump scheduling, namely, binary representation and level-controlled triggers. A detailed statistical analysis of the results indicates which parameters have the greatest effect on the performance of evolutionary algorithms. The empirical results show that an evolutionary algorithm using the proposed representations is an improvement over the results obtained by a recent state of the art hybrid genetic algorithm for pump scheduling using level-controlled triggers.

Analogous selection processes in declarative and procedural working memory: N-2 list-repetition and task-repetition costs.

PubMed

Gade, Miriam; Souza, Alessandra S; Druey, Michel D; Oberauer, Klaus

2017-01-01

Working memory (WM) holds and manipulates representations for ongoing cognition. Oberauer (Psychology of Learning and Motivation, 51, 45-100, 2009) distinguishes between two analogous WM sub-systems: a declarative WM which handles the objects of thought, and a procedural WM which handles the representations of (cognitive) actions. Here, we assessed whether analogous effects are observed when participants switch between memory sets (declarative representations) and when they switch between task sets (procedural representations). One mechanism assumed to facilitate switching in procedural WM is the inhibition of previously used, but currently irrelevant task sets, as indexed by n-2 task-repetition costs (Mayr & Keele, Journal of Experimental Psychology: General, 129(1), 4-26, 2000). In this study we tested for an analogous effect in declarative WM. We assessed the evidence for n-2 list-repetition costs across eight experiments in which participants switched between memory lists to perform speeded classifications, mental arithmetic, or a local recognition test. N-2 list-repetition costs were obtained consistently in conditions assumed to increase interference between memory lists, and when lists formed chunks in long-term memory. Further analyses across experiments revealed a substantial contribution of episodic memory to n-2 list-repetition costs, thereby questioning the interpretation of n-2 repetition costs as reflecting inhibition. We reanalyzed the data of eight task-switching experiments, and observed that episodic memory also contributes to n-2 task-repetition costs. Taken together, these results show analogous processing principles in declarative and procedural WM, and question the relevance of inhibitory processes for efficient switching between mental sets.

Linking Language with Embodied and Teleological Representations of Action for Humanoid Cognition

PubMed Central

Lallee, Stephane; Madden, Carol; Hoen, Michel; Dominey, Peter Ford

2010-01-01

The current research extends our framework for embodied language and action comprehension to include a teleological representation that allows goal-based reasoning for novel actions. The objective of this work is to implement and demonstrate the advantages of a hybrid, embodied-teleological approach to action–language interaction, both from a theoretical perspective, and via results from human–robot interaction experiments with the iCub robot. We first demonstrate how a framework for embodied language comprehension allows the system to develop a baseline set of representations for processing goal-directed actions such as “take,” “cover,” and “give.” Spoken language and visual perception are input modes for these representations, and the generation of spoken language is the output mode. Moving toward a teleological (goal-based reasoning) approach, a crucial component of the new system is the representation of the subcomponents of these actions, which includes relations between initial enabling states, and final resulting states for these actions. We demonstrate how grammatical categories including causal connectives (e.g., because, if–then) can allow spoken language to enrich the learned set of state-action-state (SAS) representations. We then examine how this enriched SAS inventory enhances the robot's ability to represent perceived actions in which the environment inhibits goal achievement. The paper addresses how language comes to reflect the structure of action, and how it can subsequently be used as an input and output vector for embodied and teleological aspects of action. PMID:20577629

Extending Primitive Spatial Data Models to Include Semantics

NASA Astrophysics Data System (ADS)

Reitsma, F.; Batcheller, J.

2009-04-01

Our traditional geospatial data model involves associating some measurable quality, such as temperature, or observable feature, such as a tree, with a point or region in space and time. When capturing data we implicitly subscribe to some kind of conceptualisation. If we can make this explicit in an ontology and associate it with the captured data, we can leverage formal semantics to reason with the concepts represented in our spatial data sets. To do so, we extend our fundamental representation of geospatial data in a data model by including a URI in our basic data model that links it to our ontology defining our conceptualisation, We thus extend Goodchild et al's geo-atom [1] with the addition of a URI: (x, Z, z(x), URI) . This provides us with pixel or feature level knowledge and the ability to create layers of data from a set of pixels or features that might be drawn from a database based on their semantics. Using open source tools, we present a prototype that involves simple reasoning as a proof of concept. References [1] M.F. Goodchild, M. Yuan, and T.J. Cova. Towards a general theory of geographic representation in gis. International Journal of Geographical Information Science, 21(3):239-260, 2007.

Starting research in interaction design with visuals for low-functioning children in the autistic spectrum: a protocol.

PubMed

Parés, Narcís; Carreras, Anna; Durany, Jaume; Ferrer, Jaume; Freixa, Pere; Gómez, David; Kruglanski, Orit; Parés, Roc; Ribas, J Ignasi; Soler, Miquel; Sanjurjo, Alex

2006-04-01

On starting to think about interaction design for low-functioning persons in the autistic spectrum (PAS), especially children, one finds a number of questions that are difficult to answer: Can we typify the PAS user? Can we engage the user in interactive communication without generating frustrating or obsessive situations? What sort of visual stimuli can we provide? Will they prefer representational or abstract visual stimuli? Will they understand three-dimensional (3D) graphic representation? What sort of interfaces will they accept? Can we set ambitious goals such as education or therapy? Unfortunately, most of these questions have no answer yet. Hence, we decided to set an apparently simple goal: to design a "fun application," with no intention to reach the level of education or therapy. The goal was to be attained by giving the users a sense of agency--by providing first a sense of control in the interaction dialogue. Our approach to visual stimuli design has been based on the use of geometric, abstract, two-dimensional (2D), real-time computer graphics in a full-body, non-invasive, interactive space. The results obtained within the European-funded project MultiSensory Environment Design for an Interface between Autistic and Typical Expressiveness (MEDIATE) have been extremely encouraging.

Multivariate Pattern Analysis Reveals Category-Related Organization of Semantic Representations in Anterior Temporal Cortex.

PubMed

Malone, Patrick S; Glezer, Laurie S; Kim, Judy; Jiang, Xiong; Riesenhuber, Maximilian

2016-09-28

The neural substrates of semantic representation have been the subject of much controversy. The study of semantic representations is complicated by difficulty in disentangling perceptual and semantic influences on neural activity, as well as in identifying stimulus-driven, "bottom-up" semantic selectivity unconfounded by top-down task-related modulations. To address these challenges, we trained human subjects to associate pseudowords (TPWs) with various animal and tool categories. To decode semantic representations of these TPWs, we used multivariate pattern classification of fMRI data acquired while subjects performed a semantic oddball detection task. Crucially, the classifier was trained and tested on disjoint sets of TPWs, so that the classifier had to use the semantic information from the training set to correctly classify the test set. Animal and tool TPWs were successfully decoded based on fMRI activity in spatially distinct subregions of the left medial anterior temporal lobe (LATL). In addition, tools (but not animals) were successfully decoded from activity in the left inferior parietal lobule. The tool-selective LATL subregion showed greater functional connectivity with left inferior parietal lobule and ventral premotor cortex, indicating that each LATL subregion exhibits distinct patterns of connectivity. Our findings demonstrate category-selective organization of semantic representations in LATL into spatially distinct subregions, continuing the lateral-medial segregation of activation in posterior temporal cortex previously observed in response to images of animals and tools, respectively. Together, our results provide evidence for segregation of processing hierarchies for different classes of objects and the existence of multiple, category-specific semantic networks in the brain. The location and specificity of semantic representations in the brain are still widely debated. We trained human participants to associate specific pseudowords with various animal and tool categories, and used multivariate pattern classification of fMRI data to decode the semantic representations of the trained pseudowords. We found that: (1) animal and tool information was organized in category-selective subregions of medial left anterior temporal lobe (LATL); (2) tools, but not animals, were encoded in left inferior parietal lobe; and (3) LATL subregions exhibited distinct patterns of functional connectivity with category-related regions across cortex. Our findings suggest that semantic knowledge in LATL is organized in category-related subregions, providing evidence for the existence of multiple, category-specific semantic representations in the brain. Copyright © 2016 the authors 0270-6474/16/3610089-08$15.00/0.

Inter-level Scaffolding and Sequences of Representational Activities in Teaching a Chemical System with Graphical Simulations

NASA Astrophysics Data System (ADS)

Li, Na; Black, John B.

2016-10-01

Chemistry knowledge can be represented at macro-, micro- and symbolic levels, and learning a chemistry topic requires students to engage in multiple representational activities. This study focused on scaffolding for inter-level connection-making in learning chemistry knowledge with graphical simulations. We also tested whether different sequences of representational activities produced different student learning outcomes in learning a chemistry topic. A sample of 129 seventh graders participated in this study. In a simulation-based environment, participants completed three representational activities to learn several ideal gas law concepts. We conducted a 2 × 3 factorial design experiment. We compared two scaffolding conditions: (1) the inter- level scaffolding condition in which participants received inter-level questions and experienced the dynamic link function in the simulation-based environment and (2) the intra- level scaffolding condition in which participants received intra-level questions and did not experience the dynamic link function. We also compared three different sequences of representational activities: macro-symbolic-micro, micro-symbolic-macro and symbolic-micro-macro. For the scaffolding variable, we found that the inter- level scaffolding condition produced significantly better performance in both knowledge comprehension and application, compared to the intra- level scaffolding condition. For the sequence variable, we found that the macro-symbolic-micro sequence produced significantly better knowledge comprehension performance than the other two sequences; however, it did not benefit knowledge application performance. There was a trend that the treatment group who experienced inter- level scaffolding and the micro-symbolic-macro sequence achieved the best knowledge application performance.

Semantic richness effects in lexical decision: The role of feedback.

PubMed

Yap, Melvin J; Lim, Gail Y; Pexman, Penny M

2015-11-01

Across lexical processing tasks, it is well established that words with richer semantic representations are recognized faster. This suggests that the lexical system has access to meaning before a word is fully identified, and is consistent with a theoretical framework based on interactive and cascaded processing. Specifically, semantic richness effects are argued to be produced by feedback from semantic representations to lower-level representations. The present study explores the extent to which richness effects are mediated by feedback from lexical- to letter-level representations. In two lexical decision experiments, we examined the joint effects of stimulus quality and four semantic richness dimensions (imageability, number of features, semantic neighborhood density, semantic diversity). With the exception of semantic diversity, robust additive effects of stimulus quality and richness were observed for the targeted dimensions. Our results suggest that semantic feedback does not typically reach earlier levels of representation in lexical decision, and further reinforces the idea that task context modulates the processing dynamics of early word recognition processes.

Team Action Imagery and Team Cognition: Imagery of Game Situations and Required Team Actions Promotes a Functional Structure in Players' Representations of Team-Level Tactics.

PubMed

Frank, Cornelia; Linstromberg, Gian-Luca; Hennig, Linda; Heinen, Thomas; Schack, Thomas

2018-02-01

A team's cognitions of interpersonally coordinated actions are a crucial component for successful team performance. Here, we present an approach to practice team action by way of imagery and examine its impact on team cognitions in long-term memory. We investigated the impact of a 4-week team action imagery intervention on futsal players' mental representations of team-level tactics. Skilled futsal players were assigned to either an imagery training group or a no imagery training control group. Participants in the imagery training group practiced four team-level tactics by imagining team actions in specific game situations for three times a week. Results revealed that the imagery training group's representations were more similar to that of an expert representation after the intervention compared with the control group. This study indicates that team action imagery training can have a significant impact on players' tactical skill representations and thus order formation in long-term memory.

A brain-based account of "basic-level" concepts.

PubMed

Bauer, Andrew James; Just, Marcel Adam

2017-11-01

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts. Copyright © 2017 Elsevier Inc. All rights reserved.

Representational geometry: integrating cognition, computation, and the brain.

PubMed

Kriegeskorte, Nikolaus; Kievit, Rogier A

2013-08-01

The cognitive concept of representation plays a key role in theories of brain information processing. However, linking neuronal activity to representational content and cognitive theory remains challenging. Recent studies have characterized the representational geometry of neural population codes by means of representational distance matrices, enabling researchers to compare representations across stages of processing and to test cognitive and computational theories. Representational geometry provides a useful intermediate level of description, capturing both the information represented in a neuronal population code and the format in which it is represented. We review recent insights gained with this approach in perception, memory, cognition, and action. Analyses of representational geometry can compare representations between models and the brain, and promise to explain brain computation as transformation of representational similarity structure. Copyright © 2013 Elsevier Ltd. All rights reserved.

Inter-Level Scaffolding and Sequences of Representational Activities in Teaching a Chemical System with Graphical Simulations

ERIC Educational Resources Information Center

Li, Na; Black, John B.

2016-01-01

Chemistry knowledge can be represented at macro-, micro- and symbolic levels, and learning a chemistry topic requires students to engage in multiple representational activities. This study focused on scaffolding for inter-level connection-making in learning chemistry knowledge with graphical simulations. We also tested whether different sequences…

Effect of Computer Simulations at the Particulate and Macroscopic Levels on Students' Understanding of the Particulate Nature of Matter

ERIC Educational Resources Information Center

Tang, Hui; Abraham, Michael R.

2016-01-01

Computer-based simulations can help students visualize chemical representations and understand chemistry concepts, but simulations at different levels of representation may vary in effectiveness on student learning. This study investigated the influence of computer activities that simulate chemical reactions at different levels of representation…

Middle-Level Preservice Mathematics Teachers' Mental Representations of Classroom Floor Plans

ERIC Educational Resources Information Center

Matteson, Shirley M.; Ganesh, Bibi S.; Coward, Fanni L.; Patrick, Patricia

2012-01-01

This study reports the results of an innovative assignment in which preservice teachers' mental representations were examined through drawing floor plans of an "ideal middle-level mathematics classroom." The 41 middle-level mathematics preservice teachers created two floor plans, one at the beginning of the semester and the other for the…

A k-mer-based barcode DNA classification methodology based on spectral representation and a neural gas network.

PubMed

Fiannaca, Antonino; La Rosa, Massimo; Rizzo, Riccardo; Urso, Alfonso

2015-07-01

In this paper, an alignment-free method for DNA barcode classification that is based on both a spectral representation and a neural gas network for unsupervised clustering is proposed. In the proposed methodology, distinctive words are identified from a spectral representation of DNA sequences. A taxonomic classification of the DNA sequence is then performed using the sequence signature, i.e., the smallest set of k-mers that can assign a DNA sequence to its proper taxonomic category. Experiments were then performed to compare our method with other supervised machine learning classification algorithms, such as support vector machine, random forest, ripper, naïve Bayes, ridor, and classification tree, which also consider short DNA sequence fragments of 200 and 300 base pairs (bp). The experimental tests were conducted over 10 real barcode datasets belonging to different animal species, which were provided by the on-line resource "Barcode of Life Database". The experimental results showed that our k-mer-based approach is directly comparable, in terms of accuracy, recall and precision metrics, with the other classifiers when considering full-length sequences. In addition, we demonstrate the robustness of our method when a classification is performed task with a set of short DNA sequences that were randomly extracted from the original data. For example, the proposed method can reach the accuracy of 64.8% at the species level with 200-bp fragments. Under the same conditions, the best other classifier (random forest) reaches the accuracy of 20.9%. Our results indicate that we obtained a clear improvement over the other classifiers for the study of short DNA barcode sequence fragments. Copyright © 2015 Elsevier B.V. All rights reserved.

Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system

NASA Astrophysics Data System (ADS)

Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Ochoa-Rodriguez, Susana; Willems, Patrick; Ichiba, Abdellah; Wang, Lipen; Pina, Rui; Van Assel, Johan; Bruni, Guendalina; Murla Tuyls, Damian; ten Veldhuis, Marie-Claire

2017-04-01

Land use distribution and sewer system geometry exhibit complex scale dependent patterns in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. Such features are well grasped with fractal tools, which are based scale invariance and intrinsically designed to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper, they are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries in the framework of the NWE Interreg RainGain project (www.raingain.eu). The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m x 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. It appears that both sewer density and imperviousness exhibit scale invariant features that can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area, consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enables to quantify how well spatial structures of imperviousness are represented in the urban hydrological models.

Tracking the Spatiotemporal Neural Dynamics of Real-world Object Size and Animacy in the Human Brain.

PubMed

Khaligh-Razavi, Seyed-Mahdi; Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2018-06-07

Animacy and real-world size are properties that describe any object and thus bring basic order into our perception of the visual world. Here, we investigated how the human brain processes real-world size and animacy. For this, we applied representational similarity to fMRI and MEG data to yield a view of brain activity with high spatial and temporal resolutions, respectively. Analysis of fMRI data revealed that a distributed and partly overlapping set of cortical regions extending from occipital to ventral and medial temporal cortex represented animacy and real-world size. Within this set, parahippocampal cortex stood out as the region representing animacy and size stronger than most other regions. Further analysis of the detailed representational format revealed differences among regions involved in processing animacy. Analysis of MEG data revealed overlapping temporal dynamics of animacy and real-world size processing starting at around 150 msec and provided the first neuromagnetic signature of real-world object size processing. Finally, to investigate the neural dynamics of size and animacy processing simultaneously in space and time, we combined MEG and fMRI with a novel extension of MEG-fMRI fusion by representational similarity. This analysis revealed partly overlapping and distributed spatiotemporal dynamics, with parahippocampal cortex singled out as a region that represented size and animacy persistently when other regions did not. Furthermore, the analysis highlighted the role of early visual cortex in representing real-world size. A control analysis revealed that the neural dynamics of processing animacy and size were distinct from the neural dynamics of processing low-level visual features. Together, our results provide a detailed spatiotemporal view of animacy and size processing in the human brain.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions

NASA Astrophysics Data System (ADS)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.; Bazile, E.; Beau, I.; Blossey, P. N.; Boutle, I. A.; de Bruijn, C.; Cheng, A.; van der Dussen, J.; Fletcher, J.; Dal Gesso, S.; Jam, A.; Kawai, H.; Cheedela, S. K.; Larson, V. E.; Lefebvre, M.-P.; Lock, A. P.; Meyer, N. R.; de Roode, S. R.; de Rooy, W.; Sandu, I.; Xiao, H.; Xu, K.-M.

2017-10-01

Results are presented of the GASS/EUCLIPSE single-column model intercomparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate models for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pacific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transition process, making use of simple metrics to establish the model performance. Using this method, some longstanding problems in low-level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure, and the associated impact on radiative transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median exhibits the well-known "too few too bright" problem. The boundary-layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular, the vertical structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid parameterization.

Getting the picture: A mixed-methods inquiry into how visual representations are interpreted by students, incorporated within textbooks, and integrated into middle-school science classrooms

NASA Astrophysics Data System (ADS)

Lee, Victor Raymond

Modern-day middle school science textbooks are heavily populated with colorful images, technical diagrams, and other forms of visual representations. These representations are commonly perceived by educators to be useful aids to support student learning of unfamiliar scientific ideas. However, as the number of representations in science textbooks has seemingly increased in recent decades, concerns have been voiced that many current of these representations are actually undermining instructional goals; they may be introducing substantial conceptual and interpretive difficulties for students. To date, very little empirical work has been done to examine how the representations used in instructional materials have changed, and what influences these changes exert on student understanding. Furthermore, there has also been limited attention given to the extent to which current representational-use routines in science classrooms may mitigate or limit interpretive difficulties. This dissertation seeks to do three things: First, it examines the nature of the relationship between published representations and students' reasoning about the natural world. Second, it considers the ways in which representations are used in textbooks and how that has changed over a span of five decades. Third, this dissertation provides an in-depth look into how middle school science classrooms naturally use these visual representations and what kinds of support are being provided. With respect to the three goals of this dissertation, three pools of data were collected and analyzed for this study. First, interview data was collected in which 32 middle school students interpreted and reasoned with a set of more and less problematic published textbook representations. Quantitative analyses of the interview data suggest that, counter to what has been anticipated in the literature, there were no significant differences in the conceptualizations of students in the different groups. An accompanying qualitative analysis probes further into why this was the case. In addition to the interview data, a corpus of graphic representations from 34 science textbooks (published between 1943-2005) was catalogued and examined for compositional trends and changes. This historical textbook analysis of images and illustrations reveals that, consistent with expectations, there has indeed been an overall increase in the number of representations in a given instructional unit. Yet, despite the increase, there is very little shift in the instructional functions that those representations serve. Where the most dramatic changes appear are with the individual representations themselves and how they are used to relate scientific ideas to middle school students. Finally, a set of video-recorded classroom observations with three different teachers was collected in order to study representational-use routines. A numerical analysis of classroom episodes suggests that it is fairly common for the majority of representations that are used to appear fleetingly and not be discussed again. When representations are reused or reintroduced, a qualitative analysis reveals that they are often accompanied by interpretive support from the teacher, which may steer students away from misinterpretations.

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system.

PubMed

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J; Sawant, Amit; Ruan, Dan

2015-11-01

To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μrecon=-2.7×10(-3) mm(-1), σrecon=7.0×10(-3) mm(-1)) and (μCT=-2.5×10(-3) mm(-1), σCT=5.3×10(-3) mm(-1)), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.

3D hierarchical spatial representation and memory of multimodal sensory data

NASA Astrophysics Data System (ADS)

Khosla, Deepak; Dow, Paul A.; Huber, David J.

2009-04-01

This paper describes an efficient method and system for representing, processing and understanding multi-modal sensory data. More specifically, it describes a computational method and system for how to process and remember multiple locations in multimodal sensory space (e.g., visual, auditory, somatosensory, etc.). The multimodal representation and memory is based on a biologically-inspired hierarchy of spatial representations implemented with novel analogues of real representations used in the human brain. The novelty of the work is in the computationally efficient and robust spatial representation of 3D locations in multimodal sensory space as well as an associated working memory for storage and recall of these representations at the desired level for goal-oriented action. We describe (1) A simple and efficient method for human-like hierarchical spatial representations of sensory data and how to associate, integrate and convert between these representations (head-centered coordinate system, body-centered coordinate, etc.); (2) a robust method for training and learning a mapping of points in multimodal sensory space (e.g., camera-visible object positions, location of auditory sources, etc.) to the above hierarchical spatial representations; and (3) a specification and implementation of a hierarchical spatial working memory based on the above for storage and recall at the desired level for goal-oriented action(s). This work is most useful for any machine or human-machine application that requires processing of multimodal sensory inputs, making sense of it from a spatial perspective (e.g., where is the sensory information coming from with respect to the machine and its parts) and then taking some goal-oriented action based on this spatial understanding. A multi-level spatial representation hierarchy means that heterogeneous sensory inputs (e.g., visual, auditory, somatosensory, etc.) can map onto the hierarchy at different levels. When controlling various machine/robot degrees of freedom, the desired movements and action can be computed from these different levels in the hierarchy. The most basic embodiment of this machine could be a pan-tilt camera system, an array of microphones, a machine with arm/hand like structure or/and a robot with some or all of the above capabilities. We describe the approach, system and present preliminary results on a real-robotic platform.

How Do Students Misunderstand Number Representations?

ERIC Educational Resources Information Center

Herman, Geoffrey L.; Zilles, Craig; Loui, Michael C.

2011-01-01

We used both student interviews and diagnostic testing to reveal students' misconceptions about number representations in computing systems. This article reveals that students who have passed an undergraduate level computer organization course still possess surprising misconceptions about positional notations, two's complement representation, and…

In the right place at the right time: habitat representation in protected areas of South American Nothofagus-dominated plants after a dispersal constrained climate change scenario.

PubMed

Alarcón, Diego; Cavieres, Lohengrin A

2015-01-01

In order to assess the effects of climate change in temperate rainforest plants in southern South America in terms of habitat size, representation in protected areas, considering also if the expected impacts are similar for dominant trees and understory plant species, we used niche modeling constrained by species migration on 118 plant species, considering two groups of dominant trees and two groups of understory ferns. Representation in protected areas included Chilean national protected areas, private protected areas, and priority areas planned for future reserves, with two thresholds for minimum representation at the country level: 10% and 17%. With a 10% representation threshold, national protected areas currently represent only 50% of the assessed species. Private reserves are important since they increase up to 66% the species representation level. Besides, 97% of the evaluated species may achieve the minimum representation target only if the proposed priority areas were included. With the climate change scenario representation levels slightly increase to 53%, 69%, and 99%, respectively, to the categories previously mentioned. Thus, the current location of all the representation categories is useful for overcoming climate change by 2050. Climate change impacts on habitat size and representation of dominant trees in protected areas are not applicable to understory plants, highlighting the importance of assessing these effects with a larger number of species. Although climate change will modify the habitat size of plant species in South American temperate rainforests, it will have no significant impact in terms of the number of species adequately represented in Chile, where the implementation of the proposed reserves is vital to accomplish the present and future minimum representation. Our results also show the importance of using migration dispersal constraints to develop more realistic future habitat maps from climate change predictions.

In the Right Place at the Right Time: Habitat Representation in Protected Areas of South American Nothofagus-Dominated Plants after a Dispersal Constrained Climate Change Scenario

PubMed Central

Alarcón, Diego; Cavieres, Lohengrin A.

2015-01-01

In order to assess the effects of climate change in temperate rainforest plants in southern South America in terms of habitat size, representation in protected areas, considering also if the expected impacts are similar for dominant trees and understory plant species, we used niche modeling constrained by species migration on 118 plant species, considering two groups of dominant trees and two groups of understory ferns. Representation in protected areas included Chilean national protected areas, private protected areas, and priority areas planned for future reserves, with two thresholds for minimum representation at the country level: 10% and 17%. With a 10% representation threshold, national protected areas currently represent only 50% of the assessed species. Private reserves are important since they increase up to 66% the species representation level. Besides, 97% of the evaluated species may achieve the minimum representation target only if the proposed priority areas were included. With the climate change scenario representation levels slightly increase to 53%, 69%, and 99%, respectively, to the categories previously mentioned. Thus, the current location of all the representation categories is useful for overcoming climate change by 2050. Climate change impacts on habitat size and representation of dominant trees in protected areas are not applicable to understory plants, highlighting the importance of assessing these effects with a larger number of species. Although climate change will modify the habitat size of plant species in South American temperate rainforests, it will have no significant impact in terms of the number of species adequately represented in Chile, where the implementation of the proposed reserves is vital to accomplish the present and future minimum representation. Our results also show the importance of using migration dispersal constraints to develop more realistic future habitat maps from climate change predictions. PMID:25786226

A brain-based account of “basic-level” concepts

PubMed Central

Bauer, Andrew James; Just, Marcel Adam

2017-01-01

This study provides a brain-based account of how object concepts at an intermediate (basic) level of specificity are represented, offering an enriched view of what it means for a concept to be a basic-level concept, a research topic pioneered by Rosch and others (Rosch et al., 1976). Applying machine learning techniques to fMRI data, it was possible to determine the semantic content encoded in the neural representations of object concepts at basic and subordinate levels of abstraction. The representation of basic-level concepts (e.g. bird) was spatially broad, encompassing sensorimotor brain areas that encode concrete object properties, and also language and heteromodal integrative areas that encode abstract semantic content. The representation of subordinate-level concepts (robin) was less widely distributed, concentrated in perceptual areas that underlie concrete content. Furthermore, basic-level concepts were representative of their subordinates in that they were neurally similar to their typical but not atypical subordinates (bird was neurally similar to robin but not woodpecker). The findings provide a brain-based account of the advantages that basic-level concepts enjoy in everyday life over subordinate-level concepts: the basic level is a broad topographical representation that encompasses both concrete and abstract semantic content, reflecting the multifaceted yet intuitive meaning of basic-level concepts. PMID:28826947

Environment parameters and basic functions for floating-point computation

NASA Technical Reports Server (NTRS)

Brown, W. S.; Feldman, S. I.

1978-01-01

A language-independent proposal for environment parameters and basic functions for floating-point computation is presented. Basic functions are proposed to analyze, synthesize, and scale floating-point numbers. The model provides a small set of parameters and a small set of axioms along with sharp measures of roundoff error. The parameters and functions can be used to write portable and robust codes that deal intimately with the floating-point representation. Subject to underflow and overflow constraints, a number can be scaled by a power of the floating-point radix inexpensively and without loss of precision. A specific representation for FORTRAN is included.

Age, familiarity, and visual processing schemes.

PubMed

De Haven, D T; Roberts-Gray, C

1978-10-01

In a partial-report task adults and 5-yr.-old children identified stimuli of two types (common objects and familiar common objects) in two representations (black-and-white line drawings or full color photographs). It was hypothesized that familiar items and photographic representation would enhance the children's accuracy. Although both children and adults were more accurate when the stimuli were from the familiar set, children performed more accurate when the stimuli were from the familiar set, children performed poorly in all stimulus conditions. Results suggest that the age difference in this task reflects the "concrete" nature of the perceptual process in children.

The role of national identity representation in the relation between in-group identification and out-group derogation: ethnic versus civic representation.

PubMed

Meeus, Joke; Duriez, Bart; Vanbeselaere, Norbert; Boen, Filip

2010-06-01

Two studies investigated whether the content of in-group identity affects the relation between in-group identification and ethnic prejudice. The first study among university students, tested whether national identity representations (i.e., ethnic vs. civic) moderate or mediate the relation between Flemish in-group identification and ethnic prejudice. A moderation hypothesis is supported when those higher in identification who subscribe to a more ethnic representation display higher ethnic prejudice levels than those higher in identification who subscribe to a more civic representation. A mediation hypothesis is supported when those higher in identification tend towards one specific representation, which in turn, should predict ethnic prejudice. Results supported a mediation hypothesis and showed that the more respondents identified with the Flemish in-group, the more ethnic their identity representation, and the more they were inclined to display ethnic prejudice. The second study tested this mediation from a longitudinal perspective in a two-wave study among high school students. In-group identification at Time 1 predicted over-time changes in identity representation, which in turn, predicted changes in ethnic prejudice. In addition to this, changes in identity representation were predicted by initial ethnic prejudice levels. The implications of these findings are discussed.

Profile of students' comprehension of 3D molecule representation and its interconversion on chirality

NASA Astrophysics Data System (ADS)

Setyarini, M.; Liliasari, Kadarohman, Asep; Martoprawiro, Muhamad A.

2016-02-01

This study aims at describing (1) students' level comprehension; (2) factors causing difficulties to 3D comprehend molecule representation and its interconversion on chirality. Data was collected using multiple-choice test consisting of eight questions. The participants were required to give answers along with their reasoning. The test was developed based on the indicators of concept comprehension. The study was conducted to 161 college students enrolled in stereochemistry topic in the odd semester (2014/2015) from two LPTK (teacher training institutes) in Bandar Lampung and Gorontalo, and one public university in Bandung. The result indicates that college students' level of comprehension towards 3D molecule representations and its inter-conversion was 5% on high level, 22 % on the moderate level, and 73 % on the low level. The dominant factors identified as the cause of difficulties to comprehend 3D molecule representation and its interconversion were (i) the lack of spatial awareness, (ii) violation of absolute configuration determination rules, (iii) imprecise placement of observers, (iv) the lack of rotation operation, and (v) the lack of understanding of correlation between the representations. This study recommends that learning show more rigorous spatial awareness training tasks accompanied using dynamic visualization media of molecules associated. Also students learned using static molecular models can help them overcome their difficulties encountered.

Learning feature representations with a cost-relevant sparse autoencoder.

PubMed

Längkvist, Martin; Loutfi, Amy

2015-02-01

There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpose. However, for data sets with a high degree of noise, a large amount of the representational capacity in the autoencoder is used to minimize the reconstruction error for these noisy inputs. This paper proposes a method that improves the feature learning process by focusing on the task relevant information in the data. This selective attention is achieved by weighting the reconstruction error and reducing the influence of noisy inputs during the learning process. The proposed model is trained on a number of publicly available image data sets and the test error rate is compared to a standard sparse autoencoder and other methods, such as the denoising autoencoder and contractive autoencoder.

Diverse Region-Based CNN for Hyperspectral Image Classification.

PubMed

Zhang, Mengmeng; Li, Wei; Du, Qian

2018-06-01

Convolutional neural network (CNN) is of great interest in machine learning and has demonstrated excellent performance in hyperspectral image classification. In this paper, we propose a classification framework, called diverse region-based CNN, which can encode semantic context-aware representation to obtain promising features. With merging a diverse set of discriminative appearance factors, the resulting CNN-based representation exhibits spatial-spectral context sensitivity that is essential for accurate pixel classification. The proposed method exploiting diverse region-based inputs to learn contextual interactional features is expected to have more discriminative power. The joint representation containing rich spectral and spatial information is then fed to a fully connected network and the label of each pixel vector is predicted by a softmax layer. Experimental results with widely used hyperspectral image data sets demonstrate that the proposed method can surpass any other conventional deep learning-based classifiers and other state-of-the-art classifiers.

Culture-specific familiarity equally mediates action representations across cultures.

PubMed

Umla-Runge, Katja; Fu, Xiaolan; Wang, Lamei; Zimmer, Hubert D

2014-01-01

Previous studies have shown that we need to distinguish between means and end information about actions. It is unclear how these two subtypes of action information relate to each other with theoretical accounts postulating the superiority of end over means information and others linking separate means and end routes of processing to actions of differential meaningfulness. Action meaningfulness or familiarity differs between cultures. In a cross-cultural setting, we investigated how action familiarity influences recognition memory for means and end information. Object directed actions of differential familiarity were presented to Chinese and German participants. Action familiarity modulated the representation of means and end information in both cultures in the same way, although the effects were based on different stimulus sets. Our results suggest that, in the representation of actions in memory, end information is superordinate to means information. This effect is independent of culture whereas action familiarity is not.

GATOR: Requirements capturing of telephony features

NASA Technical Reports Server (NTRS)

Dankel, Douglas D., II; Walker, Wayne; Schmalz, Mark

1992-01-01

We are developing a natural language-based, requirements gathering system called GATOR (for the GATherer Of Requirements). GATOR assists in the development of more accurate and complete specifications of new telephony features. GATOR interacts with a feature designer who describes a new feature, set of features, or capability to be implemented. The system aids this individual in the specification process by asking for clarifications when potential ambiguities are present, by identifying potential conflicts with other existing features, and by presenting its understanding of the feature to the designer. Through user interaction with a model of the existing telephony feature set, GATOR constructs a formal representation of the new, 'to be implemented' feature. Ultimately GATOR will produce a requirements document and will maintain an internal representation of this feature to aid in future design and specification. This paper consists of three sections that describe (1) the structure of GATOR, (2) POND, GATOR's internal knowledge representation language, and (3) current research issues.

Acoustic and Lexical Representations for Affect Prediction in Spontaneous Conversations.

PubMed

Cao, Houwei; Savran, Arman; Verma, Ragini; Nenkova, Ani

2015-01-01

In this article we investigate what representations of acoustics and word usage are most suitable for predicting dimensions of affect|AROUSAL, VALANCE, POWER and EXPECTANCY|in spontaneous interactions. Our experiments are based on the AVEC 2012 challenge dataset. For lexical representations, we compare corpus-independent features based on psychological word norms of emotional dimensions, as well as corpus-dependent representations. We find that corpus-dependent bag of words approach with mutual information between word and emotion dimensions is by far the best representation. For the analysis of acoustics, we zero in on the question of granularity. We confirm on our corpus that utterance-level features are more predictive than word-level features. Further, we study more detailed representations in which the utterance is divided into regions of interest (ROI), each with separate representation. We introduce two ROI representations, which significantly outperform less informed approaches. In addition we show that acoustic models of emotion can be improved considerably by taking into account annotator agreement and training the model on smaller but reliable dataset. Finally we discuss the potential for improving prediction by combining the lexical and acoustic modalities. Simple fusion methods do not lead to consistent improvements over lexical classifiers alone but improve over acoustic models.

DD-PREF: a language for expressing preferences over sets

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri; desJardins, Marie

2005-01-01

We present a representation language, DD-PREF (for Diversity and Depth PREFrences), for specifying the desired diversity and depth of sets of objects where each object is represented as a vector of feature values.

Incidental orthographic learning during a color detection task.

PubMed

Protopapas, Athanassios; Mitsi, Anna; Koustoumbardis, Miltiadis; Tsitsopoulou, Sofia M; Leventi, Marianna; Seitz, Aaron R

2017-09-01

Orthographic learning refers to the acquisition of knowledge about specific spelling patterns forming words and about general biases and constraints on letter sequences. It is thought to occur by strengthening simultaneously activated visual and phonological representations during reading. Here we demonstrate that a visual perceptual learning procedure that leaves no time for articulation can result in orthographic learning evidenced in improved reading and spelling performance. We employed task-irrelevant perceptual learning (TIPL), in which the stimuli to be learned are paired with an easy task target. Assorted line drawings and difficult-to-spell words were presented in red color among sequences of other black-colored words and images presented in rapid succession, constituting a fast-TIPL procedure with color detection being the explicit task. In five experiments, Greek children in Grades 4-5 showed increased recognition of words and images that had appeared in red, both during and after the training procedure, regardless of within-training testing, and also when targets appeared in blue instead of red. Significant transfer to reading and spelling emerged only after increased training intensity. In a sixth experiment, children in Grades 2-3 showed generalization to words not presented during training that carried the same derivational affixes as in the training set. We suggest that reinforcement signals related to detection of the target stimuli contribute to the strengthening of orthography-phonology connections beyond earlier levels of visually-based orthographic representation learning. These results highlight the potential of perceptual learning procedures for the reinforcement of higher-level orthographic representations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

An essay on dreaming, psychical working out and working through.

PubMed

da Rocha Barros, Elias M

2002-10-01

In this paper the author attempts to expand the idea put forward by Freud who considered dreams as a special form of unconscious thinking. It is the author's contention that the psychical working-out function performed by dreams is a form of unconscious thinking, which transforms affects into memories and mental structures. He also attempts to clarify the way in which meaning is built and transformed in mental life. In that respect the unconscious internal world is seen as a form of unconscious thinking, a private theatre where meaning is generated and transformed. He focuses on what happens to feelings in dreams in connection with the meanings as a result of and an expression of the several stages of working through. The dream world is described as the setting where the mind gives expressive pictorial representation to the emotions involved in a conflict: a first step towards thinkability. The dreamwork also constitutes a process through which meaning is apprehended, built on and transformed at an expressive non-discursive level, based on representation through figurative/pictorial images. The author draws on Meltzer's formulation to conjecture that the working-through function of dreams, mainly in response to interpretations, is performed by a process of progression in formal qualities of the representations made available by dreaming in the form he has called affective pictograms. It is through progression in formal qualities of the representation that the thinking capabilities of the affective life develop and become part of the process of what is called metaphorically the metabolisation of emotional life. This process takes place through migration of meaning across various levels of mental process. In this perspective the analyst's interpretations of dreams effect what linguists call transmutation of the symbolic basis, a process that is necessary to help the mind to improve its capacity to think. Something expressed on the evocative plane and condensed into a pictographic image is then transformed into verbal language that expresses meaning. These conceptions are illustrated by a detailed clinical case.

Unitary vs multiple semantics: PET studies of word and picture processing.

PubMed

Bright, P; Moss, H; Tyler, L K

2004-06-01

In this paper we examine a central issue in cognitive neuroscience: are there separate conceptual representations associated with different input modalities (e.g., Paivio, 1971, 1986; Warrington & Shallice, 1984) or do inputs from different modalities converge on to the same set of representations (e.g., Caramazza, Hillis, Rapp, & Romani, 1990; Lambon Ralph, Graham, Patterson, & Hodges, 1999; Rapp, Hillis, & Caramazza, 1993)? We present an analysis of four PET studies (three semantic categorisation tasks and one lexical decision task), two of which employ words as stimuli and two of which employ pictures. Using conjunction analyses, we found robust semantic activation, common to both input modalities in anterior and medial aspects of the left fusiform gyrus, left parahippocampal and perirhinal cortices, and left inferior frontal gyrus (BA 47). There were modality-specific activations in both temporal poles (words) and occipitotemporal cortices (pictures). We propose that the temporal poles are involved in processing both words and pictures, but their engagement might be primarily determined by the level of specificity at which an object is processed. Activation in posterior temporal regions associated with picture processing most likely reflects intermediate, pre-semantic stages of visual processing. Our data are most consistent with a hierarchically structured, unitary system of semantic representations for both verbal and visual modalities, subserved by anterior regions of the inferior temporal cortex.

The ‘Morbid Anatomy’ of the Human Genome: Tracing the Observational and Representational Approaches of Postwar Genetics and Biomedicine The William Bynum Prize Essay

PubMed Central

Hogan, Andrew J.

2014-01-01

This paper explores evolving conceptions and depictions of the human genome among human and medical geneticists during the postwar period. Historians of science and medicine have shown significant interest in the use of informational approaches in postwar genetics, which treat the genome as an expansive digital data set composed of three billion DNA nucleotides. Since the 1950s, however, geneticists have largely interacted with the human genome at the microscopically visible level of chromosomes. Mindful of this, I examine the observational and representational approaches of postwar human and medical genetics. During the 1970s and 1980s, the genome increasingly came to be understood as, at once, a discrete part of the human anatomy and a standardised scientific object. This paper explores the role of influential medical geneticists in recasting the human genome as being a visible, tangible, and legible entity, which was highly relevant to traditional medical thinking and practice. I demonstrate how the human genome was established as an object amenable to laboratory and clinical research, and argue that the observational and representational approaches of postwar medical genetics reflect, more broadly, the interdisciplinary efforts underlying the development of contemporary biomedicine. PMID:25045177

Fractal analysis of urban environment: land use and sewer system

NASA Astrophysics Data System (ADS)

Gires, A.; Ochoa Rodriguez, S.; Van Assel, J.; Bruni, G.; Murla Tulys, D.; Wang, L.; Pina, R.; Richard, J.; Ichiba, A.; Willems, P.; Tchiguirinskaia, I.; ten Veldhuis, M. C.; Schertzer, D. J. M.

2014-12-01

Land use distribution are usually obtained by automatic processing of satellite and airborne pictures. The complexity of the obtained patterns which are furthermore scale dependent is enhanced in urban environment. This scale dependency is even more visible in a rasterized representation where only a unique class is affected to each pixel. A parameter commonly analysed in urban hydrology is the coefficient of imperviousness, which reflects the proportion of rainfall that will be immediately active in the catchment response. This coefficient is strongly scale dependent with a rasterized representation. This complex behaviour is well grasped with the help of the scale invariant notion of fractal dimension which enables to quantify the space occupied by a geometrical set (here the impervious areas) not only at a single scale but across all scales. This fractal dimension is also compared to the ones computed on the representation of the catchments with the help of operational semi-distributed models. Fractal dimensions of the corresponding sewer systems are also computed and compared with values found in the literature for natural river networks. This methodology is tested on 7 pilot sites of the European NWE Interreg IV RainGain project located in France, Belgium, Netherlands, United-Kingdom and Portugal. Results are compared between all the case study which exhibit different physical features (slope, level of urbanisation, population density...).

Kinematic decomposition and classification of octopus arm movements.

PubMed

Zelman, Ido; Titon, Myriam; Yekutieli, Yoram; Hanassy, Shlomi; Hochner, Binyamin; Flash, Tamar

2013-01-01

The octopus arm is a muscular hydrostat and due to its deformable and highly flexible structure it is capable of a rich repertoire of motor behaviors. Its motor control system uses planning principles and control strategies unique to muscular hydrostats. We previously reconstructed a data set of octopus arm movements from records of natural movements using a sequence of 3D curves describing the virtual backbone of arm configurations. Here we describe a novel representation of octopus arm movements in which a movement is characterized by a pair of surfaces that represent the curvature and torsion values of points along the arm as a function of time. This representation allowed us to explore whether the movements are built up of elementary kinematic units by decomposing each surface into a weighted combination of 2D Gaussian functions. The resulting Gaussian functions can be considered as motion primitives at the kinematic level of octopus arm movements. These can be used to examine underlying principles of movement generation. Here we used combination of such kinematic primitives to decompose different octopus arm movements and characterize several movement prototypes according to their composition. The representation and methodology can be applied to the movement of any organ which can be modeled by means of a continuous 3D curve.

Kinematic decomposition and classification of octopus arm movements

PubMed Central

Zelman, Ido; Titon, Myriam; Yekutieli, Yoram; Hanassy, Shlomi; Hochner, Binyamin; Flash, Tamar

2013-01-01

The octopus arm is a muscular hydrostat and due to its deformable and highly flexible structure it is capable of a rich repertoire of motor behaviors. Its motor control system uses planning principles and control strategies unique to muscular hydrostats. We previously reconstructed a data set of octopus arm movements from records of natural movements using a sequence of 3D curves describing the virtual backbone of arm configurations. Here we describe a novel representation of octopus arm movements in which a movement is characterized by a pair of surfaces that represent the curvature and torsion values of points along the arm as a function of time. This representation allowed us to explore whether the movements are built up of elementary kinematic units by decomposing each surface into a weighted combination of 2D Gaussian functions. The resulting Gaussian functions can be considered as motion primitives at the kinematic level of octopus arm movements. These can be used to examine underlying principles of movement generation. Here we used combination of such kinematic primitives to decompose different octopus arm movements and characterize several movement prototypes according to their composition. The representation and methodology can be applied to the movement of any organ which can be modeled by means of a continuous 3D curve. PMID:23745113

Setting apart the amateur from the professional: maintaining the value of standardised representational photography.

PubMed

Banks, Debbie

2014-10-01

The purpose of this paper is to discuss the importance of standard representational photography in clinical photography and its aid in maintaining the gold standard in the medical illustration profession. it is important that professionals are aware of potential threats to good practice with many areas identified in the article.

77 FR 38701 - Self-Regulatory Organizations; NYSE Arca, Inc.; Notice of Filing of Proposed Rule Change Amending...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

... process for the nomination and selection of fair representation directors for the NYSE Arca Board of Directors (``NYSE Arca Board''), and NYSE Arca Equities Rule 3.2 sets forth a similar process for the nomination and selection of fair representation directors for the NYSE Arca Equities Board of Directors...

Representations of the Nature of Scientific Knowledge in Turkish Biology Textbooks

ERIC Educational Resources Information Center

Irez, Serhat

2016-01-01

Considering the impact of textbooks on learning, this study set out to assess representations of the nature of scientific knowledge in Turkish 9th grade biology textbooks. To this end, the ten most commonly used 9th grade biology textbooks were analyzed. A qualitative research approach was utilized and the textbooks were analyzed using…

Critical Media Literacy in Middle School: Exploring the Politics of Representation

ERIC Educational Resources Information Center

Gainer, Jesse S.

2010-01-01

This article explores issues of critical media literacy with middle school students in an urban setting in the United States. The author focuses on data from a qualitative study engaging students in the reading and writing of video texts. The article examines intersections of issues relating to the "crisis of representation" in social science…

Critical Perspectives on Youth Digital Media Production: "Voice" and Representation in Educational Contexts

ERIC Educational Resources Information Center

Dahya, Negin

2017-01-01

This paper offers a critical discussion on voice and representation in youth digital media production in educational settings. The paper builds on existing calls from digital media and visual studies scholars to approach youth-made media with greater attention to context in production practices. In this discussion, the author addresses the…

Tongue Motion Averaging from Contour Sequences

ERIC Educational Resources Information Center

Li, Min; Kambhamettu, Chandra; Stone, Maureen

2005-01-01

In this paper, a method to get the best representation of a speech motion from several repetitions is presented. Each repetition is a representation of the same speech captured at different times by sequence of ultrasound images and is composed of a set of 2D spatio-temporal contours. These 2D contours in different repetitions are time aligned…

The End of Innocence: Historiography and Representation in the Discursive Practice of LD

ERIC Educational Resources Information Center

Artiles, Alfredo J.

2004-01-01

In this article, I discuss two interrelated sets of challenges that the discursive practice of learning disability (LD) will need to address, namely, issues associated with the development of a historiography of special education and a more complex understanding of representation issues. I use social theory to address these challenges and raise…

DHM simulation in virtual environments: a case-study on control room design.

PubMed

Zamberlan, M; Santos, V; Streit, P; Oliveira, J; Cury, R; Negri, T; Pastura, F; Guimarães, C; Cid, G

2012-01-01

This paper will present the workflow developed for the application of serious games in the design of complex cooperative work settings. The project was based on ergonomic studies and development of a control room among participative design process. Our main concerns were the 3D human virtual representation acquired from 3D scanning, human interaction, workspace layout and equipment designed considering ergonomics standards. Using Unity3D platform to design the virtual environment, the virtual human model can be controlled by users on dynamic scenario in order to evaluate the new work settings and simulate work activities. The results obtained showed that this virtual technology can drastically change the design process by improving the level of interaction between final users and, managers and human factors team.

Color perception involves color representations firstly at a semantic level and then at a lexical level.

PubMed

Heurley, Loïc P; Brouillet, Thibaut; Chesnoy, Gabrielle; Brouillet, Denis

2013-03-01

Studies and models have suggested that color perception first involves access to semantic representations of color. This result leads to two questions: (1) is knowledge able to influence the perception of color when associated with a color? and (2) can the perception of color really involve only semantic representations? We developed an experiment where participants have to discriminate the color of a patch (yellow vs. green). The target patch is preceded either by a black-and-white line drawing or by a word representing a natural object associated with the same or a different color (banana vs. frog). We expected a priming effect for pictures because, with a 350-ms SOA, they only involve access to semantic representations of color, whereas words seem only elicit an access to lexical representations. As expected, we found a priming effect for pictures, but also for words. Moreover, we found a general slowdown of response times in the word-prime-condition suggesting the need of an additional processing step to produce priming. In a second experiment, we manipulated the SOA in order to preclude a semantic access in the word-prime-condition that could explain the additional step of processing. We also found a priming effect, suggesting that interaction with perception occurs at a lexical level and the additional step occurs at a color perception level. In the discussion, we develop a new model of color perception assuming that color perception involves access to semantic representations and then access to lexical representations.

Super Normal Vector for Human Activity Recognition with Depth Cameras.

PubMed

Yang, Xiaodong; Tian, YingLi

2017-05-01

The advent of cost-effectiveness and easy-operation depth cameras has facilitated a variety of visual recognition tasks including human activity recognition. This paper presents a novel framework for recognizing human activities from video sequences captured by depth cameras. We extend the surface normal to polynormal by assembling local neighboring hypersurface normals from a depth sequence to jointly characterize local motion and shape information. We then propose a general scheme of super normal vector (SNV) to aggregate the low-level polynormals into a discriminative representation, which can be viewed as a simplified version of the Fisher kernel representation. In order to globally capture the spatial layout and temporal order, an adaptive spatio-temporal pyramid is introduced to subdivide a depth video into a set of space-time cells. In the extensive experiments, the proposed approach achieves superior performance to the state-of-the-art methods on the four public benchmark datasets, i.e., MSRAction3D, MSRDailyActivity3D, MSRGesture3D, and MSRActionPairs3D.

Diagrammatic technique for calculating matrix elements of collective operators in superradiance. [eigenstates for N two-level atom systems

NASA Technical Reports Server (NTRS)

Lee, C. T.

1975-01-01

Adopting the so-called genealogical construction, one can express the eigenstates of collective operators corresponding to a specified mode for an N-atom system in terms of those for an (N-1) atom system. Using these Dicke states as bases and using the Wigner-Eckart theorem, a matrix element of a collective operator of an arbitrary mode can be written as the product of an m-dependent factor and an m-independent reduced matrix element (RME). A set of recursion formulas for the RME is obtained. A graphical representation of the RME on the branching diagram for binary irreducible representations of permutation groups is then introduced. This gives a simple and systematic way of calculating the RME. This method is especially useful when the cooperation number r is close to N/2, where almost exact asymptotic expressions can be obtained easily. The result shows explicity the geometry dependence of superradiance and the relative importance of r-conserving and r-nonconserving processes.

Polynomic nonlinear dynamical systems - A residual sensitivity method for model reduction

NASA Technical Reports Server (NTRS)

Yurkovich, S.; Bugajski, D.; Sain, M.

1985-01-01

The motivation for using polynomic combinations of system states and inputs to model nonlinear dynamics systems is founded upon the classical theories of analysis and function representation. A feature of such representations is the need to make available all possible monomials in these variables, up to the degree specified, so as to provide for the description of widely varying functions within a broad class. For a particular application, however, certain monomials may be quite superfluous. This paper examines the possibility of removing monomials from the model in accordance with the level of sensitivity displayed by the residuals to their absence. Critical in these studies is the effect of system input excitation, and the effect of discarding monomial terms, upon the model parameter set. Therefore, model reduction is approached iteratively, with inputs redesigned at each iteration to ensure sufficient excitation of remaining monomials for parameter approximation. Examples are reported to illustrate the performance of such model reduction approaches.

Aversive Learning Modulates Cortical Representations of Object Categories

PubMed Central

Dunsmoor, Joseph E.; Kragel, Philip A.; Martin, Alex; LaBar, Kevin S.

2014-01-01

Experimental studies of conditioned learning reveal activity changes in the amygdala and unimodal sensory cortex underlying fear acquisition to simple stimuli. However, real-world fears typically involve complex stimuli represented at the category level. A consequence of category-level representations of threat is that aversive experiences with particular category members may lead one to infer that related exemplars likewise pose a threat, despite variations in physical form. Here, we examined the effect of category-level representations of threat on human brain activation using 2 superordinate categories (animals and tools) as conditioned stimuli. Hemodynamic activity in the amygdala and category-selective cortex was modulated by the reinforcement contingency, leading to widespread fear of different exemplars from the reinforced category. Multivariate representational similarity analyses revealed that activity patterns in the amygdala and object-selective cortex were more similar among exemplars from the threat versus safe category. Learning to fear animate objects was additionally characterized by enhanced functional coupling between the amygdala and fusiform gyrus. Finally, hippocampal activity co-varied with object typicality and amygdala activation early during training. These findings provide novel evidence that aversive learning can modulate category-level representations of object concepts, thereby enabling individuals to express fear to a range of related stimuli. PMID:23709642

A ganglion-cell-based primary image representation method and its contribution to object recognition

NASA Astrophysics Data System (ADS)

Wei, Hui; Dai, Zhi-Long; Zuo, Qing-Song

2016-10-01

A visual stimulus is represented by the biological visual system at several levels: in the order from low to high levels, they are: photoreceptor cells, ganglion cells (GCs), lateral geniculate nucleus cells and visual cortical neurons. Retinal GCs at the early level need to represent raw data only once, but meet a wide number of diverse requests from different vision-based tasks. This means the information representation at this level is general and not task-specific. Neurobiological findings have attributed this universal adaptation to GCs' receptive field (RF) mechanisms. For the purposes of developing a highly efficient image representation method that can facilitate information processing and interpretation at later stages, here we design a computational model to simulate the GC's non-classical RF. This new image presentation method can extract major structural features from raw data, and is consistent with other statistical measures of the image. Based on the new representation, the performances of other state-of-the-art algorithms in contour detection and segmentation can be upgraded remarkably. This work concludes that applying sophisticated representation schema at early state is an efficient and promising strategy in visual information processing.

WURCS 2.0 Update To Encapsulate Ambiguous Carbohydrate Structures.

PubMed

Matsubara, Masaaki; Aoki-Kinoshita, Kiyoko F; Aoki, Nobuyuki P; Yamada, Issaku; Narimatsu, Hisashi

2017-04-24

Accurate representation of structural ambiguity is important for storing carbohydrate structures containing varying levels of ambiguity in the literature and databases. Although many representations for carbohydrates have been developed in the past, a generalized but discrete representation format did not exist. We had previously developed the Web3 Unique Representation of Carbohydrate Structures (WURCS) in an attempt to define a generalizable and unique linear representation for carbohydrate structures. However, it lacked sufficient rules to uniquely describe ambiguous structures. In this work, we updated WURCS to handle such ambiguous monosaccharide structures. In particular, to handle structural ambiguity around (potential) carbonyl groups incidental to the carbohydrate analysis, we defined a representation of backbone carbons containing atomic-level ambiguity. As a result, we show that WURCS 2.0 can represent a wider variety of carbohydrate structures containing ambiguous monosaccharides, such as those whose ring closure is undefined or whose anomeric information is only known. This new format provides a representation of carbohydrates that was not possible before, and it is currently being used by the International Glycan Structure Repository GlyTouCan.

Under-Representation in Nationally Representative Secondary Data

ERIC Educational Resources Information Center

Frederick, Karen; Barnard-Brak, Lucy; Sulak, Tracey

2012-01-01

There has been a significant increase in the use of secondary data sets. Many such data sets purport to be nationally representative. Secondary data sets include research commissioned by the National Center for Education Statistics, the Centers for Disease Control, and other public entities. Research increasingly utilizes these secondary data in…

DHM and serious games: a case-study oil and gas laboratories.

PubMed

Santos, V; Zamberlan, M; Streit, P; Oliveira, J; Guimarães, C; Pastura, F; Cid, G

2012-01-01

The aim in this paper is to present a research on the application of serious games for the design of laboratories in the oil and gas industries. The focus is in human virtual representation acquired from 3D scanning, human interaction, workspace layout and equipment designed considering ergonomics standards. The laboratory studies were simulated in Unity3D platform, which allows the users to control the DHM1 on the dynamic virtual scenario, in order to simulate work activities. This methodology can change the design process by improving the level of interaction between final users, managers and human factor teams. That helps to better visualize future work settings and improve the level of participation between all stakeholders.

The ARES High-level Intermediate Representation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moss, Nicholas David

The LLVM intermediate representation (IR) lacks semantic constructs for depicting common high-performance operations such as parallel and concurrent execution, communication and synchronization. Currently, representing such semantics in LLVM requires either extending the intermediate form (a signi cant undertaking) or the use of ad hoc indirect means such as encoding them as intrinsics and/or the use of metadata constructs. In this paper we discuss a work in progress to explore the design and implementation of a new compilation stage and associated high-level intermediate form that is placed between the abstract syntax tree and when it is lowered to LLVM's IR. Thismore » highlevel representation is a superset of LLVM IR and supports the direct representation of these common parallel computing constructs along with the infrastructure for supporting analysis and transformation passes on this representation.« less

Probabilistic Models for Solar Particle Events

NASA Technical Reports Server (NTRS)

Adams, James H., Jr.; Dietrich, W. F.; Xapsos, M. A.; Welton, A. M.

2009-01-01

Probabilistic Models of Solar Particle Events (SPEs) are used in space mission design studies to provide a description of the worst-case radiation environment that the mission must be designed to tolerate.The models determine the worst-case environment using a description of the mission and a user-specified confidence level that the provided environment will not be exceeded. This poster will focus on completing the existing suite of models by developing models for peak flux and event-integrated fluence elemental spectra for the Z>2 elements. It will also discuss methods to take into account uncertainties in the data base and the uncertainties resulting from the limited number of solar particle events in the database. These new probabilistic models are based on an extensive survey of SPE measurements of peak and event-integrated elemental differential energy spectra. Attempts are made to fit the measured spectra with eight different published models. The model giving the best fit to each spectrum is chosen and used to represent that spectrum for any energy in the energy range covered by the measurements. The set of all such spectral representations for each element is then used to determine the worst case spectrum as a function of confidence level. The spectral representation that best fits these worst case spectra is found and its dependence on confidence level is parameterized. This procedure creates probabilistic models for the peak and event-integrated spectra.

A Framework for Hierarchical Perception-Action Learning Utilizing Fuzzy Reasoning.

PubMed

Windridge, David; Felsberg, Michael; Shaukat, Affan

2013-02-01

Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.

View-Tolerant Face Recognition and Hebbian Learning Imply Mirror-Symmetric Neural Tuning to Head Orientation.

PubMed

Leibo, Joel Z; Liao, Qianli; Anselmi, Fabio; Freiwald, Winrich A; Poggio, Tomaso

2017-01-09

The primate brain contains a hierarchy of visual areas, dubbed the ventral stream, which rapidly computes object representations that are both specific for object identity and robust against identity-preserving transformations, like depth rotations [1, 2]. Current computational models of object recognition, including recent deep-learning networks, generate these properties through a hierarchy of alternating selectivity-increasing filtering and tolerance-increasing pooling operations, similar to simple-complex cells operations [3-6]. Here, we prove that a class of hierarchical architectures and a broad set of biologically plausible learning rules generate approximate invariance to identity-preserving transformations at the top level of the processing hierarchy. However, all past models tested failed to reproduce the most salient property of an intermediate representation of a three-level face-processing hierarchy in the brain: mirror-symmetric tuning to head orientation [7]. Here, we demonstrate that one specific biologically plausible Hebb-type learning rule generates mirror-symmetric tuning to bilaterally symmetric stimuli, like faces, at intermediate levels of the architecture and show why it does so. Thus, the tuning properties of individual cells inside the visual stream appear to result from group properties of the stimuli they encode and to reflect the learning rules that sculpted the information-processing system within which they reside. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST.

PubMed

Futter, M N; Whitehead, P G; Sarkar, S; Rodda, H; Crossman, J

2015-06-01

There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.

39. Lobby fireplace set in northwest corner with the entablature ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

39. Lobby fireplace set in northwest corner with the entablature decorated with contemporary representations of Stilwell, et. al. (see #40) - Fort Ord, Soldiers' Club, California State Highway 1 near Eighth Street, Seaside, Monterey County, CA

Method and apparatus for modeling interactions

DOEpatents

Xavier, Patrick G.

2000-08-08

A method and apparatus for modeling interactions between bodies. The method comprises representing two bodies undergoing translations and rotations by two hierarchical swept volume representations. Interactions such as nearest approach and collision can be modeled based on the swept body representations. The present invention can serve as a practical tool in motion planning, CAD systems, simulation systems, safety analysis, and applications that require modeling time-based interactions. A body can be represented in the present invention by a union of convex polygons and convex polyhedra. As used generally herein, polyhedron includes polygon, and polyhedra includes polygons. The body undergoing translation can be represented by a swept body representation, where the swept body representation comprises a hierarchical bounding volume representation whose leaves each contain a representation of the region swept by a section of the body during the translation, and where the union of the regions is a superset of the region swept by the surface of the body during translation. Interactions between two bodies thus represented can be modeled by modeling interactions between the convex hulls of the finite sets of discrete points in the swept body representations.

The DTW-based representation space for seismic pattern classification

NASA Astrophysics Data System (ADS)

Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario

2015-12-01

Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.

Social identity contingencies: how diversity cues signal threat or safety for African Americans in mainstream institutions.

PubMed

Purdie-Vaughns, Valerie; Steele, Claude M; Davies, Paul G; Ditlmann, Ruth; Crosby, Jennifer Randall

2008-04-01

This research demonstrates that people at risk of devaluation based on group membership are attuned to cues that signal social identity contingencies--judgments, stereotypes, opportunities, restrictions, and treatments that are tied to one's social identity in a given setting. In 3 experiments, African American professionals were attuned to minority representation and diversity philosophy cues when they were presented as a part of workplace settings. Low minority representation cues coupled with colorblindness (as opposed to valuing diversity) led African American professionals to perceive threatening identity contingencies and to distrust the setting (Experiment 1). The authors then verified that the mechanism mediating the effect of setting cues on trust was identity contingent evaluations (Experiments 2 & 3). The power of social identity contingencies as they relate to underrepresented groups in mainstream institutions is discussed. (c) 2008 APA, all rights reserved.

Natural language processing and the representation of clinical data.

PubMed Central

Sager, N; Lyman, M; Bucknall, C; Nhan, N; Tick, L J

1994-01-01

OBJECTIVE: Develop a representation of clinical observations and actions and a method of processing free-text patient documents to facilitate applications such as quality assurance. DESIGN: The Linguistic String Project (LSP) system of New York University utilizes syntactic analysis, augmented by a sublanguage grammar and an information structure that are specific to the clinical narrative, to map free-text documents into a database for querying. MEASUREMENTS: Information precision (I-P) and information recall (I-R) were measured for queries for the presence of 13 asthma-health-care quality assurance criteria in a database generated from 59 discharge letters. RESULTS: I-P, using counts of major errors only, was 95.7% for the 28-letter training set and 98.6% for the 31-letter test set. I-R, using counts of major omissions only, was 93.9% for the training set and 92.5% for the test set. PMID:7719796

Improving Representational Competence with Concrete Models

ERIC Educational Resources Information Center

Stieff, Mike; Scopelitis, Stephanie; Lira, Matthew E.; DeSutter, Dane

2016-01-01

Representational competence is a primary contributor to student learning in science, technology, engineering, and math (STEM) disciplines and an optimal target for instruction at all educational levels. We describe the design and implementation of a learning activity that uses concrete models to improve students' representational competence and…

Spatial frequency supports the emergence of categorical representations in visual cortex during natural scene perception.

PubMed

Dima, Diana C; Perry, Gavin; Singh, Krish D

2018-06-11

In navigating our environment, we rapidly process and extract meaning from visual cues. However, the relationship between visual features and categorical representations in natural scene perception is still not well understood. Here, we used natural scene stimuli from different categories and filtered at different spatial frequencies to address this question in a passive viewing paradigm. Using representational similarity analysis (RSA) and cross-decoding of magnetoencephalography (MEG) data, we show that categorical representations emerge in human visual cortex at ∼180 ms and are linked to spatial frequency processing. Furthermore, dorsal and ventral stream areas reveal temporally and spatially overlapping representations of low and high-level layer activations extracted from a feedforward neural network. Our results suggest that neural patterns from extrastriate visual cortex switch from low-level to categorical representations within 200 ms, highlighting the rapid cascade of processing stages essential in human visual perception. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Psychology of knowledge representation.

PubMed

Grimm, Lisa R

2014-05-01

Every cognitive enterprise involves some form of knowledge representation. Humans represent information about the external world and internal mental states, like beliefs and desires, and use this information to meet goals (e.g., classification or problem solving). Unfortunately, researchers do not have direct access to mental representations. Instead, cognitive scientists design experiments and implement computational models to develop theories about the mental representations present during task performance. There are several main types of mental representation and corresponding processes that have been posited: spatial, feature, network, and structured. Each type has a particular structure and a set of processes that are capable of accessing and manipulating information within the representation. The structure and processes determine what information can be used during task performance and what information has not been represented at all. As such, the different types of representation are likely used to solve different kinds of tasks. For example, structured representations are more complex and computationally demanding, but are good at representing relational information. Researchers interested in human psychology would benefit from considering how knowledge is represented in their domain of inquiry. For further resources related to this article, please visit the WIREs website. The author has declared no conflicts of interest for this article. © 2014 John Wiley & Sons, Ltd.

Using Concrete Manipulatives in Mathematical Instruction

ERIC Educational Resources Information Center

Jones, Julie P.; Tiller, Margaret

2017-01-01

Concrete, Representational, Abstract (CRA) instruction is a process for teaching and learning mathematical concepts. Starting with manipulation of concrete materials (counters, beans, Unifix cubes), the process moves students to the representational level (tallies, dots, stamps), and peaks at the abstract level, at which numbers and symbols are…

EliXR-TIME: A Temporal Knowledge Representation for Clinical Research Eligibility Criteria.

PubMed

Boland, Mary Regina; Tu, Samson W; Carini, Simona; Sim, Ida; Weng, Chunhua

2012-01-01

Effective clinical text processing requires accurate extraction and representation of temporal expressions. Multiple temporal information extraction models were developed but a similar need for extracting temporal expressions in eligibility criteria (e.g., for eligibility determination) remains. We identified the temporal knowledge representation requirements of eligibility criteria by reviewing 100 temporal criteria. We developed EliXR-TIME, a frame-based representation designed to support semantic annotation for temporal expressions in eligibility criteria by reusing applicable classes from well-known clinical temporal knowledge representations. We used EliXR-TIME to analyze a training set of 50 new temporal eligibility criteria. We evaluated EliXR-TIME using an additional random sample of 20 eligibility criteria with temporal expressions that have no overlap with the training data, yielding 92.7% (76 / 82) inter-coder agreement on sentence chunking and 72% (72 / 100) agreement on semantic annotation. We conclude that this knowledge representation can facilitate semantic annotation of the temporal expressions in eligibility criteria.

The tensor hierarchy algebra

DOE Office of Scientific and Technical Information (OSTI.GOV)

Palmkvist, Jakob, E-mail: palmkvist@ihes.fr

We introduce an infinite-dimensional Lie superalgebra which is an extension of the U-duality Lie algebra of maximal supergravity in D dimensions, for 3 ⩽ D ⩽ 7. The level decomposition with respect to the U-duality Lie algebra gives exactly the tensor hierarchy of representations that arises in gauge deformations of the theory described by an embedding tensor, for all positive levels p. We prove that these representations are always contained in those coming from the associated Borcherds-Kac-Moody superalgebra, and we explain why some of the latter representations are not included in the tensor hierarchy. The most remarkable feature of ourmore » Lie superalgebra is that it does not admit a triangular decomposition like a (Borcherds-)Kac-Moody (super)algebra. Instead the Hodge duality relations between level p and D − 2 − p extend to negative p, relating the representations at the first two negative levels to the supersymmetry and closure constraints of the embedding tensor.« less

Using anthropomorphic avatars resembling sedentary older individuals as models to enhance self-efficacy and adherence to physical activity: psychophysiological correlates.

PubMed

Ruiz, Jorge G; Andrade, Allen D; Anam, Ramankumar; Aguiar, Rudxandra; Sun, Huaping; Roos, Bernard A

2012-01-01

The prevalence of obesity and associated health complications are currently at unprecedented levels. Physical activity in this population can improve patient outcomes. Virtual reality (VR) self-modeling may improve self-efficacy and adherence to physical activity. We conducted a comparative study of 30 participants randomized to 3 versions of a 3D avatar-based VR intervention about exercise: virtual representation of the self exercising condition; virtual representation of other person exercising and control condition. Participants in the virtual representation of the self group significantly increased their levels of physical activity. The improvement in physical activity for participants in the visual representation of other person exercising was marginal. The improvement for the control group was not significant. However, the effect sizes for comparing the pre and post intervention physical activity levels were quite large for all three groups. We did not find any group difference in the improvements of physical activity levels and self-efficacy among sedentary, overweight or obese individuals.

TEMPEST in a gallimaufry: applying multilevel systems theory to person-in-context research.

PubMed

Peck, Stephen C

2007-12-01

Terminological ambiguity and inattention to personal and contextual multilevel systems undermine personality, self, and identity theories. Hierarchical and heterarchical systems theories are used to describe contents and processes existing within and across three interrelated multilevel systems: levels of organization, representation, and integration. Materially nested levels of organization are used to distinguish persons from contexts and personal from social identity. Functionally nested levels of representation are used to distinguish personal identity from the sense of identity and symbolic (belief) from iconic (schema) systems. Levels of integration are hypothesized to unfold separately but interdependently across levels of representation. Multilevel system configurations clarify alternative conceptualizations of traits and contextualized identity. Methodological implications for measurement and analysis (e.g., integrating variable- and pattern-centered methods) are briefly described.

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning

PubMed Central

Dann, Benjamin

2016-01-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity. PMID:27814352

Neural Population Dynamics during Reaching Are Better Explained by a Dynamical System than Representational Tuning.

PubMed

Michaels, Jonathan A; Dann, Benjamin; Scherberger, Hansjörg

2016-11-01

Recent models of movement generation in motor cortex have sought to explain neural activity not as a function of movement parameters, known as representational models, but as a dynamical system acting at the level of the population. Despite evidence supporting this framework, the evaluation of representational models and their integration with dynamical systems is incomplete in the literature. Using a representational velocity-tuning based simulation of center-out reaching, we show that incorporating variable latency offsets between neural activity and kinematics is sufficient to generate rotational dynamics at the level of neural populations, a phenomenon observed in motor cortex. However, we developed a covariance-matched permutation test (CMPT) that reassigns neural data between task conditions independently for each neuron while maintaining overall neuron-to-neuron relationships, revealing that rotations based on the representational model did not uniquely depend on the underlying condition structure. In contrast, rotations based on either a dynamical model or motor cortex data depend on this relationship, providing evidence that the dynamical model more readily explains motor cortex activity. Importantly, implementing a recurrent neural network we demonstrate that both representational tuning properties and rotational dynamics emerge, providing evidence that a dynamical system can reproduce previous findings of representational tuning. Finally, using motor cortex data in combination with the CMPT, we show that results based on small numbers of neurons or conditions should be interpreted cautiously, potentially informing future experimental design. Together, our findings reinforce the view that representational models lack the explanatory power to describe complex aspects of single neuron and population level activity.

Pixel-based meshfree modelling of skeletal muscles.

PubMed

Chen, Jiun-Shyan; Basava, Ramya Rao; Zhang, Yantao; Csapo, Robert; Malis, Vadim; Sinha, Usha; Hodgson, John; Sinha, Shantanu

2016-01-01

This paper introduces the meshfree Reproducing Kernel Particle Method (RKPM) for 3D image-based modeling of skeletal muscles. This approach allows for construction of simulation model based on pixel data obtained from medical images. The material properties and muscle fiber direction obtained from Diffusion Tensor Imaging (DTI) are input at each pixel point. The reproducing kernel (RK) approximation allows a representation of material heterogeneity with smooth transition. A multiphase multichannel level set based segmentation framework is adopted for individual muscle segmentation using Magnetic Resonance Images (MRI) and DTI. The application of the proposed methods for modeling the human lower leg is demonstrated.

Numerical computation of diffusion on a surface.

PubMed

Schwartz, Peter; Adalsteinsson, David; Colella, Phillip; Arkin, Adam Paul; Onsum, Matthew

2005-08-09

We present a numerical method for computing diffusive transport on a surface derived from image data. Our underlying discretization method uses a Cartesian grid embedded boundary method for computing the volume transport in a region consisting of all points a small distance from the surface. We obtain a representation of this region from image data by using a front propagation computation based on level set methods for solving the Hamilton-Jacobi and eikonal equations. We demonstrate that the method is second-order accurate in space and time and is capable of computing solutions on complex surface geometries obtained from image data of cells.

A Review of Feature Extraction Software for Microarray Gene Expression Data

PubMed Central

Tan, Ching Siang; Ting, Wai Soon; Mohamad, Mohd Saberi; Chan, Weng Howe; Deris, Safaai; Ali Shah, Zuraini

2014-01-01

When gene expression data are too large to be processed, they are transformed into a reduced representation set of genes. Transforming large-scale gene expression data into a set of genes is called feature extraction. If the genes extracted are carefully chosen, this gene set can extract the relevant information from the large-scale gene expression data, allowing further analysis by using this reduced representation instead of the full size data. In this paper, we review numerous software applications that can be used for feature extraction. The software reviewed is mainly for Principal Component Analysis (PCA), Independent Component Analysis (ICA), Partial Least Squares (PLS), and Local Linear Embedding (LLE). A summary and sources of the software are provided in the last section for each feature extraction method. PMID:25250315

Semiotic Activity of Young Children in Play: The Construction and Use of Schematic Representations.

ERIC Educational Resources Information Center

van Oers, Bert

1994-01-01

Examined four- through six-year olds' ability to diagram the configuration of a toy railway set they had assembled and to reconstruct the railway based on drawings. Found that motivation had a significant influence on the accuracy of drawings. Results suggest that semiotic activity with the help of schematic representations or drawings is in the…

Exploring Children's Face-Space: A Multidimensional Scaling Analysis of the Mental Representation of Facial Identity

ERIC Educational Resources Information Center

Nishimura, Mayu; Maurer, Daphne; Gao, Xiaoqing

2009-01-01

We explored differences in the mental representation of facial identity between 8-year-olds and adults. The 8-year-olds and adults made similarity judgments of a homogeneous set of faces (individual hair cues removed) using an "odd-man-out" paradigm. Multidimensional scaling (MDS) analyses were performed to represent perceived similarity of faces…

Knowledge Representation and Self-Regulatory Experiences of Expert and Novice Certified Athletic Trainers in College and University Settings

ERIC Educational Resources Information Center

Gardin, Fredrick Anthony

2009-01-01

The purpose of this study was to describe how male, collegiate, certified athletic trainers (AT's) represent knowledge during 5 injury evaluation scenarios. A second purpose of the study was to identify what self-regulatory behaviors participants engaged in to improve or maintain their skills. Knowledge representation was studied as cue selection…

The Development of Representational Play in Chimpanzees and Bonobos: Evolutionary Implications, Pretense, and the Role of Interspecies Communication

ERIC Educational Resources Information Center

Lyn, Heidi; Greenfield, Patricia; Savage-Rumbaugh, Sue

2006-01-01

This research investigates the development of symbolic or representational play in two species of the genus "Pan", bonobos ("Pan paniscus") and chimpanzees ("Pan troglodytes"). The participants varied not only by species, but also as to whether they had become proficient in communicating with humans via a set of arbitrary visual symbols, called…

"Everyone Has to Find Themselves in the Story": Exploring Minority Group Representation in the Citizenship Curriculum in Northern Ireland and Israel

ERIC Educational Resources Information Center

Hanna, Helen

2016-01-01

This article explores understandings of minority group representation in citizenship education in Northern Ireland and Israel, from the point of view of students, teachers, and policy makers. It is set against the background of the minority-majority group dichotomy within societies divided along ethnonational lines, and the challenge of delivering…

Developmental Specialization in the Right Intraparietal Sulcus for the Abstract Representation of Numerical Magnitude

ERIC Educational Resources Information Center

Holloway, Ian D.; Ansari, Daniel

2010-01-01

Because number is an abstract quality of a set, the way in which a number is externally represented does not change its quantitative meaning. In this study, we examined the development of the brain regions that support format-independent representation of numerical magnitude. We asked children and adults to perform both symbolic (Hindu-Arabic…

Word Length and Lexical Activation: Longer Is Better

ERIC Educational Resources Information Center

Pitt, Mark A.; Samuel, Arthur G.

2006-01-01

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a…

The GuideLine Interchange Format

PubMed Central

Ohno-Machado, Lucila; Gennari, John H.; Murphy, Shawn N.; Jain, Nilesh L.; Tu, Samson W.; Oliver, Diane E.; Pattison-Gordon, Edward; Greenes, Robert A.; Shortliffe, Edward H.; Barnett, G. Octo

1998-01-01

Objective: To allow exchange of clinical practice guidelines among institutions and computer-based applications. Design: The GuideLine Interchange Format (GLIF) specification consists of the GLIF model and the GLIF syntax. The GLIF model is an object-oriented representation that consists of a set of classes for guideline entities, attributes for those classes, and data types for the attribute values. The GLIF syntax specifies the format of the test file that contains the encoding. Methods: Researchers from the InterMed Collaboratory at Columbia University, Harvard University (Brigham and Women's Hospital and Massachusetts General Hospital), and Stanford University analyzed four existing guideline systems to derive a set of requirements for guideline representation. The GLIF specification is a consensus representation developed through a brainstorming process. Four clinical guidelines were encoded in GLIF to assess its expressivity and to study the variability that occurs when two people from different sites encode the same guideline. Results: The encoders reported that GLIF was adequately expressive. A comparison of the encodings revealed substantial variability. Conclusion: GLIF was sufficient to model the guidelines for the four conditions that were examined. GLIF needs improvement in standard representation of medical concepts, criterion logic, temporal information, and uncertainty. PMID:9670133

MToS: A Tree of Shapes for Multivariate Images.

PubMed

Carlinet, Edwin; Géraud, Thierry

2015-12-01

The topographic map of a gray-level image, also called tree of shapes, provides a high-level hierarchical representation of the image contents. This representation, invariant to contrast changes and to contrast inversion, has been proved very useful to achieve many image processing and pattern recognition tasks. Its definition relies on the total ordering of pixel values, so this representation does not exist for color images, or more generally, multivariate images. Common workarounds, such as marginal processing, or imposing a total order on data, are not satisfactory and yield many problems. This paper presents a method to build a tree-based representation of multivariate images, which features marginally the same properties of the gray-level tree of shapes. Briefly put, we do not impose an arbitrary ordering on values, but we only rely on the inclusion relationship between shapes in the image definition domain. The interest of having a contrast invariant and self-dual representation of multivariate image is illustrated through several applications (filtering, segmentation, and object recognition) on different types of data: color natural images, document images, satellite hyperspectral imaging, multimodal medical imaging, and videos.

Levels and loops: the future of artificial intelligence and neuroscience.

PubMed Central

Bell, A J

1999-01-01

In discussing artificial intelligence and neuroscience, I will focus on two themes. The first is the universality of cycles (or loops): sets of variables that affect each other in such a way that any feed-forward account of causality and control, while informative, is misleading. The second theme is based around the observation that a computer is an intrinsically dualistic entity, with its physical set-up designed so as not to interfere with its logical set-up, which executes the computation. The brain is different. When analysed empirically at several different levels (cellular, molecular), it appears that there is no satisfactory way to separate a physical brain model (or algorithm, or representation), from a physical implementational substrate. When program and implementation are inseparable and thus interfere with each other, a dualistic point-of-view is impossible. Forced by empiricism into a monistic perspective, the brain-mind appears as neither embodied by or embedded in physical reality, but rather as identical to physical reality. This perspective has implications for the future of science and society. I will approach these from a negative point-of-view, by critiquing some of our millennial culture's popular projected futures. PMID:10670021

Reimagining Game Design: Exploring the Design of Constructible Authentic Representations for Science Reasoning

NASA Astrophysics Data System (ADS)

Holbert, Nathan Ryan

Video games have recently become a popular space for educational design due to their interactive and engaging nature and the ubiquity of the gaming experience among youth. Though many researchers argue video games can provide opportunities for learning, educational game design has focused on the classroom rather than the informal settings where games are typically played. Educational games have been moderately successful at achieving learning gains on standardized items, but have failed to show improvements on related but distal problems. In this dissertation I develop and assess a new design principle, called constructible authentic representations for creating informal gaming experiences that players will actively draw on when reasoning in formal and real world contexts. These games provide players with opportunities to engage in meaningful construction with components that integrate relevant concepts to create in-game representations that visually and epistemologically align with related tools and representations utilized in the target domain. In the first phase of the dissertation, I observed children playing popular video games to better understand what in-game representations children attend to and how interactions with these representations contribute to intuitive ideas of encountered STEM content. Results from this study fed into the iterative design of two prototype video games, FormulaT Racing and Particles!, intending to give players useful knowledge resources for reasoning about kinematics and the particulate nature of matter respectively. Designed games encourage players to utilize and refine intuitive ideas about target content through the construction of domain relevant representations. To assess the effectiveness of these designs I conducted two studies of children ages 7-14 playing prototype games in informal settings. An analysis of pre- and post-game clinical interviews, domain specific tasks, and video and logging data of gameplay suggests players developed useful knowledge resources, likely gained and/or refined from experiences in-game, that are employed to solve non-game problems and tasks. Furthermore, players utilized in-game representations as objects-to-think-with when explaining real world phenomena and formal concepts. The results suggest that games designed to include constructible authentic representations can provide players with powerful and useful knowledge resources accessible when thinking and reasoning in a variety of contexts.

Basic-level and superordinate-like categorical representations in early infancy.

PubMed

Behl-Chadha, G

1996-08-01

A series of experiments using the paired-preference procedure examined 3- to 4-month-old infants' ability to form perceptually based categorical representations in the domains of natural kinds and artifacts and probed the underlying organizational structure of these representations. Experiments 1 and 2 found that infants could form categorical representations for chairs that excluded exemplars of couches, beds, and tables and also for couches that excluded exemplars of chairs, beds, and tables. Thus, the adult-like exclusivity shown by infants in the categorization of various animal pictures at the basic-level extends to the domain of artifacts as well--an ecologically significant ability given the numerous artifacts that populate the human environment. Experiments 3 and 4 examined infants' ability to form superordinate-like or global categorical representations for mammals and furniture. It was found that infants could form a global representation for mammals that included novel mammals and excluded other non-mammalian animals such as birds and fish as well as items from cross-ontological categories such as furniture. In addition, it was found that infants formed a representation for furniture that included novel categories of furniture and excluded exemplars from the cross-ontological category of mammals; however, it was less clear if infants' global representation for furniture also excluded other artifacts such as vehicles and thus the category of furniture may have been less exclusively represented. Overall, the present findings, by showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, underscore the importance of these early representations for later conceptual representations.

Antecedent reactivation by surface and deep anaphora in Norwegian

PubMed Central

HESTVIK, ARILD; NORDBY, HELGE; KARLSEN, GEIR

2005-01-01

Anaphora are expressions in language that depend on other linguistic entities for their full meaning. They can furthermore be divided into two types according to the level of representation where they find their antecedents: Surface anaphora, which resolve their reference at the sentence representation level, and deep anaphora, which resolve their reference at the non-grammatical level of discourse representation. The linguistic theory of these two anaphor types, and recent findings about processing differences at these two levels, combine to predict that surface anaphora should show fast and immediate reactivation of their antecedents, whereas deep anaphora should have a slower time course of antecedent reaccess. These predictions were confirmed with two lexical decision task experiments with Norwegian stimuli. PMID:15842413

Care for women involved with drugs: social representations of nurses.

PubMed

Rodrigues, Andreia Silva; Oliveira, Jeane Freitas de; Suto, Cleuma Sueli Santos; Coutinho, Maria da Penha de Lima; Paiva, Mirian Santos; Souza, Simone Santos

2017-01-01

analyze social representations of nurses related to the care for women involved with drugs. qualitative research founded on the theory of social representations, with 42 nurses from a public maternity ward of Salvador-BA, using identification questionnaire, test of free association of words, and semi-structured interview. We analyzed the structure of social representations and the similarity tree of free evocations, and also analyzed the content of interviews. care for women involved with drugs is represented by a set of words that shows theoretical questions and scientific techniques, but faced with experiences in the training, in the daily work and in ideas and values assigned to the consumption of drugs especially in the gravidic-puerperal period. The social representations of nurses show conflicts between social and cultural aspects around the problem of drugs and the health care provided to women involved with drugs.

The enhancement of students’ mathematical representation in junior high school using cognitive apprenticeship instruction (CAI)

NASA Astrophysics Data System (ADS)

Yusepa, B. G. P.; Kusumah, Y. S.; Kartasasmita, B. G.

2018-03-01

This study aims to get an in-depth understanding of the enhancement of students’ mathematical representation. This study is experimental research with pretest-posttest control group design. The subject of this study is the students’ of the eighth grade from junior high schools in Bandung: high-level and middle-level. In each school, two parallel groups were chosen as a control group and an experimental group. The experimental group was given cognitive apprenticeship instruction (CAI) treatment while the control group was given conventional learning. The results show that the enhancement of students’ mathematical representation who obtained CAI treatment was better than the conventional one, viewed which can be observed from the overall, mathematical prior knowledge (MPK), and school level. It can be concluded that CAI can be used as a good alternative learning model to enhance students’ mathematical representation.

Using pedagogical discipline representations (PDRs) to enable Astro 101 students to reason about modern astrophysics

NASA Astrophysics Data System (ADS)

Wallace, Colin Scott; Prather, Edward E.; Chambers, Timothy G.; Kamenetzky, Julia R.; Hornstein, Seth D.

2017-01-01

Instructors of introductory, college-level, general education astronomy (Astro 101) often want to include topics from the cutting-edge of modern astrophysics in their course. Unfortunately, the teaching of these cutting-edge topics is typically confined to advanced undergraduate or graduate classes, using representations (graphical, mathematical, etc.) that are inaccessible to the vast majority of Astro 101 students. Consequently, many Astro 101 instructors feel that they have no choice but to cover these modern topics at a superficial level. Pedagogical discipline representations (PDRs) are one solution to this problem. Pedagogical discipline representations are representations that are explicitly designed to enhance the teaching and learning of a topic, even though these representations may not typically be found in traditional textbooks or used by experts in the discipline who are engaged in topic-specific discourse. In some cases, PDRs are significantly simplified or altered versions of typical discipline representations (graphs, data tables, etc.); in others they may be novel and highly contextualized representations with unique features that purposefully engage novice learners’ pre-existing mental models and reasoning difficulties, facilitating critical discourse. In this talk, I will discuss important lessons that my colleagues and I have learned while developing PDRs and describe how PDRs can enable students to reason about complex modern astrophysical topics.

An integrated reweighting theory of perceptual learning

PubMed Central

Dosher, Barbara Anne; Jeter, Pamela; Liu, Jiajuan; Lu, Zhong-Lin

2013-01-01

Improvements in performance on visual tasks due to practice are often specific to a retinal position or stimulus feature. Many researchers suggest that specific perceptual learning alters selective retinotopic representations in early visual analysis. However, transfer is almost always practically advantageous, and it does occur. If perceptual learning alters location-specific representations, how does it transfer to new locations? An integrated reweighting theory explains transfer over retinal locations by incorporating higher level location-independent representations into a multilevel learning system. Location transfer is mediated through location-independent representations, whereas stimulus feature transfer is determined by stimulus similarity at both location-specific and location-independent levels. Transfer to new locations/positions differs fundamentally from transfer to new stimuli. After substantial initial training on an orientation discrimination task, switches to a new location or position are compared with switches to new orientations in the same position, or switches of both. Position switches led to the highest degree of transfer, whereas orientation switches led to the highest levels of specificity. A computational model of integrated reweighting is developed and tested that incorporates the details of the stimuli and the experiment. Transfer to an identical orientation task in a new position is mediated via more broadly tuned location-invariant representations, whereas changing orientation in the same position invokes interference or independent learning of the new orientations at both levels, reflecting stimulus dissimilarity. Consistent with single-cell recording studies, perceptual learning alters the weighting of both early and midlevel representations of the visual system. PMID:23898204

How Are New Vaccines Prioritized in Low-Income Countries? A Case Study of Human Papilloma Virus Vaccine and Pneumococcal Conjugate Vaccine in Uganda

PubMed Central

Wallace, Lauren; Kapirir, Lydia

2017-01-01

Background: To date, research on priority-setting for new vaccines has not adequately explored the influence of the global, national and sub-national levels of decision-making or contextual issues such as political pressure and stakeholder influence and power. Using Kapiriri and Martin’s conceptual framework, this paper evaluates priority setting for new vaccines in Uganda at national and sub-national levels, and considers how global priorities can influence country priorities. This study focuses on 2 specific vaccines, the human papilloma virus (HPV) vaccine and the pneumococcal conjugate vaccine (PCV). Methods: This was a qualitative study that involved reviewing relevant Ugandan policy documents and media reports, as well as 54 key informant interviews at the global level and national and sub-national levels in Uganda. Kapiriri and Martin’s conceptual framework was used to evaluate the prioritization process. Results: Priority setting for PCV and HPV was conducted by the Ministry of Health (MoH), which is considered to be a legitimate institution. While respondents described the priority setting process for PCV process as transparent, participatory, and guided by explicit relevant criteria and evidence, the prioritization of HPV was thought to have been less transparent and less participatory. Respondents reported that neither process was based on an explicit priority setting framework nor did it involve adequate representation from the districts (program implementers) or publicity. The priority setting process for both PCV and HPV was negatively affected by the larger political and economic context, which contributed to weak institutional capacity as well as power imbalances between development assistance partners and the MoH. Conclusion: Priority setting in Uganda would be improved by strengthening institutional capacity and leadership and ensuring a transparent and participatory processes in which key stakeholders such as program implementers (the districts) and beneficiaries (the public) are involved. Kapiriri and Martin’s framework has the potential to guide priority setting evaluation efforts, however, evaluation should be built into the priority setting process a priori such that information on priority setting is gathered throughout the implementation cycle. PMID:29172378

MOAB : a mesh-oriented database.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tautges, Timothy James; Ernst, Corey; Stimpson, Clint

A finite element mesh is used to decompose a continuous domain into a discretized representation. The finite element method solves PDEs on this mesh by modeling complex functions as a set of simple basis functions with coefficients at mesh vertices and prescribed continuity between elements. The mesh is one of the fundamental types of data linking the various tools in the FEA process (mesh generation, analysis, visualization, etc.). Thus, the representation of mesh data and operations on those data play a very important role in FEA-based simulations. MOAB is a component for representing and evaluating mesh data. MOAB can storemore » structured and unstructured mesh, consisting of elements in the finite element 'zoo'. The functional interface to MOAB is simple yet powerful, allowing the representation of many types of metadata commonly found on the mesh. MOAB is optimized for efficiency in space and time, based on access to mesh in chunks rather than through individual entities, while also versatile enough to support individual entity access. The MOAB data model consists of a mesh interface instance, mesh entities (vertices and elements), sets, and tags. Entities are addressed through handles rather than pointers, to allow the underlying representation of an entity to change without changing the handle to that entity. Sets are arbitrary groupings of mesh entities and other sets. Sets also support parent/child relationships as a relation distinct from sets containing other sets. The directed-graph provided by set parent/child relationships is useful for modeling topological relations from a geometric model or other metadata. Tags are named data which can be assigned to the mesh as a whole, individual entities, or sets. Tags are a mechanism for attaching data to individual entities and sets are a mechanism for describing relations between entities; the combination of these two mechanisms is a powerful yet simple interface for representing metadata or application-specific data. For example, sets and tags can be used together to describe geometric topology, boundary condition, and inter-processor interface groupings in a mesh. MOAB is used in several ways in various applications. MOAB serves as the underlying mesh data representation in the VERDE mesh verification code. MOAB can also be used as a mesh input mechanism, using mesh readers included with MOAB, or as a translator between mesh formats, using readers and writers included with MOAB. The remainder of this report is organized as follows. Section 2, 'Getting Started', provides a few simple examples of using MOAB to perform simple tasks on a mesh. Section 3 discusses the MOAB data model in more detail, including some aspects of the implementation. Section 4 summarizes the MOAB function API. Section 5 describes some of the tools included with MOAB, and the implementation of mesh readers/writers for MOAB. Section 6 contains a brief description of MOAB's relation to the TSTT mesh interface. Section 7 gives a conclusion and future plans for MOAB development. Section 8 gives references cited in this report. A reference description of the full MOAB API is contained in Section 9.« less

Two-rowed Hecke algebra representations at roots of unity

NASA Astrophysics Data System (ADS)

Welsh, Trevor Alan

1996-02-01

In this paper, we initiate a study into the explicit construction of irreducible representations of the Hecke algebraH n (q) of typeA n-1 in the non-generic case whereq is a root of unity. The approach is via the Specht modules ofH n (q) which are irreducible in the generic case, and possess a natural basis indexed by Young tableaux. The general framework in which the irreducible non-genericH n (q)-modules are to be constructed is set up and, in particular, the full set of modules corresponding to two-part partitions is described. Plentiful examples are given.

Representation of natural numbers in quantum mechanics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Benioff, Paul

2001-03-01

This paper represents one approach to making explicit some of the assumptions and conditions implied in the widespread representation of numbers by composite quantum systems. Any nonempty set and associated operations is a set of natural numbers or a model of arithmetic if the set and operations satisfy the axioms of number theory or arithmetic. This paper is limited to k-ary representations of length L and to the axioms for arithmetic modulo k{sup L}. A model of the axioms is described based on an abstract L-fold tensor product Hilbert space H{sup arith}. Unitary maps of this space onto a physicalmore » parameter based product space H{sup phy} are then described. Each of these maps makes states in H{sup phy}, and the induced operators, a model of the axioms. Consequences of the existence of many of these maps are discussed along with the dependence of Grover's and Shor's algorithms on these maps. The importance of the main physical requirement, that the basic arithmetic operations are efficiently implementable, is discussed. This condition states that there exist physically realizable Hamiltonians that can implement the basic arithmetic operations and that the space-time and thermodynamic resources required are polynomial in L.« less

Evaluation of Chemical Representations in Physical Chemistry Textbooks

ERIC Educational Resources Information Center

Nyachwaya, James M.; Wood, Nathan B.

2014-01-01

That different levels of representation are important for complete understanding of chemistry is an accepted fact in the chemistry education community. This study sought to uncover types of representations used in given physical chemistry textbooks. Textbooks play a central role in the teaching and learning of science (chemistry), and in some…

Basic-Level and Superordinate-like Categorical Representations in Early Infancy.

ERIC Educational Resources Information Center

Behl-Chadha, Gundeep

1996-01-01

Examined three- to four-month-old infants' ability to form perceptually based categorical representation in the domains of natural kinds and artifacts. By showing the availability of perceptually driven basic and superordinate-like representations in early infancy that closely correspond to adult conceptual categories, findings underscored the…

Vietnamese Document Representation and Classification

NASA Astrophysics Data System (ADS)

Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

48 CFR 52.226-3 - Disaster or Emergency Area Representation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... offeror represents that it ___does ____ does not reside or primarily do business in the set-aside area. (c) An offeror is considered to be residing or primarily doing business in the set-aside area if, during..., factors to be considered in determining whether an offeror resides or primarily does business in the set...

Set Theory Applied to Uniquely Define the Inputs to Territorial Systems in Emergy Analyses

EPA Science Inventory

The language of set theory can be utilized to represent the emergy involved in all processes. In this paper we use set theory in an emergy evaluation to ensure an accurate representation of the inputs to territorial systems. We consider a generic territorial system and we describ...

Spontaneous Analog Number Representations in 3-Year-Old Children

ERIC Educational Resources Information Center

Cantlon, Jessica F.; Safford, Kelley E.; Brannon, Elizabeth M.

2010-01-01

When enumerating small sets of elements nonverbally, human infants often show a set-size limitation whereby they are unable to represent sets larger than three elements. This finding has been interpreted as evidence that infants spontaneously represent small numbers with an object-file system instead of an analog magnitude system (Feigenson,…

Human Frequency Following Response: Neural Representation of Envelope and Temporal Fine Structure in Listeners with Normal Hearing and Sensorineural Hearing Loss

PubMed Central

Ananthakrishnan, Saradha; Krishnan, Ananthanarayan; Bartlett, Edward

2015-01-01

Objective Listeners with sensorineural hearing loss (SNHL) typically experience reduced speech perception, which is not completely restored with amplification. This likely occurs because cochlear damage, in addition to elevating audiometric thresholds, alters the neural representation of speech transmitted to higher centers along the auditory neuroaxis. While the deleterious effects of SNHL on speech perception in humans have been well-documented using behavioral paradigms, our understanding of the neural correlates underlying these perceptual deficits remains limited. Using the scalp-recorded Frequency Following Response (FFR), the authors examine the effects of SNHL and aging on subcortical neural representation of acoustic features important for pitch and speech perception, namely the periodicity envelope (F0) and temporal fine structure (TFS) (formant structure), as reflected in the phase-locked neural activity generating the FFR. Design FFRs were obtained from 10 listeners with normal hearing (NH) and 9 listeners with mild-moderate SNHL in response to a steady-state English back vowel /u/ presented at multiple intensity levels. Use of multiple presentation levels facilitated comparisons at equal sound pressure level (SPL) and equal sensation level (SL). In a second follow-up experiment to address the effect of age on envelope and TFS representation, FFRs were obtained from 25 NH and 19 listeners with mild to moderately-severe SNHL to the same vowel stimulus presented at 80 dB SPL. Temporal waveforms, Fast Fourier Transform (FFT) and spectrograms were used to evaluate the magnitude of the phase-locked activity at F0 (periodicity envelope) and F1 (TFS). Results Neural representation of both envelope (F0) and TFS (F1) at equal SPLs was stronger in NH listeners compared to listeners with SNHL. Also, comparison of neural representation of F0 and F1 across stimulus levels expressed in SPL and SL (accounting for audibility) revealed that level-related changes in F0 and F1 magnitude were different for listeners with SNHL compared to listeners with normal hearing. Further, the degradation in subcortical neural representation was observed to persist in listeners with SNHL even when the effects of age were controlled for. Conclusions Overall, our results suggest a relatively greater degradation in the neural representation of TFS compared to periodicity envelope in individuals with SNHL. This degraded neural representation of TFS in SNHL, as reflected in the brainstem FFR, may reflect a disruption in the temporal pattern of phase-locked neural activity arising from altered tonotopic maps and/or wider filters causing poor frequency selectivity in these listeners. Lastly, while preliminary results indicate that the deleterious effects of SNHL may be greater than age-related degradation in subcortical neural representation, the lack of a balanced age-matched control group in this study does not permit us to completely rule out the effects of age on subcortical neural representation. PMID:26583482

Making data matter: Voxel printing for the digital fabrication of data across scales and domains.

PubMed

Bader, Christoph; Kolb, Dominik; Weaver, James C; Sharma, Sunanda; Hosny, Ahmed; Costa, João; Oxman, Neri

2018-05-01

We present a multimaterial voxel-printing method that enables the physical visualization of data sets commonly associated with scientific imaging. Leveraging voxel-based control of multimaterial three-dimensional (3D) printing, our method enables additive manufacturing of discontinuous data types such as point cloud data, curve and graph data, image-based data, and volumetric data. By converting data sets into dithered material deposition descriptions, through modifications to rasterization processes, we demonstrate that data sets frequently visualized on screen can be converted into physical, materially heterogeneous objects. Our approach alleviates the need to postprocess data sets to boundary representations, preventing alteration of data and loss of information in the produced physicalizations. Therefore, it bridges the gap between digital information representation and physical material composition. We evaluate the visual characteristics and features of our method, assess its relevance and applicability in the production of physical visualizations, and detail the conversion of data sets for multimaterial 3D printing. We conclude with exemplary 3D-printed data sets produced by our method pointing toward potential applications across scales, disciplines, and problem domains.

Multivariate Patterns in the Human Object-Processing Pathway Reveal a Shift from Retinotopic to Shape Curvature Representations in Lateral Occipital Areas, LO-1 and LO-2.

PubMed

Vernon, Richard J W; Gouws, André D; Lawrence, Samuel J D; Wade, Alex R; Morland, Antony B

2016-05-25

Representations in early visual areas are organized on the basis of retinotopy, but this organizational principle appears to lose prominence in the extrastriate cortex. Nevertheless, an extrastriate region, such as the shape-selective lateral occipital cortex (LO), must still base its activation on the responses from earlier retinotopic visual areas, implying that a transition from retinotopic to "functional" organizations should exist. We hypothesized that such a transition may lie in LO-1 or LO-2, two visual areas lying between retinotopically defined V3d and functionally defined LO. Using a rapid event-related fMRI paradigm, we measured neural similarity in 12 human participants between pairs of stimuli differing along dimensions of shape exemplar and shape complexity within both retinotopically and functionally defined visual areas. These neural similarity measures were then compared with low-level and more abstract (curvature-based) measures of stimulus similarity. We found that low-level, but not abstract, stimulus measures predicted V1-V3 responses, whereas the converse was true for LO, a double dissociation. Critically, abstract stimulus measures were most predictive of responses within LO-2, akin to LO, whereas both low-level and abstract measures were predictive for responses within LO-1, perhaps indicating a transitional point between those two organizational principles. Similar transitions to abstract representations were not observed in the more ventral stream passing through V4 and VO-1/2. The transition we observed in LO-1 and LO-2 demonstrates that a more "abstracted" representation, typically considered the preserve of "category-selective" extrastriate cortex, can nevertheless emerge in retinotopic regions. Visual areas are typically identified either through retinotopy (e.g., V1-V3) or from functional selectivity [e.g., shape-selective lateral occipital complex (LOC)]. We combined these approaches to explore the nature of shape representations through the visual hierarchy. Two different representations emerged: the first reflected low-level shape properties (dependent on the spatial layout of the shape outline), whereas the second captured more abstract curvature-related shape features. Critically, early visual cortex represented low-level information but this diminished in the extrastriate cortex (LO-1/LO-2/LOC), in which the abstract representation emerged. Therefore, this work further elucidates the nature of shape representations in the LOC, provides insight into how those representations emerge from early retinotopic cortex, and crucially demonstrates that retinotopically tuned regions (LO-1/LO-2) are not necessarily constrained to retinotopic representations. Copyright © 2016 Vernon et al.

Multivariate Patterns in the Human Object-Processing Pathway Reveal a Shift from Retinotopic to Shape Curvature Representations in Lateral Occipital Areas, LO-1 and LO-2

PubMed Central

Vernon, Richard J. W.; Gouws, André D.; Lawrence, Samuel J. D.; Wade, Alex R.

2016-01-01

Representations in early visual areas are organized on the basis of retinotopy, but this organizational principle appears to lose prominence in the extrastriate cortex. Nevertheless, an extrastriate region, such as the shape-selective lateral occipital cortex (LO), must still base its activation on the responses from earlier retinotopic visual areas, implying that a transition from retinotopic to “functional” organizations should exist. We hypothesized that such a transition may lie in LO-1 or LO-2, two visual areas lying between retinotopically defined V3d and functionally defined LO. Using a rapid event-related fMRI paradigm, we measured neural similarity in 12 human participants between pairs of stimuli differing along dimensions of shape exemplar and shape complexity within both retinotopically and functionally defined visual areas. These neural similarity measures were then compared with low-level and more abstract (curvature-based) measures of stimulus similarity. We found that low-level, but not abstract, stimulus measures predicted V1–V3 responses, whereas the converse was true for LO, a double dissociation. Critically, abstract stimulus measures were most predictive of responses within LO-2, akin to LO, whereas both low-level and abstract measures were predictive for responses within LO-1, perhaps indicating a transitional point between those two organizational principles. Similar transitions to abstract representations were not observed in the more ventral stream passing through V4 and VO-1/2. The transition we observed in LO-1 and LO-2 demonstrates that a more “abstracted” representation, typically considered the preserve of “category-selective” extrastriate cortex, can nevertheless emerge in retinotopic regions. SIGNIFICANCE STATEMENT Visual areas are typically identified either through retinotopy (e.g., V1–V3) or from functional selectivity [e.g., shape-selective lateral occipital complex (LOC)]. We combined these approaches to explore the nature of shape representations through the visual hierarchy. Two different representations emerged: the first reflected low-level shape properties (dependent on the spatial layout of the shape outline), whereas the second captured more abstract curvature-related shape features. Critically, early visual cortex represented low-level information but this diminished in the extrastriate cortex (LO-1/LO-2/LOC), in which the abstract representation emerged. Therefore, this work further elucidates the nature of shape representations in the LOC, provides insight into how those representations emerge from early retinotopic cortex, and crucially demonstrates that retinotopically tuned regions (LO-1/LO-2) are not necessarily constrained to retinotopic representations. PMID:27225766

Visual search for object categories is predicted by the representational architecture of high-level visual cortex

PubMed Central

Alvarez, George A.; Nakayama, Ken; Konkle, Talia

2016-01-01

Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system. NEW & NOTEWORTHY Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex underlying visual object processing. PMID:27832600

Acoustic representation of tomographic data

NASA Astrophysics Data System (ADS)

Wampler, Cheryl; Zahrt, John D.; Hotchkiss, Robert S.; Zahrt, Rebecca; Kust, Mark

1993-04-01

Tomographic data and tomographic reconstructions are naturally periodic in the angle of rotation of the turntable and the polar angel of the coordinates in the object, respectively. Similarly, acoustic waves are periodic and have amplitude and wavelength as free parameters that can be fit to another representation. Work has been in progress for some time in bringing the acoustic senses to bear on large data sets rather than just the visual sense. We will provide several different acoustic representations of both raw data and density maps. Rather than graphical portrayal of the data and reconstructions, you will be presented various 'tone poems.'

Squeezed states: A geometric framework

NASA Technical Reports Server (NTRS)

Ali, S. T.; Brooke, J. A.; Gazeau, J.-P.

1992-01-01

A general definition of squeezed states is proposed and its main features are illustrated through a discussion of the standard optical coherent states represented by 'Gaussian pure states'. The set-up involves representations of groups on Hilbert spaces over homogeneous spaces of the group, and relies on the construction of a square integrable (coherent state) group representation modulo a subgroup. This construction depends upon a choice of a Borel section which has a certain permissible arbitrariness in its selection; this freedom is attributable to a squeezing of the defining coherent states of the representation, and corresponds in this way to a sort of gauging.

Do Stimulus-Action Associations Contribute to Repetition Priming?

ERIC Educational Resources Information Center

Dennis, Ian; Perfect, Timothy J.

2013-01-01

Despite evidence that response learning makes a major contribution to repetition priming, the involvement of response representations at the level of motor actions remains uncertain. Levels of response representation were investigated in 4 experiments that used different tasks at priming and test. Priming for stimuli that required congruent…

Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI

NASA Astrophysics Data System (ADS)

Hwuang, Eileen; Rusu, Mirabela; Karthigeyan, Sudha; Agner, Shannon C.; Sparks, Rachel; Shih, Natalie; Tomaszewski, John E.; Rosen, Mark; Feldman, Michael; Madabhushi, Anant

2014-03-01

Multi-modal image registration is needed to align medical images collected from different protocols or imaging sources, thereby allowing the mapping of complementary information between images. One challenge of multimodal image registration is that typical similarity measures rely on statistical correlations between image intensities to determine anatomical alignment. The use of alternate image representations could allow for mapping of intensities into a space or representation such that the multimodal images appear more similar, thus facilitating their co-registration. In this work, we present a spectral embedding based registration (SERg) method that uses non-linearly embedded representations obtained from independent components of statistical texture maps of the original images to facilitate multimodal image registration. Our methodology comprises the following main steps: 1) image-derived textural representation of the original images, 2) dimensionality reduction using independent component analysis (ICA), 3) spectral embedding to generate the alternate representations, and 4) image registration. The rationale behind our approach is that SERg yields embedded representations that can allow for very different looking images to appear more similar, thereby facilitating improved co-registration. Statistical texture features are derived from the image intensities and then reduced to a smaller set by using independent component analysis to remove redundant information. Spectral embedding generates a new representation by eigendecomposition from which only the most important eigenvectors are selected. This helps to accentuate areas of salience based on modality-invariant structural information and therefore better identifies corresponding regions in both the template and target images. The spirit behind SERg is that image registration driven by these areas of salience and correspondence should improve alignment accuracy. In this work, SERg is implemented using Demons to allow the algorithm to more effectively register multimodal images. SERg is also tested within the free-form deformation framework driven by mutual information. Nine pairs of synthetic T1-weighted to T2-weighted brain MRI were registered under the following conditions: five levels of noise (0%, 1%, 3%, 5%, and 7%) and two levels of bias field (20% and 40%) each with and without noise. We demonstrate that across all of these conditions, SERg yields a mean squared error that is 81.51% lower than that of Demons driven by MRI intensity alone. We also spatially align twenty-six ex vivo histology sections and in vivo prostate MRI in order to map the spatial extent of prostate cancer onto corresponding radiologic imaging. SERg performs better than intensity registration by decreasing the root mean squared distance of annotated landmarks in the prostate gland via both Demons algorithm and mutual information-driven free-form deformation. In both synthetic and clinical experiments, the observed improvement in alignment of the template and target images suggest the utility of parametric eigenvector representations and hence SERg for multimodal image registration.

Multiple time-scales and the developmental dynamics of social systems

PubMed Central

Flack, Jessica C.

2012-01-01

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819

Multiple time-scales and the developmental dynamics of social systems.

PubMed

Flack, Jessica C

2012-07-05

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.

Spatial Data Transfer Standard (SDTS), part 3 : ISO 8211 encoding

DOT National Transportation Integrated Search

1997-11-20

The ISO 8211 encoding provides a representation of a Spatial Data Transfer Standard (SDTS) file set in a standardized method enabling the file set to be exported to or imported from different media by general purpose ISO 8211 software.

Children's representations of multiple family relationships: organizational structure and development in early childhood.

PubMed

Schermerhorn, Alice C; Cummings, E Mark; Davies, Patrick T

2008-02-01

The authors examine mutual family influence processes at the level of children's representations of multiple family relationships, as well as the structure of those representations. From a community sample with 3 waves, each spaced 1 year apart, kindergarten-age children (105 boys and 127 girls) completed a story-stem completion task, tapping representations of multiple family relationships. Structural equation modeling with autoregressive controls indicated that representational processes involving different family relationships were interrelated over time, including links between children's representations of marital conflict and reactions to conflict, between representations of security about marital conflict and parent-child relationships, and between representations of security in father-child and mother-child relationships. Mixed support was found for notions of increasing stability in representations during this developmental period. Results are discussed in terms of notions of transactional family dynamics, including family-wide perspectives on mutual influence processes attributable to multiple family relationships.

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

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.

Mathematical Fundamentals of Probabilistic Semantics for High-Level Fusion

DTIC Science & Technology

2013-12-02

understanding of the fundamental aspects of uncertainty representation and reasoning that a theory of hard and soft high-level fusion must encompass...representation and reasoning that a theory of hard and soft high-level fusion must encompass. Successful completion requires an unbiased, in-depth...and soft information is the lack of a fundamental HLIF theory , backed by a consistent mathematical framework and supporting algorithms. Although there

Convergence in the Bilingual Lexicon: A Pre-registered Replication of Previous Studies.

PubMed

White, Anne; Malt, Barbara C; Storms, Gert

2016-01-01

Naming patterns of bilinguals have been found to converge and form a new intermediate language system from elements of both the bilinguals' languages. This converged naming pattern differs from the monolingual naming patterns of both a bilingual's languages. We conducted a pre-registered replication study of experiments addressing the question whether there is a convergence between a bilingual's both lexicons. The replication used an enlarged set of stimuli of common household containers, providing generalizability, and more reliable representations of the semantic domain. Both an analysis at the group-level and at the individual level of the correlations between naming patterns reject the two-pattern hypothesis that poses that bilinguals use two monolingual-like naming patterns, one for each of their two languages. However, the results of the original study and the replication comply with the one-pattern hypothesis, which poses that bilinguals converge the naming patterns of their two languages and form a compromise. Since this convergence is only partial the naming pattern in bilinguals corresponds to a moderate version of the one-pattern hypothesis. These findings are further confirmed by a representation of the semantic domain in a multidimensional space and the finding of shorter distances between bilingual category centers than monolingual category centers in this multidimensional space both in the original and in the replication study.

Understanding pictorial information in biology: students' cognitive activities and visual reading strategies

NASA Astrophysics Data System (ADS)

Brandstetter, Miriam; Sandmann, Angela; Florian, Christine

2017-06-01

In classroom, scientific contents are increasingly communicated through visual forms of representations. Students' learning outcomes rely on their ability to read and understand pictorial information. Understanding pictorial information in biology requires cognitive effort and can be challenging to students. Yet evidence-based knowledge about students' visual reading strategies during the process of understanding pictorial information is pending. Therefore, 42 students at the age of 14-15 were asked to think aloud while trying to understand visual representations of the blood circulatory system and the patellar reflex. A category system was developed differentiating 16 categories of cognitive activities. A Principal Component Analysis revealed two underlying patterns of activities that can be interpreted as visual reading strategies: 1. Inferences predominated by using a problem-solving schema; 2. Inferences predominated by recall of prior content knowledge. Each pattern consists of a specific set of cognitive activities that reflect selection, organisation and integration of pictorial information as well as different levels of expertise. The results give detailed insights into cognitive activities of students who were required to understand the pictorial information of complex organ systems. They provide an evidence-based foundation to derive instructional aids that can promote students pictorial-information-based learning on different levels of expertise.

Service Level Agreements in BREIN

NASA Astrophysics Data System (ADS)

Koller, Bastian; Frutos, Henar Munoz; Laria, Giuseppe

With electronic business (eBusiness) becoming ubiquitous, the traditional ways of doing commerce need to be changed or completely replaced to support the end users effectively in performing their business. This includes especially the representation of business relationships with an electronic format to allow for automated processing of the respective parts of e.g. contractual obligations. One prominent representation tool are Service Level Agreements. Conceptually established as paper representation to describe parts of contracts of telecom operators, SLAs have become a research topic in the ICT domain now since several years.

Representation and matching of knowledge to design digital systems

NASA Technical Reports Server (NTRS)

Jones, J. U.; Shiva, S. G.

1988-01-01

A knowledge-based expert system is described that provides an approach to solve a problem requiring an expert with considerable domain expertise and facts about available digital hardware building blocks. To design digital hardware systems from their high level VHDL (Very High Speed Integrated Circuit Hardware Description Language) representation to their finished form, a special data representation is required. This data representation as well as the functioning of the overall system is described.

Representation of Biomedical Expertise in Ontologies: a Case Study about Knowledge Acquisition on HTLV viruses and their clinical manifestations.

PubMed

Cardoso Coelho, Kátia; Barcellos Almeida, Maurício

2015-01-01

In this paper, we introduce a set of methodological steps for knowledge acquisition applied to the organization of biomedical information through ontologies. Those steps are tested in a real case involving Human T Cell Lymphotropic Virus (HTLV), which causes myriad infectious diseases. We hope to contribute to providing suitable knowledge representation of scientific domains.

Children's Enactment of Characters' Movements: A Novel Measure of Spatial Situation Model Representations and Indicator of Comprehension

ERIC Educational Resources Information Center

Nyhout, Angela; O'Neill, Daniela K.

2017-01-01

A story's space or setting often determines and constrains the actions of its characters. We report on an experiment with 106 children of 7-8 years old in which, using a novel enactment task, we measured children's representation of a story character's movement during story listening. We found that children were more likely to enact movements that…

Investigating Change in Young People's Understandings of Japan: A Study of Learning about a Distant Place

ERIC Educational Resources Information Center

Taylor, Liz

2011-01-01

This article demonstrates how a set of complementary qualitative methods can be used to construct a detailed picture not only of the nature of young people's representations of a distant place but the processes of learning by which such representations develop over the medium term. The analysis is based on an interpretive case study of a class of…

Validating a hydrodynamic framework for long-term modelling of the German Bight

NASA Astrophysics Data System (ADS)

Koesters, Frank; Pluess, Andreas; Heyer, Harro; Kastens, Marko; Sehili, Aissa

2010-05-01

The intention of the "AufMod" project is to set up a modelling framework for questions concerning the large-scale, long-term morphodynamic evolution of the German Bight. First a hydrodynamic model has been set up which includes the entire North Sea and a sophisticated representation of the German Bight. In a second step, simulations of sediment transport and morphodynamic changes will be processed. This paper deals with the calibration and validation process for the hydrodynamic model in detail. The starting point for "AufMod" was the aim to better understand the morphodynamic processes in the German Bight. Changes in bottom topography need to be predicted to ensure a safe and easy transport through the German waterways leading to ports at the German coast such as Hamburg and Bremerhaven. Within "AufMod" this question is addressed through a combined effort of gaining a comprehensive sedimentological and bathymetric data set as well as running different numerical models. The model is based on the numerical method UnTRIM (Casulli and Zanolli, 2002). The model uses an unstructured grid in the horizontal to provide a good representation of the complex topography. The spatial resolution increases from about 20 km in the North Sea to 20 m within the estuaries. The model forcing represents conditions for the year 2006 and consists of wind stress at the surface, water level elevation and salinity at the open boundaries as well as freshwater inflows. Temperature is not taken into account. For the model validation, there exists a large number of over 40 hydrodynamic monitoring stations which are used to compare modelled and measured data. The calibration process consists of adapting the tidal components at the open boundaries following the approach of Pluess (2003). The validation process includes the analysis of tidal components of water level elevation and current values as well as an analysis of tidal characteristic values, e.g. tidal low and high water. Based on these numerical measures, the representation of the underlying physics is quantified by using a skill score. The overall hydrodynamic structure is represented well by the model and will be starting point for the following morphodynamic experiments. Literature Casulli and Zanolli (2002) V. Casulli and P. Zanolli. Semi-Implicit Numerical Modelling of Non-Hydrostatic Free-surface Flows for Environmental Problems. Mathematical and Computer Modelling, 36:1131-1149, 2002. Pluess (2003) A. Pluess. Das Nordseemodell der BAW zur Simulation der Tide in der Deutschen Bucht. Die Kueste, Heft 67, 2003, ISBN 3-8042-1058-9, pp 83-128

How task demands shape brain responses to visual food cues.

PubMed

Pohl, Tanja Maria; Tempelmann, Claus; Noesselt, Toemme

2017-06-01

Several previous imaging studies have aimed at identifying the neural basis of visual food cue processing in humans. However, there is little consistency of the functional magnetic resonance imaging (fMRI) results across studies. Here, we tested the hypothesis that this variability across studies might - at least in part - be caused by the different tasks employed. In particular, we assessed directly the influence of task set on brain responses to food stimuli with fMRI using two tasks (colour vs. edibility judgement, between-subjects design). When participants judged colour, the left insula, the left inferior parietal lobule, occipital areas, the left orbitofrontal cortex and other frontal areas expressed enhanced fMRI responses to food relative to non-food pictures. However, when judging edibility, enhanced fMRI responses to food pictures were observed in the superior and middle frontal gyrus and in medial frontal areas including the pregenual anterior cingulate cortex and ventromedial prefrontal cortex. This pattern of results indicates that task sets can significantly alter the neural underpinnings of food cue processing. We propose that judging low-level visual stimulus characteristics - such as colour - triggers stimulus-related representations in the visual and even in gustatory cortex (insula), whereas discriminating abstract stimulus categories activates higher order representations in both the anterior cingulate and prefrontal cortex. Hum Brain Mapp 38:2897-2912, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Single-Column Model Simulations of Subtropical Marine Boundary-Layer Cloud Transitions Under Weakening Inversions: SCM SIMULATIONS OF CLOUD TRANSITIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neggers, R. A. J.; Ackerman, A. S.; Angevine, W. M.

Results are presented of the GASS/EUCLIPSE single-column model inter-comparison study on the subtropical marine low-level cloud transition. A central goal is to establish the performance of state-of-the-art boundary-layer schemes for weather and climate mod- els for this cloud regime, using large-eddy simulations of the same scenes as a reference. A novelty is that the comparison covers four different cases instead of one, in order to broaden the covered parameter space. Three cases are situated in the North-Eastern Pa- cific, while one reflects conditions in the North-Eastern Atlantic. A set of variables is considered that reflects key aspects of the transitionmore » process, making use of simple met- rics to establish the model performance. Using this method some longstanding problems in low level cloud representation are identified. Considerable spread exists among models concerning the cloud amount, its vertical structure and the associated impact on radia- tive transfer. The sign and amplitude of these biases differ somewhat per case, depending on how far the transition has progressed. After cloud breakup the ensemble median ex- hibits the well-known “too few too bright” problem. The boundary layer deepening rate and its state of decoupling are both underestimated, while the representation of the thin capping cloud layer appears complicated by a lack of vertical resolution. Encouragingly, some models are successful in representing the full set of variables, in particular the verti- cal structure and diurnal cycle of the cloud layer in transition. An intriguing result is that the median of the model ensemble performs best, inspiring a new approach in subgrid pa- rameterization.« less

Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.

PubMed

Jones, Matt; Love, Bradley C

2011-08-01

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements.

Developmental dyscalculia.

PubMed

Price, Gavin R; Ansari, Daniel

2013-01-01

Developmental dyscalculia (DD) is a learning disorder affecting the acquisition of school level arithmetic skills present in approximately 3-6% of the population. At the behavioral level DD is characterized by poor retrieval of arithmetic facts from memory, the use of immature calculation procedures and counting strategies, and the atypical representation and processing of numerical magnitude. At the neural level emerging evidence suggests DD is associated with atypical structure and function in brain regions associated with the representation of numerical magnitude. The current state of knowledge points to a core deficit in numerical magnitude representation in DD, but further work is required to elucidate causal mechanisms underlying the disorder. Copyright © 2013 Elsevier B.V. All rights reserved.

Solving Additive Problems at Pre-Elementary School Level with the Support of Graphical Representation

ERIC Educational Resources Information Center

Selva, Ana Coelho Vieira; Falcao, Jorge Tarcisio da Rocha; Nunes, Terezinha

2005-01-01

This research offers empirical evidence of the importance of supplying diverse symbolic representations in order to support concept development in mathematics. Graphical representation can be a helpful symbolic tool for concept development in the conceptual field of additive structures. Nevertheless, this symbolic tool has specific difficulties…

The Changing Role of Students' Representation in Poland: An Historical Appraisal

ERIC Educational Resources Information Center

Antonowicz, Dominik; Pinheiro, Rómulo; Smuzewska, Marcelina

2014-01-01

Student representation in Poland has a relatively short but turbulent history. This article offers an historical appraisal of the development of student representation at the national level in the context of rapid and deep structural changes in Polish higher education. Based on a desktop analysis of official documentation, legislation, ideological…

Random Versus Blocked Practice to Enhance Mental Representation in Golf Putting.

PubMed

Fazeli, Davoud; Taheri, HamidReza; Saberi Kakhki, Alireza

2017-06-01

The purpose of this study was to investigate changes in mental representation from either random or blocked practice when engaged in golf putting. Thirty participants were randomly assigned to random practice, blocked practice, and no-practice groups. First, we measured novice golfers' initial mental representation levels and required them to perform 18 putting trials as a pre-test. We then asked random and blocked groups to practice in accordance with their group assignment for six consecutive days (10 blocks each day, 18 trials each). A week after the last practice session, we re-measured all participants' final mental representation levels and required them to perform 18 putting trials to evaluate learning retention through practice. While those engaged in the random practice method putted more poorly during acquisition (i.e., practice) than those in blocked practice, the random practice group experienced more accurate retention during the final putting trials, and they showed a more structured mental representation than those in blocked practice, one that was more similar to that of skilled golfers. These results support the acquisition of a rich mental representation through random versus blocked practice.

An application of object-oriented knowledge representation to engineering expert systems

NASA Technical Reports Server (NTRS)

Logie, D. S.; Kamil, H.; Umaretiya, J. R.

1990-01-01

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

Verifying the equivalence of representations of the knee joint moment vector from a drop vertical jump task.

PubMed

Nichols, Julia K; O'Reilly, Oliver M

2017-03-01

Biomechanics software programs, such as Visual3D, Nexus, Cortex, and OpenSim, have the capability of generating several distinct component representations for joint moments and forces from motion capture data. These representations include those for orthonormal proximal and distal coordinate systems and a non-orthogonal joint coordinate system. In this article, a method is presented to address the challenging problem of evaluating and verifying the equivalence of these representations. The method accommodates the difficulty that there are two possible sets of non-orthogonal basis vectors that can be used to express a vector in the joint coordinate system and is illuminated using motion capture data from a drop vertical jump task. Copyright © 2016 Elsevier B.V. All rights reserved.

Adinkra (in)equivalence from Coxeter group representations: A case study

NASA Astrophysics Data System (ADS)

Chappell, Isaac; Gates, S. James; Hübsch, T.

2014-02-01

Using a MathematicaTM code, we present a straightforward numerical analysis of the 384-dimensional solution space of signed permutation 4×4 matrices, which in sets of four, provide representations of the 𝒢ℛ(4, 4) algebra, closely related to the 𝒩 = 1 (simple) supersymmetry algebra in four-dimensional space-time. Following after ideas discussed in previous papers about automorphisms and classification of adinkras and corresponding supermultiplets, we make a new and alternative proposal to use equivalence classes of the (unsigned) permutation group S4 to define distinct representations of higher-dimensional spin bundles within the context of adinkras. For this purpose, the definition of a dual operator akin to the well-known Hodge star is found to partition the space of these 𝒢ℛ(4, 4) representations into three suggestive classes.

Towards a multilevel cognitive probabilistic representation of space

NASA Astrophysics Data System (ADS)

Tapus, Adriana; Vasudevan, Shrihari; Siegwart, Roland

2005-03-01

This paper addresses the problem of perception and representation of space for a mobile agent. A probabilistic hierarchical framework is suggested as a solution to this problem. The method proposed is a combination of probabilistic belief with "Object Graph Models" (OGM). The world is viewed from a topological optic, in terms of objects and relationships between them. The hierarchical representation that we propose permits an efficient and reliable modeling of the information that the mobile agent would perceive from its environment. The integration of both navigational and interactional capabilities through efficient representation is also addressed. Experiments on a set of images taken from the real world that validate the approach are reported. This framework draws on the general understanding of human cognition and perception and contributes towards the overall efforts to build cognitive robot companions.

The analytical design of spectral measurements for multispectral remote sensor systems

NASA Technical Reports Server (NTRS)

Wiersma, D. J.; Landgrebe, D. A. (Principal Investigator)

1979-01-01

The author has identified the following significant results. In order to choose a design which will be optimal for the largest class of remote sensing problems, a method was developed which attempted to represent the spectral response function from a scene as accurately as possible. The performance of the overall recognition system was studied relative to the accuracy of the spectral representation. The spectral representation was only one of a set of five interrelated parameter categories which also included the spatial representation parameter, the signal to noise ratio, ancillary data, and information classes. The spectral response functions observed from a stratum were modeled as a stochastic process with a Gaussian probability measure. The criterion for spectral representation was defined by the minimum expected mean-square error.

Towards the use of similarity distances to music genre classification: A comparative study.

PubMed

Goienetxea, Izaro; Martínez-Otzeta, José María; Sierra, Basilio; Mendialdua, Iñigo

2018-01-01

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets -or clusters- and then generating in an automatic way a new song which is somehow "inspired" in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is.

Towards the use of similarity distances to music genre classification: A comparative study

PubMed Central

Martínez-Otzeta, José María; Sierra, Basilio; Mendialdua, Iñigo

2018-01-01

Music genre classification is a challenging research concept, for which open questions remain regarding classification approach, music piece representation, distances between/within genres, and so on. In this paper an investigation on the classification of generated music pieces is performed, based on the idea that grouping close related known pieces in different sets –or clusters– and then generating in an automatic way a new song which is somehow “inspired” in each set, the new song would be more likely to be classified as belonging to the set which inspired it, based on the same distance used to separate the clusters. Different music pieces representations and distances among pieces are used; obtained results are promising, and indicate the appropriateness of the used approach even in a such a subjective area as music genre classification is. PMID:29444160

A clustering-based graph Laplacian framework for value function approximation in reinforcement learning.

PubMed

Xu, Xin; Huang, Zhenhua; Graves, Daniel; Pedrycz, Witold

2014-12-01

In order to deal with the sequential decision problems with large or continuous state spaces, feature representation and function approximation have been a major research topic in reinforcement learning (RL). In this paper, a clustering-based graph Laplacian framework is presented for feature representation and value function approximation (VFA) in RL. By making use of clustering-based techniques, that is, K-means clustering or fuzzy C-means clustering, a graph Laplacian is constructed by subsampling in Markov decision processes (MDPs) with continuous state spaces. The basis functions for VFA can be automatically generated from spectral analysis of the graph Laplacian. The clustering-based graph Laplacian is integrated with a class of approximation policy iteration algorithms called representation policy iteration (RPI) for RL in MDPs with continuous state spaces. Simulation and experimental results show that, compared with previous RPI methods, the proposed approach needs fewer sample points to compute an efficient set of basis functions and the learning control performance can be improved for a variety of parameter settings.

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

Longitudinal associations between maternal disrupted representations, maternal interactive behavior and infant attachment: a comparison between full-term and preterm dyads.

PubMed

Hall, R A S; Hoffenkamp, H N; Tooten, A; Braeken, J; Vingerhoets, A J J M; van Bakel, H J A

2015-04-01

This prospective study examined whether or not a mother's representations of her infant were more often disrupted after premature childbirth. Furthermore, the study examined if different components of maternal interactive behavior mediated the relation between maternal disrupted representations and infant attachment. The participants were mothers of full-term (n = 75), moderately preterm (n = 68) and very preterm infants (n = 67). Maternal representations were assessed by the Working Model of the Child Interview at 6 months post-partum. Maternal interactive behavior was evaluated at 6 and 24 months post-partum, using the National Institute of Child Health and Human Development Early Care Research Network mother-infant observation scales. Infant attachment was observed at 24 months post-partum and was coded by the Attachment Q-Set. The results reveal that a premature childbirth does not necessarily generate disrupted maternal representations of the infant. Furthermore, maternal interactive behavior appears to be an important mechanism through which maternal representations influence the development of infant attachment in full-term and preterm infants. Early assessment of maternal representations can identify mother-infant dyads at risk, in full-term and preterm samples.

Identification of methylation haplotype blocks aids in deconvolution of heterogeneous tissue samples and tumor tissue-of-origin mapping from plasma DNA.

PubMed

Guo, Shicheng; Diep, Dinh; Plongthongkum, Nongluk; Fung, Ho-Lim; Zhang, Kang; Zhang, Kun

2017-04-01

Adjacent CpG sites in mammalian genomes can be co-methylated owing to the processivity of methyltransferases or demethylases, yet discordant methylation patterns have also been observed, which are related to stochastic or uncoordinated molecular processes. We focused on a systematic search and investigation of regions in the full human genome that show highly coordinated methylation. We defined 147,888 blocks of tightly coupled CpG sites, called methylation haplotype blocks, after analysis of 61 whole-genome bisulfite sequencing data sets and validation with 101 reduced-representation bisulfite sequencing data sets and 637 methylation array data sets. Using a metric called methylation haplotype load, we performed tissue-specific methylation analysis at the block level. Subsets of informative blocks were further identified for deconvolution of heterogeneous samples. Finally, using methylation haplotypes we demonstrated quantitative estimation of tumor load and tissue-of-origin mapping in the circulating cell-free DNA of 59 patients with lung or colorectal cancer.

Sociology through Photography

ERIC Educational Resources Information Center

Hyde, Katherine

2015-01-01

This chapter describes how photography can inspire and cultivate sociological mindfulness. One set of assignments uses self-portraiture to highlight the complexity of visual representations of social identity. Another uses photography to guide sociological inquiry. Both sets of assignments draw on the Literacy Through Photography methodology,…

The Dynamics of Phonological Planning

ERIC Educational Resources Information Center

Roon, Kevin D.

2013-01-01

This dissertation proposes a dynamical computational model of the timecourse of phonological parameter setting. In the model, phonological representations embrace phonetic detail, with phonetic parameters represented as activation fields that evolve over time and determine the specific parameter settings of a planned utterance. Existing models of…

Spatiotemporal historical datasets at micro-level for geocoded individuals in five Swedish parishes, 1813–1914

PubMed Central

Hedefalk, Finn; Svensson, Patrick; Harrie, Lars

2017-01-01

This paper presents datasets that enable historical longitudinal studies of micro-level geographic factors in a rural setting. These types of datasets are new, as historical demography studies have generally failed to properly include the micro-level geographic factors. Our datasets describe the geography over five Swedish rural parishes, and by linking them to a longitudinal demographic database, we obtain a geocoded population (at the property unit level) for this area for the period 1813–1914. The population is a subset of the Scanian Economic Demographic Database (SEDD). The geographic information includes the following feature types: property units, wetlands, buildings, roads and railroads. The property units and wetlands are stored in object-lifeline time representations (information about creation, changes and ends of objects are recorded in time), whereas the other feature types are stored as snapshots in time. Thus, the datasets present one of the first opportunities to study historical spatio-temporal patterns at the micro-level. PMID:28398288

Motion representation of the long fingers: a proposal for the definitions of new anatomical frames.

PubMed

Coupier, Jérôme; Moiseev, Fédor; Feipel, Véronique; Rooze, Marcel; Van Sint Jan, Serge

2014-04-11

Despite the availability of the International Society of Biomechanics (ISB) recommendations for the orientation of anatomical frames, no consensus exists about motion representations related to finger kinematics. This paper proposes novel anatomical frames for motion representation of the phalangeal segments of the long fingers. A three-dimensional model of a human forefinger was acquired from a non-pathological fresh-frozen hand. Medical imaging was used to collect phalangeal discrete positions. Data processing was performed using a customized software interface ("lhpFusionBox") to create a specimen-specific model and to reconstruct the discrete motion path. Five examiners virtually palpated two sets of landmarks. These markers were then used to build anatomical frames following two methods: a reference method following ISB recommendations and a newly-developed method based on the mean helical axis (HA). Motion representations were obtained and compared between examiners. Virtual palpation precision was around 1mm, which is comparable to results from the literature. The comparison of the two methods showed that the helical axis method seemed more reproducible between examiners especially for secondary, or accessory, motions. Computed Root Mean Square distances comparing methods showed that the ISB method displayed a variability 10 times higher than the HA method. The HA method seems to be suitable for finger motion representation using discrete positions from medical imaging. Further investigations are required before being able to use the methodology with continuous tracking of markers set on the subject's hand. Copyright © 2014 Elsevier Ltd. All rights reserved.

Wait-Time and Multiple Representation Levels in Chemistry Lessons

ERIC Educational Resources Information Center

Li, Winnie Sim Siew; Arshad, Mohammad Yusof

2014-01-01

Wait-time is an important aspect in a teaching and learning process, especially after the teacher has posed questions to students, as it is one of the factors in determining quality of students' responses. This article describes the practices of wait-time one after teacher's questions at multiple representation levels among twenty three chemistry…

A Supervisor like Me: Race, Representation, and the Satisfaction and Turnover Decisions of Public Sector Employees

ERIC Educational Resources Information Center

Grissom, Jason A.; Keiser, Lael R.

2011-01-01

Studies of race representation in public organizations illustrate the importance of bureaucrat race in determining client-level outcomes. Building "upward" from this research, this study examines how supervisor race impacts outcomes for street-level bureaucrats using data from a nationally representative sample of public schools. Employing…

Kac determinant and singular vector of the level N representation of Ding-Iohara-Miki algebra

NASA Astrophysics Data System (ADS)

Ohkubo, Yusuke

2018-05-01

In this paper, we obtain the formula for the Kac determinant of the algebra arising from the level N representation of the Ding-Iohara-Miki algebra. It is also discovered that its singular vectors correspond to generalized Macdonald functions (the q-deformed version of the AFLT basis).

A high-level 3D visualization API for Java and ImageJ.

PubMed

Schmid, Benjamin; Schindelin, Johannes; Cardona, Albert; Longair, Mark; Heisenberg, Martin

2010-05-21

Current imaging methods such as Magnetic Resonance Imaging (MRI), Confocal microscopy, Electron Microscopy (EM) or Selective Plane Illumination Microscopy (SPIM) yield three-dimensional (3D) data sets in need of appropriate computational methods for their analysis. The reconstruction, segmentation and registration are best approached from the 3D representation of the data set. Here we present a platform-independent framework based on Java and Java 3D for accelerated rendering of biological images. Our framework is seamlessly integrated into ImageJ, a free image processing package with a vast collection of community-developed biological image analysis tools. Our framework enriches the ImageJ software libraries with methods that greatly reduce the complexity of developing image analysis tools in an interactive 3D visualization environment. In particular, we provide high-level access to volume rendering, volume editing, surface extraction, and image annotation. The ability to rely on a library that removes the low-level details enables concentrating software development efforts on the algorithm implementation parts. Our framework enables biomedical image software development to be built with 3D visualization capabilities with very little effort. We offer the source code and convenient binary packages along with extensive documentation at http://3dviewer.neurofly.de.

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya

2015-11-15

Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discretemore » models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μ{sub recon} = − 2.7 × 10{sup −3} mm{sup −1}, σ{sub recon} = 7.0 × 10{sup −3} mm{sup −1}) and (μ{sub CT} = − 2.5 × 10{sup −3} mm{sup −1}, σ{sub CT} = 5.3 × 10{sup −3} mm{sup −1}), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy.« less

A continuous surface reconstruction method on point cloud captured from a 3D surface photogrammetry system

PubMed Central

Liu, Wenyang; Cheung, Yam; Sabouri, Pouya; Arai, Tatsuya J.; Sawant, Amit; Ruan, Dan

2015-01-01

Purpose: To accurately and efficiently reconstruct a continuous surface from noisy point clouds captured by a surface photogrammetry system (VisionRT). Methods: The authors have developed a level-set based surface reconstruction method on point clouds captured by a surface photogrammetry system (VisionRT). The proposed method reconstructs an implicit and continuous representation of the underlying patient surface by optimizing a regularized fitting energy, offering extra robustness to noise and missing measurements. By contrast to explicit/discrete meshing-type schemes, their continuous representation is particularly advantageous for subsequent surface registration and motion tracking by eliminating the need for maintaining explicit point correspondences as in discrete models. The authors solve the proposed method with an efficient narrowband evolving scheme. The authors evaluated the proposed method on both phantom and human subject data with two sets of complementary experiments. In the first set of experiment, the authors generated a series of surfaces each with different black patches placed on one chest phantom. The resulting VisionRT measurements from the patched area had different degree of noise and missing levels, since VisionRT has difficulties in detecting dark surfaces. The authors applied the proposed method to point clouds acquired under these different configurations, and quantitatively evaluated reconstructed surfaces by comparing against a high-quality reference surface with respect to root mean squared error (RMSE). In the second set of experiment, the authors applied their method to 100 clinical point clouds acquired from one human subject. In the absence of ground-truth, the authors qualitatively validated reconstructed surfaces by comparing the local geometry, specifically mean curvature distributions, against that of the surface extracted from a high-quality CT obtained from the same patient. Results: On phantom point clouds, their method achieved submillimeter reconstruction RMSE under different configurations, demonstrating quantitatively the faith of the proposed method in preserving local structural properties of the underlying surface in the presence of noise and missing measurements, and its robustness toward variations of such characteristics. On point clouds from the human subject, the proposed method successfully reconstructed all patient surfaces, filling regions where raw point coordinate readings were missing. Within two comparable regions of interest in the chest area, similar mean curvature distributions were acquired from both their reconstructed surface and CT surface, with mean and standard deviation of (μrecon = − 2.7 × 10−3 mm−1, σrecon = 7.0 × 10−3 mm−1) and (μCT = − 2.5 × 10−3 mm−1, σCT = 5.3 × 10−3 mm−1), respectively. The agreement of local geometry properties between the reconstructed surfaces and the CT surface demonstrated the ability of the proposed method in faithfully representing the underlying patient surface. Conclusions: The authors have integrated and developed an accurate level-set based continuous surface reconstruction method on point clouds acquired by a 3D surface photogrammetry system. The proposed method has generated a continuous representation of the underlying phantom and patient surfaces with good robustness against noise and missing measurements. It serves as an important first step for further development of motion tracking methods during radiotherapy. PMID:26520747

Stochastic level-set variational implicit-solvent approach to solute-solvent interfacial fluctuations

PubMed Central

Zhou, Shenggao; Sun, Hui; Cheng, Li-Tien; Dzubiella, Joachim; McCammon, J. Andrew

2016-01-01

Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the inclusion of fluctuations into the VISM and understanding the impact of interfacial fluctuations on biomolecular solvation with an implicit-solvent approach. PMID:27497546

Representation learning via Dual-Autoencoder for recommendation.

PubMed

Zhuang, Fuzhen; Zhang, Zhiqiang; Qian, Mingda; Shi, Chuan; Xie, Xing; He, Qing

2017-06-01

Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e.g., social relationships of users and items' attributions, to improve the recommendation performance under the matrix factorization framework. However, matrix factorization methods may not make full use of the limited information from rating or check-in matrices, and achieve unsatisfying results. Recently, deep learning has proven able to learn good representation in natural language processing, image classification, and so on. Along this line, we propose a new representation learning framework called Recommendation via Dual-Autoencoder (ReDa). In this framework, we simultaneously learn the new hidden representations of users and items using autoencoders, and minimize the deviations of training data by the learnt representations of users and items. Based on this framework, we develop a gradient descent method to learn hidden representations. Extensive experiments conducted on several real-world data sets demonstrate the effectiveness of our proposed method compared with state-of-the-art matrix factorization based methods. Copyright © 2017 Elsevier Ltd. All rights reserved.