Representation and Integration: Combining Robot Control, High-Level Planning, and Action Learning

DEFF Research Database (Denmark)

Petrick, Ronald; Kraft, Dirk; Mourao, Kira

We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....... learning, and focuses on the representational needs of these components.We also make use of a simple representational unit called an instantiated state transition fragment (ISTF) and a related structure called an object-action complex (OAC). The goal of this work is a general approach for inducing high...

Analysis-Driven Design of Representations For Sensing-Action Systems

Science.gov (United States)

2017-10-01

representation, under the action of a ( group ) invertible nuisance. For instance, the theory of Mallat aims to compute a “transform” from which the original...valid for locally compact groups . The problem is that, in vision, occlusions are not a group , so any theory that hinges on nuisances having a group ...knowledge, the first complete theory of representation for decision and control task, which has shown not only to encompass and explain all known

Shared Action Spaces: a basis function framework for social re-calibration of sensorimotor representations supporting joint action

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Giovanni ePezzulo

2013-11-01

Full Text Available The article explores the possibilities of formalizing and explaining the mechanisms that support spatial and social perspective alignment sustained over the duration of a social interaction. The basic proposed principle is that in social contexts the mechanisms for sensorimotor transformations and multisensory integration (learn to incorporate information relative to the other actor(s, similar to the "re-calibration" of visual receptive fields in response to repeated tool use. This process aligns or merges the co-actors' spatial representations and creates a "Shared Action Space" supporting key computations of social interactions and joint actions; for example, the remapping between the coordinate systems and frames of reference of the co-actors, including perspective taking, the sensorimotor transformations required for lifting jointly an object, and the predictions of the sensory effects of such joint action. The social re-calibration is proposed to be based on common basis function maps and could constitute an optimal solution to sensorimotor transformation and multisensory integration in joint action or more in general social interaction contexts. However, certain situations such as discrepant postural and viewpoint alignment and associated differences in perspectives between the co-actors could constrain the process quite differently. We discuss how alignment is achieved in the first place, and how it is maintained over time, providing a taxonomy of various forms and mechanisms of space alignment and overlap based, for instance, on automaticity vs. control of the transformations between the two agents. Finally, we discuss the link between low-level mechanisms for the sharing of space and high-level mechanisms for the sharing of cognitive representations.

Path integral representations in noncommutative quantum mechanics and noncommutative version of Berezin-Marinov action

Energy Technology Data Exchange (ETDEWEB)

Gitman, D.M. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, SP (Brazil); Kupriyanov, V.G. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, SP (Brazil); Tomsk State University, Physics Department, Tomsk (Russian Federation)

2008-03-15

It is known that the actions of field theories on a noncommutative space-time can be written as some modified (we call them {theta}-modified) classical actions already on the commutative space-time (introducing a star product). Then the quantization of such modified actions reproduces both space-time noncommutativity and the usual quantum mechanical features of the corresponding field theory. In the present article, we discuss the problem of constructing {theta}-modified actions for relativistic QM. We construct such actions for relativistic spinless and spinning particles. The key idea is to extract {theta}-modified actions of the relativistic particles from path-integral representations of the corresponding noncommutative field theory propagators. We consider the Klein-Gordon and Dirac equations for the causal propagators in such theories. Then we construct for the propagators path-integral representations. Effective actions in such representations we treat as {theta}-modified actions of the relativistic particles. To confirm the interpretation, we canonically quantize these actions. Thus, we obtain the Klein-Gordon and Dirac equations in the noncommutative field theories. The {theta}-modified action of the relativistic spinning particle is just a generalization of the Berezin-Marinov pseudoclassical action for the noncommutative case. (orig.)

The structure of affective action representations: temporal binding of affective response codes.

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Eder, Andreas B; Müsseler, Jochen; Hommel, Bernhard

2012-01-01

Two experiments examined the hypothesis that preparing an action with a specific affective connotation involves the binding of this action to an affective code reflecting this connotation. This integration into an action plan should lead to a temporary occupation of the affective code, which should impair the concurrent representation of affectively congruent events, such as the planning of another action with the same valence. This hypothesis was tested with a dual-task setup that required a speeded choice between approach- and avoidance-type lever movements after having planned and before having executed an evaluative button press. In line with the code-occupation hypothesis, slower lever movements were observed when the lever movement was affectively compatible with the prepared evaluative button press than when the two actions were affectively incompatible. Lever movements related to approach and avoidance and evaluative button presses thus seem to share a code that represents affective meaning. A model of affective action control that is based on the theory of event coding is discussed.

A Common Representation of Spatial Features Drives Action and Perception

DEFF Research Database (Denmark)

Christiansen, Jens H; Christensen, Jeppe Høy; Grünbaum, Thor

2014-01-01

Spatial features of an object can be specified using two different response types: either by use of symbols or motorically by directly acting upon the object. Is this response dichotomy reflected in a dual representation of the visual world: one for perception and one for action? Previously, symb...... of matching object-processing characteristics is also in agreement with the idea of a common representation driving both response types....

Mental Representations in Musical Processing and their Role in Action-Perception Loops

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Rebecca S. Schaefer

2015-05-01

Full Text Available I address the diverging usage of the term "imagery" by delineating different types of imagery, each of which is supported by multimodal mental representations that are informed and modulated by the body and its in- and outputs, and that in turn modulate and inform perception and action through predictive processing. These multimodal representations, viewed here as mental models, underlie our individual perceptual experience of music, which is constructed in the listener as it is perceived and interpreted. While tracking incoming auditory information, mental representations of music unfold on multiple levels as we listen, from regularities detected across notes to the structure of entire pieces of music, generating predictions for different musical aspects. These predictions lead to specific percepts and behavioral outputs, illustrating a tight coupling of cognition, perception and action. This coupling and the prominence of predictive mechanisms in music processing are described in the context of the broader role of predictive processing in cognitive function, which is well suited to account for the role of mental models in musical perception and action. As a proxy for mental representations, investigating the cerebral correlates of constructive imagination may offer an experimentally tractable approach to clarifying how mental models of music are implemented in the brain.

On the Dynamics of Action Representations Evoked by Names of Manipulable Objects

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Bub, Daniel N.; Masson, Michael E. J.

2012-01-01

Two classes of hand action representations are shown to be activated by listening to the name of a manipulable object (e.g., cellphone). The functional action associated with the proper use of an object is evoked soon after the onset of its name, as indicated by primed execution of that action. Priming is sustained throughout the duration of the…

Mental Representation and Motor Imagery Training

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Thomas eSchack

2014-05-01

Full Text Available Research in sports, dance and rehabilitation has shown that Basic Action Concepts (BACs are fundamental building blocks of mental action representations. BACs are based on chunked body postures related to common functions for realizing action goals. In this paper, we outline issues in research methodology and an experimental method, SDA-M (structural dimensional analysis of mental representation, to assess action-relevant representational structures that reflect the organization of BACs. The SDA-M reveals a strong relationship between cognitive representation and performance if complex actions are performed. We show how the SDA-M can improve motor imagery training and how it contributes to our understanding of coaching processes. The SDA-M capitalizes on the objective measurement of individual mental movement representations before training and the integration of these results into the motor imagery training. Such motor imagery training based on mental representations has been applied successfully in professional sports such as golf, volleyball, gymnastics, windsurfing, and recently in the rehabilitation of patients who have suffered a stroke.

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.

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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.

Body-specific representations of action word meanings in right and left handers

OpenAIRE

Daniel Casasanto

2007-01-01

If understanding action words involves mentally simulating our own actions, then the neurocognitive representation of word meanings must differ for people with different kinds of bodies, who perform actions in systematically different ways. In a test of the _Body-Specificity Hypothesis_, right- and left-handers were compared on two motor-meaning congruity tasks. Double dissociations in both action execution and recognition memory results showed that right and left handers form body-specific r...

Idiosyncratic representation of peripersonal space depends on the success of one's own motor actions, but also the successful actions of others!

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Coello, Yann; Quesque, François; Gigliotti, Maria-Francesca; Ott, Laurent; Bruyelle, Jean-Luc

2018-01-01

Peripersonal space is a multisensory representation of the environment around the body in relation to the motor system, underlying the interactions with the physical and social world. Although changing body properties and social context have been shown to alter the functional processing of space, little is known about how changing the value of objects influences the representation of peripersonal space. In two experiments, we tested the effect of modifying the spatial distribution of reward-yielding targets on manual reaching actions and peripersonal space representation. Before and after performing a target-selection task consisting of manually selecting a set of targets on a touch-screen table, participants performed a two-alternative forced-choice reachability-judgment task. In the target-selection task, half of the targets were associated with a reward (change of colour from grey to green, providing 1 point), the other half being associated with no reward (change of colour from grey to red, providing no point). In Experiment 1, the target-selection task was performed individually with the aim of maximizing the point count, and the distribution of the reward-yielding targets was either 50%, 25% or 75% in the proximal and distal spaces. In Experiment 2, the target-selection task was performed in a social context involving cooperation between two participants to maximize the point count, and the distribution of the reward-yielding targets was 50% in the proximal and distal spaces. Results showed that changing the distribution of the reward-yielding targets or introducing the social context modified concurrently the amplitude of self-generated manual reaching actions and the representation of peripersonal space. Moreover, a decrease of the amplitude of manual reaching actions caused a reduction of peripersonal space when resulting from the distribution of reward-yielding targets, while this effect was not observed in a social interaction context. In that case, the

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

Representation of knowledge in artificially intelligent systems is discussed. Types of knowledge that might need to be represented in AI systems are listed, and include knowledge about objects, events, knowledge about how to do things, and knowledge about what human beings know (meta-knowledge). The use of knowledge in AI systems is discussed in terms of acquiring and retrieving knowledge and reasoning about known facts. Different kinds of reasonings or representations are ghen described with some examples given. These include formal reasoning or logical representation, which is related to mathematical logic, production systems, which are based on the idea of condition-action pairs (production), procedural reasoning, which uses pre-formed plans to solve problems, frames, which provide a structure for representing knowledge in an organized manner, direct analogical representations, which represent knowledge in such a manner that permits some observation without deduction

Cognitive, perceptual and action-oriented representations of falling objects.

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Zago, Myrka; Lacquaniti, Francesco

2005-01-01

We interact daily with moving objects. How accurate are our predictions about objects' motions? What sources of information do we use? These questions have received wide attention from a variety of different viewpoints. On one end of the spectrum are the ecological approaches assuming that all the information about the visual environment is present in the optic array, with no need to postulate conscious or unconscious representations. On the other end of the spectrum are the constructivist approaches assuming that a more or less accurate representation of the external world is built in the brain using explicit or implicit knowledge or memory besides sensory inputs. Representations can be related to naive physics or to context cue-heuristics or to the construction of internal copies of environmental invariants. We address the issue of prediction of objects' fall at different levels. Cognitive understanding and perceptual judgment of simple Newtonian dynamics can be surprisingly inaccurate. By contrast, motor interactions with falling objects are often very accurate. We argue that the pragmatic action-oriented behaviour and the perception-oriented behaviour may use different modes of operation and different levels of representation.

Knowledge representation and knowledge base design for operator advisor system

International Nuclear Information System (INIS)

Hangos, K.M.; Sziano, T.; Tapolcai, L.

1990-01-01

The problems of knowledge representation, knowledge base handling and design has been described for an Operator Advisor System in the Paks Nuclear Power Plant. The Operator Advisor System is to be implemented as a part of the 5th and 6th unit. The knowledge of the Operator Advisor system is described by a few elementary knowledge items (diagnostic event functions, fault graph, action trees), weighted directed graphs have been found as their common structure. List-type and relational representation of these graphs have been used for the on-line and off-line part of the knowledge base respectively. A uniform data base design and handling has been proposed which consists of a design system, a knowledge base editor and a knowledge base compiler

Marginalised Stacked Denoising Autoencoders for Robust Representation of Real-Time Multi-View Action Recognition

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Feng Gu

2015-07-01

Full Text Available Multi-view action recognition has gained a great interest in video surveillance, human computer interaction, and multimedia retrieval, where multiple cameras of different types are deployed to provide a complementary field of views. Fusion of multiple camera views evidently leads to more robust decisions on both tracking multiple targets and analysing complex human activities, especially where there are occlusions. In this paper, we incorporate the marginalised stacked denoising autoencoders (mSDA algorithm to further improve the bag of words (BoWs representation in terms of robustness and usefulness for multi-view action recognition. The resulting representations are fed into three simple fusion strategies as well as a multiple kernel learning algorithm at the classification stage. Based on the internal evaluation, the codebook size of BoWs and the number of layers of mSDA may not significantly affect recognition performance. According to results on three multi-view benchmark datasets, the proposed framework improves recognition performance across all three datasets and outputs record recognition performance, beating the state-of-art algorithms in the literature. It is also capable of performing real-time action recognition at a frame rate ranging from 33 to 45, which could be further improved by using more powerful machines in future applications.

Dynamic evocation of hand action representations during sentence comprehension.

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Masson, Michael E J; Bub, Daniel N; Lavelle, Hillary

2013-08-01

When listening to a sentence describing an interaction with a manipulable object, understanding the actor's intentions is shown to have a striking influence on action representations evoked during comprehension. Subjects performed a cued reach and grasp response while listening to a context sentence. Responses were primed when they were consistent with the proximal intention of an actor ("John lifted the cell phone..."), but this effect was evanescent and appeared only when sentences mentioned the proximal intention first. When the sentence structure was changed to mention the distal intention first ("To clear the shelf..."), priming effects were no longer context specific and actions pertaining to the function of an object were clearly favored. These results are not compatible with a straightforward mental-simulation account of sentence comprehension but instead reflect a hierarchy of intentions distinguishing how and why actions are performed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Dissociating the Representation of Action- and Sound-Related Concepts in Middle Temporal Cortex

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Kiefer, Markus; Trumpp, Natalie; Herrnberger, Barbel; Sim, Eun-Jin; Hoenig, Klaus; Pulvermuller, Friedemann

2012-01-01

Modality-specific models of conceptual memory propose close links between concepts and the sensory-motor systems. Neuroimaging studies found, in different subject groups, that action-related and sound-related concepts activated different parts of posterior middle temporal gyrus (pMTG), suggesting a modality-specific representation of conceptual…

Multi-representation based on scientific investigation for enhancing students’ representation skills

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Siswanto, J.; Susantini, E.; Jatmiko, B.

2018-03-01

This research aims to implementation learning physics with multi-representation based on the scientific investigation for enhancing students’ representation skills, especially on the magnetic field subject. The research design is one group pretest-posttest. This research was conducted in the department of mathematics education, Universitas PGRI Semarang, with the sample is students of class 2F who take basic physics courses. The data were obtained by representation skills test and documentation of multi-representation worksheet. The Results show gain analysis value of .64 which means some medium improvements. The result of t-test (α = .05) is shows p-value = .001. This learning significantly improves students representation skills.

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

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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%).

Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

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Rui Sun

2016-08-01

Full Text Available Vision-based pedestrian detection has become an active topic in computer vision and autonomous vehicles. It aims at detecting pedestrians appearing ahead of the vehicle using a camera so that autonomous vehicles can assess the danger and take action. Due to varied illumination and appearance, complex background and occlusion pedestrian detection in outdoor environments is a difficult problem. In this paper, we propose a novel hierarchical feature extraction and weighted kernel sparse representation model for pedestrian classification. Initially, hierarchical feature extraction based on a CENTRIST descriptor is used to capture discriminative structures. A max pooling operation is used to enhance the invariance of varying appearance. Then, a kernel sparse representation model is proposed to fully exploit the discrimination information embedded in the hierarchical local features, and a Gaussian weight function as the measure to effectively handle the occlusion in pedestrian images. Extensive experiments are conducted on benchmark databases, including INRIA, Daimler, an artificially generated dataset and a real occluded dataset, demonstrating the more robust performance of the proposed method compared to state-of-the-art pedestrian classification methods.

Bruner's Three Forms of Representation Revisited: Action, Pictures and Words for Effective Computer Instruction.

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Presno, Caroline

1997-01-01

Discusses computer instruction in light of Bruner's theory of three forms of representation (action, icons, and symbols). Examines how studies regarding Paivio's dual-coding theory and studies focusing on procedural knowledge support Bruner's theory. Provides specific examples for instruction in three categories: demonstrations, pictures and…

Adaptive control of human action: The role of outcome representations and reward signals

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Hans eMarien

2013-09-01

Full Text Available The present paper aims to advance the understanding of the control of human behavior by integrating two lines of literature that so far have led separate lives. First, one line of literature is concerned with the ideomotor principle of human behavior, according to which actions are represented in terms of their outcomes. The second line of literature mainly considers the role of reward signals in adaptive control. Here, we offer a combined perspective on how outcome representations and reward signals work together to modulate adaptive control processes. We propose that reward signals signify the value of outcome representations and facilitate the recruitment of control resources in situations where behavior needs to be maintained or adapted to attain the represented outcome. We discuss recent research demonstrating how adaptive control of goal-directed behavior may emerge when outcome representations are co-activated with positive reward signals.

The interaction between felt touch and tactile consequences of observed actions: an action-based somatosensory congruency paradigm.

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Deschrijver, Eliane; Wiersema, Jan R; Brass, Marcel

2016-07-01

Action observation leads to a representation of both the motor aspect of an observed action (motor simulation) and its somatosensory consequences (action-based somatosensory simulation) in the observer's brain. In the current electroencephalography-study, we investigated the neuronal interplay of action-based somatosensory simulation and felt touch. We presented index or middle finger tapping movements of a human or a wooden hand, while simultaneously presenting 'tap-like' tactile sensations to either the corresponding or non-corresponding fingertip of the participant. We focused on an early stage of somatosensory processing [P50, N100 and N140 sensory evoked potentials (SEPs)] and on a later stage of higher-order processing (P3-complex). The results revealed an interaction effect of animacy and congruency in the early P50 SEP and an animacy effect in the N100/N140 SEPs. In the P3-complex, we found an interaction effect indicating that the influence of congruency was larger in the human than in the wooden hand. We argue that the P3-complex may reflect higher-order self-other distinction by signaling simulated action-based touch that does not match own tactile information. As such, the action-based somatosensory congruency paradigm might help understand higher-order social processes from a somatosensory point of view. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Human action recognition based on estimated weak poses

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Gong, Wenjuan; Gonzàlez, Jordi; Roca, Francesc Xavier

2012-12-01

We present a novel method for human action recognition (HAR) based on estimated poses from image sequences. We use 3D human pose data as additional information and propose a compact human pose representation, called a weak pose, in a low-dimensional space while still keeping the most discriminative information for a given pose. With predicted poses from image features, we map the problem from image feature space to pose space, where a Bag of Poses (BOP) model is learned for the final goal of HAR. The BOP model is a modified version of the classical bag of words pipeline by building the vocabulary based on the most representative weak poses for a given action. Compared with the standard k-means clustering, our vocabulary selection criteria is proven to be more efficient and robust against the inherent challenges of action recognition. Moreover, since for action recognition the ordering of the poses is discriminative, the BOP model incorporates temporal information: in essence, groups of consecutive poses are considered together when computing the vocabulary and assignment. We tested our method on two well-known datasets: HumanEva and IXMAS, to demonstrate that weak poses aid to improve action recognition accuracies. The proposed method is scene-independent and is comparable with the state-of-art method.

Neural representations of kinematic laws of motion: evidence for action-perception coupling.

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Dayan, Eran; Casile, Antonino; Levit-Binnun, Nava; Giese, Martin A; Hendler, Talma; Flash, Tamar

2007-12-18

Behavioral and modeling studies have established that curved and drawing human hand movements obey the 2/3 power law, which dictates a strong coupling between movement curvature and velocity. Human motion perception seems to reflect this constraint. The functional MRI study reported here demonstrates that the brain's response to this law of motion is much stronger and more widespread than to other types of motion. Compliance with this law is reflected in the activation of a large network of brain areas subserving motor production, visual motion processing, and action observation functions. Hence, these results strongly support the notion of similar neural coding for motion perception and production. These findings suggest that cortical motion representations are optimally tuned to the kinematic and geometrical invariants characterizing biological actions.

Action Categories in Lateral Occipitotemporal Cortex Are Organized Along Sociality and Transitivity.

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Wurm, Moritz F; Caramazza, Alfonso; Lingnau, Angelika

2017-01-18

How neural specificity for distinct conceptual knowledge categories arises is central for understanding the organization of semantic memory in the human brain. Although there is a large body of research on the neural processing of distinct object categories, the organization of action categories remains largely unknown. In particular, it is unknown whether different action categories follow a specific topographical organization on the cortical surface analogously to the category-specific organization of object knowledge. Here, we tested whether the neural representation of action knowledge is organized in terms of nonsocial versus social and object-unrelated versus object-related actions (sociality and transitivity, respectively, hereafter). We hypothesized a major distinction of sociality and transitivity along dorsal and ventral lateral occipitotemporal cortex (LOTC), respectively. Using fMRI-based multivoxel pattern analysis, we identified neural representations of action information associated with sociality and transitivity in bilateral LOTC. Representational similarity analysis revealed a dissociation between dorsal and ventral LOTC. We found that action representations in dorsal LOTC are segregated along features of sociality, whereas action representations in ventral LOTC are segregated along features of transitivity. In addition, representations of sociality and transitivity features were found more anteriorly in LOTC than representations of specific subtypes of actions, suggesting a posterior-anterior gradient from concrete to abstract action features. These findings elucidate how the neural representations of perceptually and conceptually diverse actions are organized in distinct subsystems in the LOTC. The lateral occipitotemporal cortex (LOTC) is critically involved in the recognition of objects and actions, but our knowledge about the underlying organizing principles is limited. Here, we discovered a dorsal-ventral distinction of actions in LOTC

Exploration of solids based on representation systems

Directory of Open Access Journals (Sweden)

Publio Suárez Sotomonte

2011-01-01

Full Text Available This article refers to some of the findings of a research project implemented as a teaching strategy to generate environments for the learning of platonic and archimedean solids, with a group of eighth grade students. This strategy was based on the meaningful learning approach and on the use of representation systems using the ontosemiotic approach in mathematical education, as a framework for the construction of mathematical concepts. This geometry teaching strategy adopts the stages of exploration, representation-modeling, formal construction and study of applications. It uses concrete, physical and tangible materials for origami, die making, and structures for the construction of threedimensional solids considered external tangible solid representation systems, as well as computer based educational tools to design dynamic geometry environments as intangible external representation systems.These strategies support both the imagination and internal systems of representation, fundamental to the comprehension of geometry concepts.

Supervised Filter Learning for Representation Based Face Recognition.

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Chao Bi

Full Text Available Representation based classification methods, such as Sparse Representation Classification (SRC and Linear Regression Classification (LRC have been developed for face recognition problem successfully. However, most of these methods use the original face images without any preprocessing for recognition. Thus, their performances may be affected by some problematic factors (such as illumination and expression variances in the face images. In order to overcome this limitation, a novel supervised filter learning algorithm is proposed for representation based face recognition in this paper. The underlying idea of our algorithm is to learn a filter so that the within-class representation residuals of the faces' Local Binary Pattern (LBP features are minimized and the between-class representation residuals of the faces' LBP features are maximized. Therefore, the LBP features of filtered face images are more discriminative for representation based classifiers. Furthermore, we also extend our algorithm for heterogeneous face recognition problem. Extensive experiments are carried out on five databases and the experimental results verify the efficacy of the proposed algorithm.

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

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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.

3D hierarchical spatial representation and memory of multimodal sensory data

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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

An analysis of primary school students’ representational ability in mathematics based on gender perspective

Science.gov (United States)

Kowiyah; Mulyawati, I.

2018-01-01

Mathematic representation is one of the basic mathematic skills that allows students to communicate their mathematic ideas through visual realities such as pictures, tables, mathematic expressions and mathematic equities. The present research aims at: 1) analysing students’ mathematic representation ability in solving mathematic problems and 2) examining the difference of students’ mathematic ability based on their gender. A total of sixty primary school students participated in this study comprising of thirty males and thirty females. Data required in this study were collected through mathematic representation tests, interviews and test evaluation rubric. Findings of this study showed that students’ mathematic representation of visual realities (image and tables) was reported higher at 62.3% than at in the form of description (or statement) at 8.6%. From gender perspective, male students performed better than the females at action planning stage. The percentage of males was reported at 68% (the highest), 33% (medium) and 21.3% (the lowest) while the females were at 36% (the highest), 37.7% (medium) and 32.6% (the lowest).

Grasp Representations Depend on Knowledge and Attention

Science.gov (United States)

Chua, Kao-Wei; Bub, Daniel N.; Masson, Michael E. J.; Gauthier, Isabel

2018-01-01

Seeing pictures of objects activates the motor cortex and can have an influence on subsequent grasping actions. However, the exact nature of the motor representations evoked by these pictures is unclear. For example, action plans engaged by pictures could be most affected by direct visual input and computed online based on object shape.…

Distributed representations of action sequences in anterior cingulate cortex: A recurrent neural network approach.

Science.gov (United States)

Shahnazian, Danesh; Holroyd, Clay B

2018-02-01

Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed representations across a network of interconnected processing units. Based on the proposal that ACC is concerned with the execution of extended, goal-directed action sequences, we trained a recurrent neural network to predict each successive step of several sequences associated with multiple tasks. In keeping with neurophysiological observations from nonhuman animals, the network yields distributed patterns of activity across ACC neurons that track the progression of each sequence, and in keeping with human neuroimaging data, the network produces discrepancy signals when any step of the sequence deviates from the predicted step. These simulations illustrate a novel approach for investigating ACC function.

A neural network model of causative actions

Directory of Open Access Journals (Sweden)

Jeremy eLee-Hand

2015-06-01

Full Text Available A common idea in models of action representation is that actions are represented in terms of their perceptual effects (see e.g. Prinz, 1997; Hommel et al., 2001; Sahin et al., 2007; Umilta et al., 2008; Hommel et al., 2013. In this paper we extend existing models of effect-based action representations to account for a novel distinction. Some actions bring about effects that are independent events in their own right: for instance, if John 'smashes' a cup, he brings about the event of 'the cup smashing'. Other actions do not bring about such effects. For instance, if John 'grabs' a cup, this action does not cause the cup to 'do' anything: a grab action has well-defined perceptual effects, but these are not registered by the perceptual system that detects independent events involving external objects in the world. In our model, effect-based actions are implemented in several distinct neural circuits, which are organised into a hierarchy based on the complexity of their associated perceptual effects. The circuit at the top of this hierarchy is responsible for actions that bring about independently perceivable events. This circuit receives input from the perceptual module that recognises arbitrary events taking place in the world, and learns movements that reliably cause such events. We assess our model against existing experimental observations about effect-based motor representations, and make some novel experimental predictions. We also consider the possibility that the 'causative actions' circuit in our model can be identified with a motor pathway reported in other work, specialising in 'functional' actions on manipulable tools (Bub et al., 2008; Binkofski and Buxbaum, 2013.

A neural network model of causative actions.

Science.gov (United States)

Lee-Hand, Jeremy; Knott, Alistair

2015-01-01

A common idea in models of action representation is that actions are represented in terms of their perceptual effects (see e.g., Prinz, 1997; Hommel et al., 2001; Sahin et al., 2007; Umiltà et al., 2008; Hommel, 2013). In this paper we extend existing models of effect-based action representations to account for a novel distinction. Some actions bring about effects that are independent events in their own right: for instance, if John smashes a cup, he brings about the event of the cup smashing. Other actions do not bring about such effects. For instance, if John grabs a cup, this action does not cause the cup to "do" anything: a grab action has well-defined perceptual effects, but these are not registered by the perceptual system that detects independent events involving external objects in the world. In our model, effect-based actions are implemented in several distinct neural circuits, which are organized into a hierarchy based on the complexity of their associated perceptual effects. The circuit at the top of this hierarchy is responsible for actions that bring about independently perceivable events. This circuit receives input from the perceptual module that recognizes arbitrary events taking place in the world, and learns movements that reliably cause such events. We assess our model against existing experimental observations about effect-based motor representations, and make some novel experimental predictions. We also consider the possibility that the "causative actions" circuit in our model can be identified with a motor pathway reported in other work, specializing in "functional" actions on manipulable tools (Bub et al., 2008; Binkofski and Buxbaum, 2013).

Hearing sounds, understanding actions: action representation in mirror neurons.

Science.gov (United States)

Kohler, Evelyne; Keysers, Christian; Umiltà, M Alessandra; Fogassi, Leonardo; Gallese, Vittorio; Rizzolatti, Giacomo

2002-08-02

Many object-related actions can be recognized by their sound. We found neurons in monkey premotor cortex that discharge when the animal performs a specific action and when it hears the related sound. Most of the neurons also discharge when the monkey observes the same action. These audiovisual mirror neurons code actions independently of whether these actions are performed, heard, or seen. This discovery in the monkey homolog of Broca's area might shed light on the origin of language: audiovisual mirror neurons code abstract contents-the meaning of actions-and have the auditory access typical of human language to these contents.

Weighted Discriminative Dictionary Learning based on Low-rank Representation

International Nuclear Information System (INIS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

Intrinsic resonance representation of quantum mechanics

DEFF Research Database (Denmark)

Carioli, M.; Heller, E.J.; Møller, Klaus Braagaard

1997-01-01

an optimal representation, based purely on classical mechanics. ''Hidden'' constants of the motion and good actions already known to the classical mechanics are thus incorporated into the basis, leaving the quantum effects to be isolated and included by small matrix diagonalizations. This simplifies...

Comparative investigations of manual action representations: evidence that chimpanzees represent the costs of potential future actions involving tools.

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Frey, Scott H; Povinelli, Daniel J

2012-01-12

The ability to adjust one's ongoing actions in the anticipation of forthcoming task demands is considered as strong evidence for the existence of internal action representations. Studies of action selection in tool use reveal that the behaviours that we choose in the present moment differ depending on what we intend to do next. Further, they point to a specialized role for mechanisms within the human cerebellum and dominant left cerebral hemisphere in representing the likely sensory costs of intended future actions. Recently, the question of whether similar mechanisms exist in other primates has received growing, but still limited, attention. Here, we present data that bear on this issue from a species that is a natural user of tools, our nearest living relative, the chimpanzee. In experiment 1, a subset of chimpanzees showed a non-significant tendency for their grip preferences to be affected by anticipation of the demands associated with bringing a tool's baited end to their mouths. In experiment 2, chimpanzees' initial grip preferences were consistently affected by anticipation of the forthcoming movements in a task that involves using a tool to extract a food reward. The partial discrepancy between the results of these two studies is attributed to the ability to accurately represent differences between the motor costs associated with executing the two response alternatives available within each task. These findings suggest that chimpanzees are capable of accurately representing the costs of intended future actions, and using those predictions to select movements in the present even in the context of externally directed tool use.

Part-based deep representation for product tagging and search

Science.gov (United States)

Chen, Keqing

2017-06-01

Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

Preexisting semantic representation improves working memory performance in the visuospatial domain.

Science.gov (United States)

Rudner, Mary; Orfanidou, Eleni; Cardin, Velia; Capek, Cheryl M; Woll, Bencie; Rönnberg, Jerker

2016-05-01

Working memory (WM) for spoken language improves when the to-be-remembered items correspond to preexisting representations in long-term memory. We investigated whether this effect generalizes to the visuospatial domain by administering a visual n-back WM task to deaf signers and hearing signers, as well as to hearing nonsigners. Four different kinds of stimuli were presented: British Sign Language (BSL; familiar to the signers), Swedish Sign Language (SSL; unfamiliar), nonsigns, and nonlinguistic manual actions. The hearing signers performed better with BSL than with SSL, demonstrating a facilitatory effect of preexisting semantic representation. The deaf signers also performed better with BSL than with SSL, but only when WM load was high. No effect of preexisting phonological representation was detected. The deaf signers performed better than the hearing nonsigners with all sign-based materials, but this effect did not generalize to nonlinguistic manual actions. We argue that deaf signers, who are highly reliant on visual information for communication, develop expertise in processing sign-based items, even when those items do not have preexisting semantic or phonological representations. Preexisting semantic representation, however, enhances the quality of the gesture-based representations temporarily maintained in WM by this group, thereby releasing WM resources to deal with increased load. Hearing signers, on the other hand, may make strategic use of their speech-based representations for mnemonic purposes. The overall pattern of results is in line with flexible-resource models of WM.

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

Science.gov (United States)

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

2017-01-01

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…

Mental representation for action in the elderly: implications for movement efficiency and injury risk.

Science.gov (United States)

Gabbard, Carl

2015-04-01

Recent research findings indicate that with older adulthood, there are functional decrements in spatial cognition and more specially, in the ability to mentally represent and effectively plan motor actions. A typical finding is a significant over- or underestimation of one's actual physical abilities with movement planning-planning that has implications for movement efficiency and physical safety. A practical, daily life example is estimation of reachability--a situation that for the elderly may be linked with fall incidence. A strategy used to mentally represent action is the use of motor imagery--an ability that also declines with advancing older age. This brief review highlights research findings on mental representation and motor imagery in the elderly and addresses the implications for improving movement efficiency and lowering the risk of movement-related injury. © The Author(s) 2013.

Signal- and Symbol-based Representations in Computer Vision

DEFF Research Database (Denmark)

Krüger, Norbert; Felsberg, Michael

We discuss problems of signal-- and symbol based representations in terms of three dilemmas which are faced in the design of each vision system. Signal- and symbol-based representations are opposite ends of a spectrum of conceivable design decisions caught at opposite sides of the dilemmas. We make...... inherent problems explicit and describe potential design decisions for artificial visual systems to deal with the dilemmas....

A Subdivision-Based Representation for Vector Image Editing.

Science.gov (United States)

Liao, Zicheng; Hoppe, Hugues; Forsyth, David; Yu, Yizhou

2012-11-01

Vector graphics has been employed in a wide variety of applications due to its scalability and editability. Editability is a high priority for artists and designers who wish to produce vector-based graphical content with user interaction. In this paper, we introduce a new vector image representation based on piecewise smooth subdivision surfaces, which is a simple, unified and flexible framework that supports a variety of operations, including shape editing, color editing, image stylization, and vector image processing. These operations effectively create novel vector graphics by reusing and altering existing image vectorization results. Because image vectorization yields an abstraction of the original raster image, controlling the level of detail of this abstraction is highly desirable. To this end, we design a feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously. Our new vector image representation can be rasterized efficiently using GPU-accelerated subdivision. Experiments indicate that our vector image representation achieves high visual quality and better supports editing operations than existing representations.

Integrating Globality and Locality for Robust Representation Based Classification

Directory of Open Access Journals (Sweden)

Zheng Zhang

2014-01-01

Full Text Available The representation based classification method (RBCM has shown huge potential for face recognition since it first emerged. Linear regression classification (LRC method and collaborative representation classification (CRC method are two well-known RBCMs. LRC and CRC exploit training samples of each class and all the training samples to represent the testing sample, respectively, and subsequently conduct classification on the basis of the representation residual. LRC method can be viewed as a “locality representation” method because it just uses the training samples of each class to represent the testing sample and it cannot embody the effectiveness of the “globality representation.” On the contrary, it seems that CRC method cannot own the benefit of locality of the general RBCM. Thus we propose to integrate CRC and LRC to perform more robust representation based classification. The experimental results on benchmark face databases substantially demonstrate that the proposed method achieves high classification accuracy.

Live-action Virtual Reality Games

OpenAIRE

Valente, Luis; Clua, Esteban; Silva, Alexandre Ribeiro; Feijó, Bruno

2016-01-01

This paper proposes the concept of "live-action virtual reality games" as a new genre of digital games based on an innovative combination of live-action, mixed-reality, context-awareness, and interaction paradigms that comprise tangible objects, context-aware input devices, and embedded/embodied interactions. Live-action virtual reality games are "live-action games" because a player physically acts out (using his/her real body and senses) his/her "avatar" (his/her virtual representation) in t...

Facilitating Mathematical Practices through Visual Representations

Science.gov (United States)

Murata, Aki; Stewart, Chana

2017-01-01

Effective use of mathematical representation is key to supporting student learning. In "Principles to Actions: Ensuring Mathematical Success for All" (NCTM 2014), "use and connect mathematical representations" is one of the effective Mathematics Teaching Practices. By using different representations, students examine concepts…

Consultation system with knowledge representation by decision rules

Energy Technology Data Exchange (ETDEWEB)

Senne, E L.F.; Simoni, P O

1982-04-01

The use of decision rules in the representation of empirical knowledge supplied by application domain experts is discussed. Based on this representation, a system is described which employs artificial intelligence techniques to yield inferences within a specific domain. Three modules composing the system are described: the acquisition one, that allows the insertion of new rules; the diagnostic one, that uses rules in the inference process; and the explanation one, that exhibits reasons for each system action.

Neural Representation. A Survey-Based Analysis of the Notion

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Oscar Vilarroya

2017-08-01

Full Text Available 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.

Action-based flood forecasting for triggering humanitarian action

Science.gov (United States)

Coughlan de Perez, Erin; van den Hurk, Bart; van Aalst, Maarten K.; Amuron, Irene; Bamanya, Deus; Hauser, Tristan; Jongma, Brenden; Lopez, Ana; Mason, Simon; Mendler de Suarez, Janot; Pappenberger, Florian; Rueth, Alexandra; Stephens, Elisabeth; Suarez, Pablo; Wagemaker, Jurjen; Zsoter, Ervin

2016-09-01

Too often, credible scientific early warning information of increased disaster risk does not result in humanitarian action. With financial resources tilted heavily towards response after a disaster, disaster managers have limited incentive and ability to process complex scientific data, including uncertainties. These incentives are beginning to change, with the advent of several new forecast-based financing systems that provide funding based on a forecast of an extreme event. Given the changing landscape, here we demonstrate a method to select and use appropriate forecasts for specific humanitarian disaster prevention actions, even in a data-scarce location. This action-based forecasting methodology takes into account the parameters of each action, such as action lifetime, when verifying a forecast. Forecasts are linked with action based on an understanding of (1) the magnitude of previous flooding events and (2) the willingness to act "in vain" for specific actions. This is applied in the context of the Uganda Red Cross Society forecast-based financing pilot project, with forecasts from the Global Flood Awareness System (GloFAS). Using this method, we define the "danger level" of flooding, and we select the probabilistic forecast triggers that are appropriate for specific actions. Results from this methodology can be applied globally across hazards and fed into a financing system that ensures that automatic, pre-funded early action will be triggered by forecasts.

Action Priority: Early Neurophysiological Interaction of Conceptual and Motor Representations

Science.gov (United States)

Koester, Dirk; Schack, Thomas

2016-01-01

Handling our everyday life, we often react manually to verbal requests or instruction, but the functional interrelations of motor control and language are not fully understood yet, especially their neurophysiological basis. Here, we investigated whether specific motor representations for grip types interact neurophysiologically with conceptual information, that is, when reading nouns. Participants performed lexical decisions and, for words, executed a grasp-and-lift task on objects of different sizes involving precision or power grips while the electroencephalogram was recorded. Nouns could denote objects that require either a precision or a power grip and could, thus, be (in)congruent with the performed grasp. In a control block, participants pointed at the objects instead of grasping them. The main result revealed an event-related potential (ERP) interaction of grip type and conceptual information which was not present for pointing. Incongruent compared to congruent conditions elicited an increased positivity (100–200 ms after noun onset). Grip type effects were obtained in response-locked analyses of the grasping ERPs (100–300 ms at left anterior electrodes). These findings attest that grip type and conceptual information are functionally related when planning a grasping action but such an interaction could not be detected for pointing. Generally, the results suggest that control of behaviour can be modulated by task demands; conceptual noun information (i.e., associated action knowledge) may gain processing priority if the task requires a complex motor response. PMID:27973539

EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning.

Science.gov (United States)

Zhao, Chao; Jiang, Jingchi; Guan, Yi; Guo, Xitong; He, Bin

2018-05-01

Electronic medical records (EMRs) contain medical knowledge that can be used for clinical decision support (CDS). Our objective is to develop a general system that can extract and represent knowledge contained in EMRs to support three CDS tasks-test recommendation, initial diagnosis, and treatment plan recommendation-given the condition of a patient. We extracted four kinds of medical entities from records and constructed an EMR-based medical knowledge network (EMKN), in which nodes are entities and edges reflect their co-occurrence in a record. Three bipartite subgraphs (bigraphs) were extracted from the EMKN, one to support each task. One part of the bigraph was the given condition (e.g., symptoms), and the other was the condition to be inferred (e.g., diseases). Each bigraph was regarded as a Markov random field (MRF) to support the inference. We proposed three graph-based energy functions and three likelihood-based energy functions. Two of these functions are based on knowledge representation learning and can provide distributed representations of medical entities. Two EMR datasets and three metrics were utilized to evaluate the performance. As a whole, the evaluation results indicate that the proposed system outperformed the baseline methods. The distributed representation of medical entities does reflect similarity relationships with respect to knowledge level. Combining EMKN and MRF is an effective approach for general medical knowledge representation and inference. Different tasks, however, require individually designed energy functions. Copyright © 2018 Elsevier B.V. All rights reserved.

Constructing visual representations

DEFF Research Database (Denmark)

Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

2014-01-01

tangible building blocks. We learned that all participants, most of whom had little experience in visualization authoring, were readily able to create and talk about their own visualizations. Based on our observations, we discuss participants’ actions during the development of their visual representations......The accessibility of infovis authoring tools to a wide audience has been identified as a major research challenge. A key task in the authoring process is the development of visual mappings. While the infovis community has long been deeply interested in finding effective visual mappings......, comparatively little attention has been placed on how people construct visual mappings. In this paper, we present the results of a study designed to shed light on how people transform data into visual representations. We asked people to create, update and explain their own information visualizations using only...

Graphical representation of covariant-contravariant modal formulae

Directory of Open Access Journals (Sweden)

Miguel Palomino

2011-08-01

Full Text Available Covariant-contravariant simulation is a combination of standard (covariant simulation, its contravariant counterpart and bisimulation. We have previously studied its logical characterization by means of the covariant-contravariant modal logic. Moreover, we have investigated the relationships between this model and that of modal transition systems, where two kinds of transitions (the so-called may and must transitions were combined in order to obtain a simple framework to express a notion of refinement over state-transition models. In a classic paper, Boudol and Larsen established a precise connection between the graphical approach, by means of modal transition systems, and the logical approach, based on Hennessy-Milner logic without negation, to system specification. They obtained a (graphical representation theorem proving that a formula can be represented by a term if, and only if, it is consistent and prime. We show in this paper that the formulae from the covariant-contravariant modal logic that admit a "graphical" representation by means of processes, modulo the covariant-contravariant simulation preorder, are also the consistent and prime ones. In order to obtain the desired graphical representation result, we first restrict ourselves to the case of covariant-contravariant systems without bivariant actions. Bivariant actions can be incorporated later by means of an encoding that splits each bivariant action into its covariant and its contravariant parts.

Mathematical Representation Ability by Using Project Based Learning on the Topic of Statistics

Science.gov (United States)

Widakdo, W. A.

2017-09-01

Seeing the importance of the role of mathematics in everyday life, mastery of the subject areas of mathematics is a must. Representation ability is one of the fundamental ability that used in mathematics to make connection between abstract idea with logical thinking to understanding mathematics. Researcher see the lack of mathematical representation and try to find alternative solution to dolve it by using project based learning. This research use literature study from some books and articles in journals to see the importance of mathematical representation abiliy in mathemtics learning and how project based learning able to increase this mathematical representation ability on the topic of Statistics. The indicators for mathematical representation ability in this research classifies namely visual representation (picture, diagram, graph, or table); symbolize representation (mathematical statement. Mathematical notation, numerical/algebra symbol) and verbal representation (written text). This article explain about why project based learning able to influence student’s mathematical representation by using some theories in cognitive psychology, also showing the example of project based learning that able to use in teaching statistics, one of mathematics topic that very useful to analyze data.

SAR Target Recognition Based on Multi-feature Multiple Representation Classifier Fusion

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Zhang Xinzheng

2017-10-01

Full Text Available In this paper, we present a Synthetic Aperture Radar (SAR image target recognition algorithm based on multi-feature multiple representation learning classifier fusion. First, it extracts three features from the SAR images, namely principal component analysis, wavelet transform, and Two-Dimensional Slice Zernike Moments (2DSZM features. Second, we harness the sparse representation classifier and the cooperative representation classifier with the above-mentioned features to get six predictive labels. Finally, we adopt classifier fusion to obtain the final recognition decision. We researched three different classifier fusion algorithms in our experiments, and the results demonstrate thatusing Bayesian decision fusion gives thebest recognition performance. The method based on multi-feature multiple representation learning classifier fusion integrates the discrimination of multi-features and combines the sparse and cooperative representation classification performance to gain complementary advantages and to improve recognition accuracy. The experiments are based on the Moving and Stationary Target Acquisition and Recognition (MSTAR database,and they demonstrate the effectiveness of the proposed approach.

Sparse Representation Based SAR Vehicle Recognition along with Aspect Angle

Directory of Open Access Journals (Sweden)

Xiangwei Xing

2014-01-01

Full Text Available As a method of representing the test sample with few training samples from an overcomplete dictionary, sparse representation classification (SRC has attracted much attention in synthetic aperture radar (SAR automatic target recognition (ATR recently. In this paper, we develop a novel SAR vehicle recognition method based on sparse representation classification along with aspect information (SRCA, in which the correlation between the vehicle’s aspect angle and the sparse representation vector is exploited. The detailed procedure presented in this paper can be summarized as follows. Initially, the sparse representation vector of a test sample is solved by sparse representation algorithm with a principle component analysis (PCA feature-based dictionary. Then, the coefficient vector is projected onto a sparser one within a certain range of the vehicle’s aspect angle. Finally, the vehicle is classified into a certain category that minimizes the reconstruction error with the novel sparse representation vector. Extensive experiments are conducted on the moving and stationary target acquisition and recognition (MSTAR dataset and the results demonstrate that the proposed method performs robustly under the variations of depression angle and target configurations, as well as incomplete observation.

Action-based effects on music perception.

Science.gov (United States)

Maes, Pieter-Jan; Leman, Marc; Palmer, Caroline; Wanderley, Marcelo M

2014-01-03

The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral processes. In contrast, embodied accounts of music cognition emphasize the central role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework that captures the ways in which the human motor system and its actions can reciprocally influence the perception of music. The cornerstone of this framework is the common coding theory, postulating a representational overlap in the brain between the planning, the execution, and the perception of movement. The integration of action and perception in so-called internal models is explained as a result of associative learning processes. Characteristic of internal models is that they allow intended or perceived sensory states to be transferred into corresponding motor commands (inverse modeling), and vice versa, to predict the sensory outcomes of planned actions (forward modeling). Embodied accounts typically refer to inverse modeling to explain action effects on music perception (Leman, 2007). We extend this account by pinpointing forward modeling as an alternative mechanism by which action can modulate perception. We provide an extensive overview of recent empirical evidence in support of this idea. Additionally, we demonstrate that motor dysfunctions can cause perceptual disabilities, supporting the main idea of the paper that the human motor system plays a functional role in auditory perception. The finding that music perception is shaped by the human motor system and its actions suggests that the musical mind is highly embodied. However, we advocate for a more radical approach to embodied (music) cognition in the sense that it needs to be considered as a dynamical process, in which aspects of action, perception, introspection, and social interaction are of crucial importance.

Action-based effects on music perception

Science.gov (United States)

Maes, Pieter-Jan; Leman, Marc; Palmer, Caroline; Wanderley, Marcelo M.

2013-01-01

The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral processes. In contrast, embodied accounts of music cognition emphasize the central role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework that captures the ways in which the human motor system and its actions can reciprocally influence the perception of music. The cornerstone of this framework is the common coding theory, postulating a representational overlap in the brain between the planning, the execution, and the perception of movement. The integration of action and perception in so-called internal models is explained as a result of associative learning processes. Characteristic of internal models is that they allow intended or perceived sensory states to be transferred into corresponding motor commands (inverse modeling), and vice versa, to predict the sensory outcomes of planned actions (forward modeling). Embodied accounts typically refer to inverse modeling to explain action effects on music perception (Leman, 2007). We extend this account by pinpointing forward modeling as an alternative mechanism by which action can modulate perception. We provide an extensive overview of recent empirical evidence in support of this idea. Additionally, we demonstrate that motor dysfunctions can cause perceptual disabilities, supporting the main idea of the paper that the human motor system plays a functional role in auditory perception. The finding that music perception is shaped by the human motor system and its actions suggests that the musical mind is highly embodied. However, we advocate for a more radical approach to embodied (music) cognition in the sense that it needs to be considered as a dynamical process, in which aspects of action, perception, introspection, and social interaction are of crucial importance. PMID:24454299

Action-based effects on music perception

Directory of Open Access Journals (Sweden)

Pieter-Jan eMaes

2014-01-01

Full Text Available The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral phenomena. In contrast, embodied accounts to music cognition emphasize the central role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework capturing the ways that the human motor system, and the actions it produces, can reciprocally influence the perception of music. The cornerstone of this framework is the common coding theory postulating a representational overlap in the brain between the planning, the execution, and the perception of movement. The integration of action and perception in so-called internal models is explained as a result of associative learning processes. Characteristic of internal models is that they allow intended or perceived sensory states to be transferred into corresponding motor commands (inverse modelling, and vice versa, to predict the sensory outcomes of planned actions (forward modelling. Embodied accounts typically adhere to inverse modelling to explain action effects on music perception (Leman, 2007. We extent this account by pinpointing forward modelling as an alternative mechanism by which action can modulate perception. We provide an extensive overview of recent empirical evidence in support of this idea. Additionally, we demonstrate that motor dysfunctions can cause perceptual disabilities, supporting the main idea of the paper that the human motor system plays a functional role in auditory perception. The finding that music perception is shaped by the human motor system, and the action it produces, suggests that the musical mind is highly embodied. However, we advocate for a more radical approach to embodied (music cognition in the sense that it needs to be considered as a dynamic process, in which aspects of action, perception, introspection, and social interaction are of crucial

Convolution-based classification of audio and symbolic representations of music

DEFF Research Database (Denmark)

Velarde, Gissel; Cancino Chacón, Carlos; Meredith, David

2018-01-01

We present a novel convolution-based method for classification of audio and symbolic representations of music, which we apply to classification of music by style. Pieces of music are first sampled to pitch–time representations (piano-rolls or spectrograms) and then convolved with a Gaussian filter......-class composer identification, methods specialised for classifying symbolic representations of music are more effective. We also performed experiments on symbolic representations, synthetic audio and two different recordings of The Well-Tempered Clavier by J. S. Bach to study the method’s capacity to distinguish...

Representation: a call to action for allied health professionals.

Science.gov (United States)

Rourke, K M; Kuck, L; Rosenbloom, J; Wilson, S L

2000-01-01

The Coalition of Allied Health Leadership (CAHL) Representation Project committee examined the representation of allied health professionals in political and other policy-making groups and found it both fragmented and lacking. The benefits to individuals participating in such groups, as well as to the allied health profession as a whole and to the groups themselves, are described. Individuals are urged to participate, and the means to do so are presented.

Learning word vector representations based on acoustic counts

OpenAIRE

Ribeiro, Sam; Watts, Oliver; Yamagishi, Junichi

2017-01-01

This paper presents a simple count-based approach to learning word vector representations by leveraging statistics of cooccurrences between text and speech. This type of representation requires two discrete sequences of units defined across modalities. Two possible methods for the discretization of an acoustic signal are presented, which are then applied to fundamental frequency and energy contours of a transcribed corpus of speech, yielding a sequence of textual objects (e.g. words, syllable...

The representation of knowledge within model-based control systems

International Nuclear Information System (INIS)

Weygand, D.P.; Koul, R.

1987-01-01

The ability to represent knowledge is often considered essential to build systems with reasoning capabilities. In computer science, a good solution often depends on a good representation. The first step in development of most computer applications is selection of a representation for the input, output, and intermediate results that the program will operate upon. For applications in artificial intelligence, this initial choice of representation is especially important. This is because the possible representational paradigms are diverse and the forcing criteria for the choice are usually not clear in the beginning. Yet, the consequences of an inadequate choice can be devastating in the later state of a project if it is discovered that critical information cannot be encoded within the chosen representational paradigm. Problems arise when designing representational systems to support any kind of Knowledge-Base System, that is a computer system that uses knowledge to perform some task. The general case of knowledge-based systems can be thought of as reasoning agents applying knowledge to achieve goals. Artificial Intelligence (AI) research involves building computer systems to perform tasks of perception and reasoning, as well as storage and retrieval of data. The problem of automatically perceiving large patterns in data is a perceptual task that begins to be important for many expert systems applications. Most of AI research assumes that what needs to be represented is known a priori; an AI researcher's job is just figuring out how to encode the information in the system's data structure and procedures. 10 refs

Mining Key Skeleton Poses with Latent SVM for Action Recognition

Directory of Open Access Journals (Sweden)

Xiaoqiang Li

2017-01-01

Full Text Available Human action recognition based on 3D skeleton has become an active research field in recent years with the recently developed commodity depth sensors. Most published methods analyze an entire 3D depth data, construct mid-level part representations, or use trajectory descriptor of spatial-temporal interest point for recognizing human activities. Unlike previous work, a novel and simple action representation is proposed in this paper which models the action as a sequence of inconsecutive and discriminative skeleton poses, named as key skeleton poses. The pairwise relative positions of skeleton joints are used as feature of the skeleton poses which are mined with the aid of the latent support vector machine (latent SVM. The advantage of our method is resisting against intraclass variation such as noise and large nonlinear temporal deformation of human action. We evaluate the proposed approach on three benchmark action datasets captured by Kinect devices: MSR Action 3D dataset, UTKinect Action dataset, and Florence 3D Action dataset. The detailed experimental results demonstrate that the proposed approach achieves superior performance to the state-of-the-art skeleton-based action recognition methods.

Memetics of representation

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Roberto De Rubertis

2012-06-01

Full Text Available This article will discuss about the physiological genesis of representation and then it will illustrate the developments, especially in evolutionary perspective, and it will show how these are mainly a result of accidental circumstances, rather than of deliberate intention of improvement. In particular, it will be argue that the representation has behaved like a meme that has arrived to its own progressive evolution coming into symbiosis with the different cultures in which it has spread, and using in this activity human work “unconsciously”. Finally it will be shown how in this action the geometry is an element key, linked to representation both to construct images using graphics operations and to erect buildings using concrete operations.

A novel video recommendation system based on efficient retrieval of human actions

Science.gov (United States)

Ramezani, Mohsen; Yaghmaee, Farzin

2016-09-01

In recent years, fast growth of online video sharing eventuated new issues such as helping users to find their requirements in an efficient way. Hence, Recommender Systems (RSs) are used to find the users' most favorite items. Finding these items relies on items or users similarities. Though, many factors like sparsity and cold start user impress the recommendation quality. In some systems, attached tags are used for searching items (e.g. videos) as personalized recommendation. Different views, incomplete and inaccurate tags etc. can weaken the performance of these systems. Considering the advancement of computer vision techniques can help improving RSs. To this end, content based search can be used for finding items (here, videos are considered). In such systems, a video is taken from the user to find and recommend a list of most similar videos to the query one. Due to relating most videos to humans, we present a novel low complex scalable method to recommend videos based on the model of included action. This method has recourse to human action retrieval approaches. For modeling human actions, some interest points are extracted from each action and their motion information are used to compute the action representation. Moreover, a fuzzy dissimilarity measure is presented to compare videos for ranking them. The experimental results on HMDB, UCFYT, UCF sport and KTH datasets illustrated that, in most cases, the proposed method can reach better results than most used methods.

Representations of space based on haptic input

NARCIS (Netherlands)

Zuidhoek, S.

2005-01-01

The present thesis focused on the representations of grasping space based on haptic input. We aimed at identifying their characteristics, and the underlying neurocognitive processes and mechanisms. To this end, we studied the systematic distortions in performance on several orientation perception

Categorification and higher representation theory

CERN Document Server

Beliakova, Anna

2017-01-01

The emergent mathematical philosophy of categorification is reshaping our view of modern mathematics by uncovering a hidden layer of structure in mathematics, revealing richer and more robust structures capable of describing more complex phenomena. Categorified representation theory, or higher representation theory, aims to understand a new level of structure present in representation theory. Rather than studying actions of algebras on vector spaces where algebra elements act by linear endomorphisms of the vector space, higher representation theory describes the structure present when algebras act on categories, with algebra elements acting by functors. The new level of structure in higher representation theory arises by studying the natural transformations between functors. This enhanced perspective brings into play a powerful new set of tools that deepens our understanding of traditional representation theory. This volume exhibits some of the current trends in higher representation theory and the diverse te...

PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

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Xingxing Zhu

2018-05-01

Full Text Available Nonrigid multimodal image registration remains a challenging task in medical image processing and analysis. The structural representation (SR-based registration methods have attracted much attention recently. However, the existing SR methods cannot provide satisfactory registration accuracy due to the utilization of hand-designed features for structural representation. To address this problem, the structural representation method based on the improved version of the simple deep learning network named PCANet is proposed for medical image registration. In the proposed method, PCANet is firstly trained on numerous medical images to learn convolution kernels for this network. Then, a pair of input medical images to be registered is processed by the learned PCANet. The features extracted by various layers in the PCANet are fused to produce multilevel features. The structural representation images are constructed for two input images based on nonlinear transformation of these multilevel features. The Euclidean distance between structural representation images is calculated and used as the similarity metrics. The objective function defined by the similarity metrics is optimized by L-BFGS method to obtain parameters of the free-form deformation (FFD model. Extensive experiments on simulated and real multimodal image datasets show that compared with the state-of-the-art registration methods, such as modality-independent neighborhood descriptor (MIND, normalized mutual information (NMI, Weber local descriptor (WLD, and the sum of squared differences on entropy images (ESSD, the proposed method provides better registration performance in terms of target registration error (TRE and subjective human vision.

Effects of Computer-Based Visual Representation on Mathematics Learning and Cognitive Load

Science.gov (United States)

Yung, Hsin I.; Paas, Fred

2015-01-01

Visual representation has been recognized as a powerful learning tool in many learning domains. Based on the assumption that visual representations can support deeper understanding, we examined the effects of visual representations on learning performance and cognitive load in the domain of mathematics. An experimental condition with visual…

Prototype Theory Based Feature Representation for PolSAR Images

OpenAIRE

Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

2016-01-01

This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory. Then, regularized logistic regression is used to predict similarities between a test sample and each prototype set. Finally, the PolSAR image feature representation is obtained by ensemble projection. Experimental results of an unsupervised classification of PolSAR images show that our...

3D ear identification based on sparse representation.

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Lin Zhang

Full Text Available Biometrics based personal authentication is an effective way for automatically recognizing, with a high confidence, a person's identity. Recently, 3D ear shape has attracted tremendous interests in research field due to its richness of feature and ease of acquisition. However, the existing ICP (Iterative Closet Point-based 3D ear matching methods prevalent in the literature are not quite efficient to cope with the one-to-many identification case. In this paper, we aim to fill this gap by proposing a novel effective fully automatic 3D ear identification system. We at first propose an accurate and efficient template-based ear detection method. By utilizing such a method, the extracted ear regions are represented in a common canonical coordinate system determined by the ear contour template, which facilitates much the following stages of feature extraction and classification. For each extracted 3D ear, a feature vector is generated as its representation by making use of a PCA-based local feature descriptor. At the stage of classification, we resort to the sparse representation based classification approach, which actually solves an l1-minimization problem. To the best of our knowledge, this is the first work introducing the sparse representation framework into the field of 3D ear identification. Extensive experiments conducted on a benchmark dataset corroborate the effectiveness and efficiency of the proposed approach. The associated Matlab source code and the evaluation results have been made publicly online available at http://sse.tongji.edu.cn/linzhang/ear/srcear/srcear.htm.

Social Representations of the Development of Intelligence, Parental Values and Parenting Styles: A Theoretical Model for Analysis

Science.gov (United States)

Miguel, Isabel; Valentim, Joaquim Pires; Carugati, Felice

2013-01-01

Within the theoretical framework of social representations theory, a substantial body of literature has advocated and shown that, as interpretative systems and forms of knowledge concurring in the construction of a social reality, social representations are guides for action, influencing behaviours and social relations. Based on this assumption,…

Multi-Layer Sparse Representation for Weighted LBP-Patches Based Facial Expression Recognition

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Qi Jia

2015-03-01

Full Text Available In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach.

Object-based attention: strength of object representation and attentional guidance.

Science.gov (United States)

Shomstein, Sarah; Behrmann, Marlene

2008-01-01

Two or more features belonging to a single object are identified more quickly and more accurately than are features belonging to different objects--a finding attributed to sensory enhancement of all features belonging to an attended or selected object. However, several recent studies have suggested that this "single-object advantage" may be a product of probabilistic and configural strategic prioritizations rather than of object-based perceptual enhancement per se, challenging the underlying mechanism that is thought to give rise to object-based attention. In the present article, we further explore constraints on the mechanisms of object-based selection by examining the contribution of the strength of object representations to the single-object advantage. We manipulated factors such as exposure duration (i.e., preview time) and salience of configuration (i.e., objects). Varying preview time changes the magnitude of the object-based effect, so that if there is ample time to establish an object representation (i.e., preview time of 1,000 msec), then both probability and configuration (i.e., objects) guide attentional selection. If, however, insufficient time is provided to establish a robust object-based representation, then only probabilities guide attentional selection. Interestingly, at a short preview time of 200 msec, when the two objects were sufficiently different from each other (i.e., different colors), both configuration and probability guided attention selection. These results suggest that object-based effects can be explained both in terms of strength of object representations (established at longer exposure durations and by pictorial cues) and probabilistic contingencies in the visual environment.

Group representations, error bases and quantum codes

Energy Technology Data Exchange (ETDEWEB)

Knill, E

1996-01-01

This report continues the discussion of unitary error bases and quantum codes. Nice error bases are characterized in terms of the existence of certain characters in a group. A general construction for error bases which are non-abelian over the center is given. The method for obtaining codes due to Calderbank et al. is generalized and expressed purely in representation theoretic terms. The significance of the inertia subgroup both for constructing codes and obtaining the set of transversally implementable operations is demonstrated.

Conformal-Based Surface Morphing and Multi-Scale Representation

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Ka Chun Lam

2014-05-01

Full Text Available This paper presents two algorithms, based on conformal geometry, for the multi-scale representations of geometric shapes and surface morphing. A multi-scale surface representation aims to describe a 3D shape at different levels of geometric detail, which allows analyzing or editing surfaces at the global or local scales effectively. Surface morphing refers to the process of interpolating between two geometric shapes, which has been widely applied to estimate or analyze deformations in computer graphics, computer vision and medical imaging. In this work, we propose two geometric models for surface morphing and multi-scale representation for 3D surfaces. The basic idea is to represent a 3D surface by its mean curvature function, H, and conformal factor function λ, which uniquely determine the geometry of the surface according to Riemann surface theory. Once we have the (λ, H parameterization of the surface, post-processing of the surface can be done directly on the conformal parameter domain. In particular, the problem of multi-scale representations of shapes can be reduced to the signal filtering on the λ and H parameters. On the other hand, the surface morphing problem can be transformed to an interpolation process of two sets of (λ, H parameters. We test the proposed algorithms on 3D human face data and MRI-derived brain surfaces. Experimental results show that our proposed methods can effectively obtain multi-scale surface representations and give natural surface morphing results.

Motor consciousness during intention-based and stimulus-based actions: modulating attention resources through Mindfulness meditation

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Yvonne Nathalie Delevoye-Turrell

2012-09-01

Full Text Available Mindfulness-Based Stress Reduction meditation (MBSR may offer optimal performance through heightened attention for increased body consciousness. To test this hypothesis, MBSR effects were assessed on the simple task of lifting an object. A dual task paradigm was included to assess the opposite effect of a limited amount of attention on motor consciousness. In a stimulus-based condition, the subjects’ task was to lift an object that was hefted with weights. In an intentional-based condition, subjects were required to lift a light object while imagining that the object was virtually heavier and thus, adjust their grip voluntarily. The degree of motor consciousness was evaluated by calculating correlation factors for each participant between the grip force level used during the lift trial (lift the object and that used during its associated reproduce trial (without lifting, indicate the force you think you used in the previous trial. Under dual task condition, motor consciousness decreased for intention- and stimulus-based actions, revealing the importance of top-down attention for building the motor representation that guides action planning. For MBSR-experts, heightened attention provided stronger levels of motor consciousness; this was true for both intention and stimulus-based actions. For controls, heightened attention decreased the capacity to reproduce force levels, suggesting that voluntary top-down attention interfered with the automatic bottom-up emergence of body sensations.Our results provide strong arguments for involvement of two types of attention for the emergence of motor consciousness. Bottom-up attention would serve as an amplifier of motor-sensory afferences; Top down attention would help transfer the motor-sensory content from a pre-conscious to a conscious state of processing. MBSR would be a specific state for which both types of attention are optimally combined to provide experts with total experiences of their body in

The processing of actions and action-words in amyotrophic lateral sclerosis patients.

Science.gov (United States)

Papeo, Liuba; Cecchetto, Cinzia; Mazzon, Giulia; Granello, Giulia; Cattaruzza, Tatiana; Verriello, Lorenzo; Eleopra, Roberto; Rumiati, Raffaella I

2015-03-01

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with prime consequences on the motor function and concomitant cognitive changes, most frequently in the domain of executive functions. Moreover, poorer performance with action-verbs versus object-nouns has been reported in ALS patients, raising the hypothesis that the motor dysfunction deteriorates the semantic representation of actions. Using action-verbs and manipulable-object nouns sharing semantic relationship with the same motor representations, the verb-noun difference was assessed in a group of 21 ALS-patients with severely impaired motor behavior, and compared with a normal sample's performance. ALS-group performed better on nouns than verbs, both in production (action and object naming) and comprehension (word-picture matching). This observation implies that the interpretation of the verb-noun difference in ALS cannot be accounted by the relatedness of verbs to motor representations, but has to consider the role of other semantic and/or morpho-phonological dimensions that distinctively define the two grammatical classes. Moreover, this difference in the ALS-group was not greater than the noun-verb difference in the normal sample. The mental representation of actions also involves an executive-control component to organize, in logical/temporal order, the individual motor events (or sub-goals) that form a purposeful action. We assessed this ability with action sequencing tasks, requiring participants to re-construct a purposeful action from the scrambled presentation of its constitutive motor events, shown in the form of photographs or short sentences. In those tasks, ALS-group's performance was significantly poorer than controls'. Thus, the executive dysfunction manifested in the sequencing deficit -but not the selective verb deficit- appears as a consistent feature of the cognitive profile associated with ALS. We suggest that ALS can offer a valuable model to study the relationship between

Order-based representation in random networks of cortical neurons.

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Goded Shahaf

2008-11-01

Full Text Available The wide range of time scales involved in neural excitability and synaptic transmission might lead to ongoing change in the temporal structure of responses to recurring stimulus presentations on a trial-to-trial basis. This is probably the most severe biophysical constraint on putative time-based primitives of stimulus representation in neuronal networks. Here we show that in spontaneously developing large-scale random networks of cortical neurons in vitro the order in which neurons are recruited following each stimulus is a naturally emerging representation primitive that is invariant to significant temporal changes in spike times. With a relatively small number of randomly sampled neurons, the information about stimulus position is fully retrievable from the recruitment order. The effective connectivity that makes order-based representation invariant to time warping is characterized by the existence of stations through which activity is required to pass in order to propagate further into the network. This study uncovers a simple invariant in a noisy biological network in vitro; its applicability under in vivo constraints remains to be seen.

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

Science.gov (United States)

Galvan, Jose Ramon; Saxena, Abhinav; Goebel, Kai Frank

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

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

Science.gov (United States)

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

Learning connective-based word representations for implicit discourse relation identification

DEFF Research Database (Denmark)

Braud, Chloé Elodie; Denis, Pascal

2016-01-01

We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represen...... their simplicity, these connective-based rep-resentations outperform various off-the-shelf word embeddings, and achieve state-of-the-art performance on this problem.......We introduce a simple semi-supervised ap-proach to improve implicit discourse relation identification. This approach harnesses large amounts of automatically extracted discourse connectives along with their arguments to con-struct new distributional word representations. Specifically, we represent...... words in the space of discourse connectives as a way to directly encode their rhetorical function. Experiments on the Penn Discourse Treebank demonstrate the effectiveness of these task-tailored repre-sentations in predicting implicit discourse re-lations. Our results indeed show that, despite...

Towards Web-based representation and processing of health information

DEFF Research Database (Denmark)

Gao, S.; Mioc, Darka; Yi, X.L.

2009-01-01

facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC) services. It brought a new solution in better health data representation and initial exploration of the Web-based processing of health information. Conclusion: The designed......Background: There is great concern within health surveillance, on how to grapple with environmental degradation, rapid urbanization, population mobility and growth. The Internet has emerged as an efficient way to share health information, enabling users to access and understand data....... For the representation of health information through Web-mapping applications, there still lacks a standard format to accommodate all fixed (such as location) and variable (such as age, gender, health outcome, etc) indicators in the representation of health information. Furthermore, net-centric computing has not been...

Good Practices for Learning to Recognize Actions Using FV and VLAD.

Science.gov (United States)

Wu, Jianxin; Zhang, Yu; Lin, Weiyao

2016-12-01

High dimensional representations such as Fisher vectors (FV) and vectors of locally aggregated descriptors (VLAD) have shown state-of-the-art accuracy for action recognition in videos. The high dimensionality, on the other hand, also causes computational difficulties when scaling up to large-scale video data. This paper makes three lines of contributions to learning to recognize actions using high dimensional representations. First, we reviewed several existing techniques that improve upon FV or VLAD in image classification, and performed extensive empirical evaluations to assess their applicability for action recognition. Our analyses of these empirical results show that normality and bimodality are essential to achieve high accuracy. Second, we proposed a new pooling strategy for VLAD and three simple, efficient, and effective transformations for both FV and VLAD. Both proposed methods have shown higher accuracy than the original FV/VLAD method in extensive evaluations. Third, we proposed and evaluated new feature selection and compression methods for the FV and VLAD representations. This strategy uses only 4% of the storage of the original representation, but achieves comparable or even higher accuracy. Based on these contributions, we recommend a set of good practices for action recognition in videos for practitioners in this field.

Reference Frame Fields based on Quantum Theory Representations of Real and Complex Numbers

OpenAIRE

Benioff, Paul

2007-01-01

A quantum theory representations of real (R) and complex (C) numbers is given that is based on states of single, finite strings of qukits for any base k > 1. Both unary representations and the possibility that qukits with k a prime number are elementary and the rest composite are discussed. Cauchy sequences of qukit string states are defined from the arithmetic properties. The representations of R and C, as equivalence classes of these sequences, differ from classical kit string state represe...

A Possible Neural Representation of Mathematical Group Structures.

Science.gov (United States)

Pomi, Andrés

2016-09-01

Every cognitive activity has a neural representation in the brain. When humans deal with abstract mathematical structures, for instance finite groups, certain patterns of activity are occurring in the brain that constitute their neural representation. A formal neurocognitive theory must account for all the activities developed by our brain and provide a possible neural representation for them. Associative memories are neural network models that have a good chance of achieving a universal representation of cognitive phenomena. In this work, we present a possible neural representation of mathematical group structures based on associative memory models that store finite groups through their Cayley graphs. A context-dependent associative memory stores the transitions between elements of the group when multiplied by each generator of a given presentation of the group. Under a convenient election of the vector basis mapping the elements of the group in the neural activity, the input of a vector corresponding to a generator of the group collapses the context-dependent rectangular matrix into a virtual square permutation matrix that is the matrix representation of the generator. This neural representation corresponds to the regular representation of the group, in which to each element is assigned a permutation matrix. This action of the generator on the memory matrix can also be seen as the dissection of the corresponding monochromatic subgraph of the Cayley graph of the group, and the adjacency matrix of this subgraph is the permutation matrix corresponding to the generator.

A minimal architecture for joint action

DEFF Research Database (Denmark)

Vesper, Cordula; Butterfill, Stephen; Knoblich, Günther

2010-01-01

What kinds of processes and representations make joint action possible? In this paper we suggest a minimal architecture for joint action that focuses on representations, action monitoring and action prediction processes, as well as ways of simplifying coordination. The architecture spells out...... minimal requirements for an individual agent to engage in a joint action. We discuss existing evidence in support of the architecture as well as open questions that remain to be empirically addressed. In addition, we suggest possible interfaces between the minimal architecture and other approaches...... to joint action. The minimal architecture has implications for theorizing about the emergence of joint action, for human-machine interaction, and for understanding how coordination can be facilitated by exploiting relations between multiple agents’ actions and between actions and the environment....

Designing electronic module based on learning content development system in fostering students’ multi representation skills

Science.gov (United States)

Resita, I.; Ertikanto, C.

2018-05-01

This study aims to develop electronic module design based on Learning Content Development System (LCDS) to foster students’ multi representation skills in physics subject material. This study uses research and development method to the product design. This study involves 90 students and 6 physics teachers who were randomly chosen from 3 different Senior High Schools in Lampung Province. The data were collected by using questionnaires and analyzed by using quantitative descriptive method. Based on the data, 95% of the students only use one form of representation in solving physics problems. Representation which is tend to be used by students is symbolic representation. Students are considered to understand the concept of physics if they are able to change from one form to the other forms of representation. Product design of LCDS-based electronic module presents text, image, symbolic, video, and animation representation.

Improving the learning of clinical reasoning through computer-based cognitive representation.

Science.gov (United States)

Wu, Bian; Wang, Minhong; Johnson, Janice M; Grotzer, Tina A

2014-01-01

Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. A significant improvement was found in students' learning products from the beginning to the end of the study, consistent with students' report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge construction.

Social representations and normative beliefs of aging.

Science.gov (United States)

Torres, Tatiana de Lucena; Camargo, Brigido Vizeu; Boulsfield, Andréa Barbará; Silva, Antônia Oliveira

2015-12-01

This study adopted the theory of social representations as a theoretical framework in order to characterize similarities and differences in social representations and normative beliefs of aging for different age groups. The 638 participants responded to self-administered questionnaire and were equally distributed by sex and age. The results show that aging is characterized by positive stereotypes (knowledge and experience); however, retirement is linked to aging, but in a negative way, particularly for men, involving illness, loneliness and disability. When age was considered, it was verified that the connections with the representational elements became more complex for older groups, showing social representation functionality, largely for the elderly. Adulthood seems to be preferred and old age is disliked. There were divergences related to the perception of the beginning of life phases, especially that of old age. Work was characterized as the opposite of aging, and it revealed the need for actions intended for the elderly and retired workers, with post-retirement projects. In addition, it suggests investment in public policies that encourage intergenerational contact, with efforts to reduce intolerance and discrimination based on age of people.

Actionability and Simulation: No Representation without Communication

Directory of Open Access Journals (Sweden)

Jerome Arthur Feldman

2016-09-01

Full Text Available .There remains considerable controversy about how the brain operates. This review focuses on brain activity rather than just structure and on concepts of action and actionability rather than truth conditions. Neural Communication is reviewed as a crucial aspect of neural encoding. Consequently, logical inference is superseded by neural simulation. Some remaining mysteries are discussed.

Optimal Couple Projections for Domain Adaptive Sparse Representation-based Classification.

Science.gov (United States)

Zhang, Guoqing; Sun, Huaijiang; Porikli, Fatih; Liu, Yazhou; Sun, Quansen

2017-08-29

In recent years, sparse representation based classification (SRC) is one of the most successful methods and has been shown impressive performance in various classification tasks. However, when the training data has a different distribution than the testing data, the learned sparse representation may not be optimal, and the performance of SRC will be degraded significantly. To address this problem, in this paper, we propose an optimal couple projections for domain-adaptive sparse representation-based classification (OCPD-SRC) method, in which the discriminative features of data in the two domains are simultaneously learned with the dictionary that can succinctly represent the training and testing data in the projected space. OCPD-SRC is designed based on the decision rule of SRC, with the objective to learn coupled projection matrices and a common discriminative dictionary such that the between-class sparse reconstruction residuals of data from both domains are maximized, and the within-class sparse reconstruction residuals of data are minimized in the projected low-dimensional space. Thus, the resulting representations can well fit SRC and simultaneously have a better discriminant ability. In addition, our method can be easily extended to multiple domains and can be kernelized to deal with the nonlinear structure of data. The optimal solution for the proposed method can be efficiently obtained following the alternative optimization method. Extensive experimental results on a series of benchmark databases show that our method is better or comparable to many state-of-the-art methods.

Developing young adults' representational competence through infographic-based science news reporting

Science.gov (United States)

Gebre, Engida H.; Polman, Joseph L.

2016-12-01

This study presents descriptive analysis of young adults' use of multiple representations in the context of science news reporting. Across one semester, 71 high school students, in a socioeconomically diverse suburban secondary school in Midwestern United States, participated in activities of researching science topics of their choice and producing infographic-based science news for possible online publication. An external editor reviewed their draft infographics and provided comments for subsequent revision. Students also provided peer feedback to the draft version of infographics using an online commentary tool. We analysed the nature of representations students used as well as the comments from peer and the editor feedback. Results showed both students' capabilities and challenges in learning with representations in this context. Students frequently rely on using certain kinds of representations that are depictive in nature, and supporting their progress towards using more abstract representations requires special attention and identifying learning gaps. Results also showed that students were able to determine representational adequacy in the context of providing peer feedback. The study has implication for research and instruction using infographics as expressive tools to support learning.

Fast and accurate grid representations for atom-based docking with partner flexibility.

Science.gov (United States)

de Vries, Sjoerd J; Zacharias, Martin

2017-06-30

Macromolecular docking methods can broadly be divided into geometric and atom-based methods. Geometric methods use fast algorithms that operate on simplified, grid-like molecular representations, while atom-based methods are more realistic and flexible, but far less efficient. Here, a hybrid approach of grid-based and atom-based docking is presented, combining precalculated grid potentials with neighbor lists for fast and accurate calculation of atom-based intermolecular energies and forces. The grid representation is compatible with simultaneous multibody docking and can tolerate considerable protein flexibility. When implemented in our docking method ATTRACT, grid-based docking was found to be ∼35x faster. With the OPLSX forcefield instead of the ATTRACT coarse-grained forcefield, the average speed improvement was >100x. Grid-based representations may allow atom-based docking methods to explore large conformational spaces with many degrees of freedom, such as multiple macromolecules including flexibility. This increases the domain of biological problems to which docking methods can be applied. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Modelling Dowel Action of Discrete Reinforcing Bars in Cracked Concrete Structures

International Nuclear Information System (INIS)

Kwan, A. K. H.; Ng, P. L.; Lam, J. Y. K.

2010-01-01

Dowel action is one of the component actions for shear force transfer in cracked reinforced concrete. In finite element analysis of concrete structures, the use of discrete representation of reinforcing bars is considered advantageous over the smeared representation due to the relative ease of modelling the bond-slip behaviour. However, there is very limited research on how to simulate the dowel action of discrete reinforcing bars. Herein, a numerical model for dowel action of discrete reinforcing bars crossing cracks in concrete is developed. The model features the derivation of dowel stiffness matrix based on beam-on-elastic-foundation theory and the direct assemblage of dowel stiffness into the concrete element stiffness matrices. The dowel action model is incorporated in a nonlinear finite element programme with secant stiffness formulation. Deep beams tested in the literature are analysed and it is found that the incorporation of dowel action model improves the accuracy of analysis.

Teaching object concepts for XML-based representations.

Energy Technology Data Exchange (ETDEWEB)

Kelsey, R. L. (Robert L.)

2002-01-01

Students learned about object-oriented design concepts and knowledge representation through the use of a set of toy blocks. The blocks represented a limited and focused domain of knowledge and one that was physical and tangible. The blocks helped the students to better visualize, communicate, and understand the domain of knowledge as well as how to perform object decomposition. The blocks were further abstracted to an engineering design kit for water park design. This helped the students to work on techniques for abstraction and conceptualization. It also led the project from tangible exercises into software and programming exercises. Students employed XML to create object-based knowledge representations and Java to use the represented knowledge. The students developed and implemented software allowing a lay user to design and create their own water slide and then to take a simulated ride on their slide.

An Improved Information Hiding Method Based on Sparse Representation

Directory of Open Access Journals (Sweden)

Minghai Yao

2015-01-01

Full Text Available A novel biometric authentication information hiding method based on the sparse representation is proposed for enhancing the security of biometric information transmitted in the network. In order to make good use of abundant information of the cover image, the sparse representation method is adopted to exploit the correlation between the cover and biometric images. Thus, the biometric image is divided into two parts. The first part is the reconstructed image, and the other part is the residual image. The biometric authentication image cannot be restored by any one part. The residual image and sparse representation coefficients are embedded into the cover image. Then, for the sake of causing much less attention of attackers, the visual attention mechanism is employed to select embedding location and embedding sequence of secret information. Finally, the reversible watermarking algorithm based on histogram is utilized for embedding the secret information. For verifying the validity of the algorithm, the PolyU multispectral palmprint and the CASIA iris databases are used as biometric information. The experimental results show that the proposed method exhibits good security, invisibility, and high capacity.

Representational contents of domestic violence against women among nursing students

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Camila Daiane Silva

2016-12-01

Full Text Available This study aimed to analyze the representational contents of domestic violence against women among nursing students. This is a qualitative research, based on the Theory of Social Representations. We collected the data from August to November/2014 by semi-structured interviews, analyzed by software. Thirty-three students participated, 16 from the initial grades and 17 from the final grades. We identified two categories: representational content acquired in the pre-university and university years. The initial grades listed high school, cases with family members and colleagues. Among the final grades, knowledge was acquired during academic weeks, research groups, practical activities, and internships. The knowledge of common sense is constant, especially between the students of initial grades and the reified, between the final series. The actions of the future professional life can base on personal experiences, reified common sense knowledge, and practical knowledge generated during graduation. It highlights the impact on training to provide assistance to women/persons in situations of violence.

Mirror neurons and the action theory of language origins

OpenAIRE

Steels, Luc

2000-01-01

The research reported here attempts to understand how language may have originated from sensori-motor competences. Recently the observation of mirror neurons has lead to the suggestion that there is not only a rich representation of motor action but also that this representation is used for multiple purposes: action execution, action planning, action imaging, and action recognition. Of particular importance is the observation that one agent can recognise an action plan of another one and t...

Hand Specific Representations in Language Comprehension

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Claire eMoody-Triantis

2014-06-01

Full Text Available Theories of embodied cognition argue that language comprehension involves sensory-motor re-enactments of the actions described. However, the degree of specificity of these re-enactments as well as the relationship between action and language remains a matter of debate. Here we investigate these issues by examining how hand-specific information (left or right hand is recruited in language comprehension and action execution. An fMRI study tested right-handed participants in two separate tasks that were designed to be as similar as possible to increase sensitivity of the comparison across task: an action execution go/no-go task where participants performed right or left hand actions, and a language task where participants read sentences describing the same left or right handed actions as in the execution task. We found that language-induced activity did not match the hand-specific patterns of activity found for action execution in primary somatosensory and motor cortex, but it overlapped with pre-motor and parietal regions associated with action planning. Within these pre-motor regions, both right hand actions and sentences elicited stronger activity than left hand actions and sentences - a dominant hand effect -. Importantly, both dorsal and ventral sections of the left pre-central gyrus were recruited by both tasks, suggesting different action features being recruited. These results suggest that (a language comprehension elicits motor representations that are hand-specific and akin to multimodal action plans, rather than full action re-enactments; and (b language comprehension and action execution share schematic hand-specific representations that are richer for the dominant hand, and thus linked to previous motor experience.

Hand specific representations in language comprehension.

Science.gov (United States)

Moody-Triantis, Claire; Humphreys, Gina F; Gennari, Silvia P

2014-01-01

Theories of embodied cognition argue that language comprehension involves sensory-motor re-enactments of the actions described. However, the degree of specificity of these re-enactments as well as the relationship between action and language remains a matter of debate. Here we investigate these issues by examining how hand-specific information (left or right hand) is recruited in language comprehension and action execution. An fMRI study tested self-reported right-handed participants in two separate tasks that were designed to be as similar as possible to increase sensitivity of the comparison across task: an action execution go/no-go task where participants performed right or left hand actions, and a language task where participants read sentences describing the same left or right handed actions as in the execution task. We found that language-induced activity did not match the hand-specific patterns of activity found for action execution in primary somatosensory and motor cortex, but it overlapped with pre-motor and parietal regions associated with action planning. Within these pre-motor regions, both right hand actions and sentences elicited stronger activity than left hand actions and sentences-a dominant hand effect. Importantly, both dorsal and ventral sections of the left pre-central gyrus were recruited by both tasks, suggesting different action features being recruited. These results suggest that (a) language comprehension elicits motor representations that are hand-specific and akin to multimodal action plans, rather than full action re-enactments; and (b) language comprehension and action execution share schematic hand-specific representations that are richer for the dominant hand, and thus linked to previous motor experience.

Representing others' actions: the role of expertise in the aging mind

NARCIS (Netherlands)

Diersch, N.; Cross, E.S.; Stadler, W.; Schulz-Bosbach, S.; Rieger, M.

2012-01-01

A large body of evidence suggests that action execution and action observation share a common representational domain. To date, little is known about age-related changes in these action representations that are assumed to support various abilities such as the prediction of observed actions. The

An intact action-perception coupling depends on the integrity of the cerebellum.

Science.gov (United States)

Christensen, Andrea; Giese, Martin A; Sultan, Fahad; Mueller, Oliver M; Goericke, Sophia L; Ilg, Winfried; Timmann, Dagmar

2014-05-07

It is widely accepted that action and perception in humans functionally interact on multiple levels. Moreover, areas originally suggested to be predominantly motor-related, as the cerebellum, are also involved in action observation. However, as yet, few studies provided unequivocal evidence that the cerebellum is involved in the action perception coupling (APC), specifically in the integration of motor and multisensory information for perception. We addressed this question studying patients with focal cerebellar lesions in a virtual-reality paradigm measuring the effect of action execution on action perception presenting self-generated movements as point lights. We measured the visual sensitivity to the point light stimuli based on signal detection theory. Compared with healthy controls cerebellar patients showed no beneficial influence of action execution on perception indicating deficits in APC. Applying lesion symptom mapping, we identified distinct areas in the dentate nucleus and the lateral cerebellum of both hemispheres that are causally involved in APC. Lesions of the right ventral dentate, the ipsilateral motor representations (lobules V/VI), and most interestingly the contralateral posterior cerebellum (lobule VII) impede the benefits of motor execution on perception. We conclude that the cerebellum establishes time-dependent multisensory representations on different levels, relevant for motor control as well as supporting action perception. Ipsilateral cerebellar motor representations are thought to support the somatosensory state estimate of ongoing movements, whereas the ventral dentate and the contralateral posterior cerebellum likely support sensorimotor integration in the cerebellar-parietal loops. Both the correct somatosensory as well as the multisensory state representations are vital for an intact APC.

Time-Frequency Distribution of Music based on Sparse Wavelet Packet Representations

DEFF Research Database (Denmark)

Endelt, Line Ørtoft

We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found using...... the minimization methods basis pursuit and best orthogonal basis. Visualizations of the time-frequency distribution are constructed based on a simplified energy distribution in the wavelet packet decomposition. The time-frequency distributions emphasizes structured musical content, including non-stationary content...

Improving the learning of clinical reasoning through computer-based cognitive representation

Directory of Open Access Journals (Sweden)

Bian Wu

2014-12-01

Full Text Available Objective: Clinical reasoning is usually taught using a problem-solving approach, which is widely adopted in medical education. However, learning through problem solving is difficult as a result of the contextualization and dynamic aspects of actual problems. Moreover, knowledge acquired from problem-solving practice tends to be inert and fragmented. This study proposed a computer-based cognitive representation approach that externalizes and facilitates the complex processes in learning clinical reasoning. The approach is operationalized in a computer-based cognitive representation tool that involves argument mapping to externalize the problem-solving process and concept mapping to reveal the knowledge constructed from the problems. Methods: Twenty-nine Year 3 or higher students from a medical school in east China participated in the study. Participants used the proposed approach implemented in an e-learning system to complete four learning cases in 4 weeks on an individual basis. For each case, students interacted with the problem to capture critical data, generate and justify hypotheses, make a diagnosis, recall relevant knowledge, and update their conceptual understanding of the problem domain. Meanwhile, students used the computer-based cognitive representation tool to articulate and represent the key elements and their interactions in the learning process. Results: A significant improvement was found in students’ learning products from the beginning to the end of the study, consistent with students’ report of close-to-moderate progress in developing problem-solving and knowledge-construction abilities. No significant differences were found between the pretest and posttest scores with the 4-week period. The cognitive representation approach was found to provide more formative assessment. Conclusions: The computer-based cognitive representation approach improved the learning of clinical reasoning in both problem solving and knowledge

The inability to mentally represent action may be associated with performance deficits in children with developmental coordination disorder.

Science.gov (United States)

Gabbard, Carl; Bobbio, Tatiana

2011-03-01

Several research studies indicate that children with developmental coordination disorder (DCD) show delays with an array of perceptual-motor skills. One of the explanations, based on limited research, is that these children have problems generating and/or monitoring a mental (action) representation of intended actions, termed the "internal modeling deficit" (IMD) hypothesis. According to the hypothesis, children with DCD have significant limitations in their ability to accurately generate and utilize internal models of motor planning and control. The focus of this review is on one of the methods used to examine action representation-motor imagery, which theorists argue provides a window into the process of action representation (e.g., Jeannerod, 2001 . Neural simulation of action: A unifying mechanism for motor cognition. Neuroimage, 14, 103-109.). Included in the review are performance studies of typically developing and DCD children, and possible brain structures involved.

Intrinsically motivated action-outcome learning and goal-based action recall: a system-level bio-constrained computational model.

Science.gov (United States)

Baldassarre, Gianluca; Mannella, Francesco; Fiore, Vincenzo G; Redgrave, Peter; Gurney, Kevin; Mirolli, Marco

2013-05-01

Reinforcement (trial-and-error) learning in animals is driven by a multitude of processes. Most animals have evolved several sophisticated systems of 'extrinsic motivations' (EMs) that guide them to acquire behaviours allowing them to maintain their bodies, defend against threat, and reproduce. Animals have also evolved various systems of 'intrinsic motivations' (IMs) that allow them to acquire actions in the absence of extrinsic rewards. These actions are used later to pursue such rewards when they become available. Intrinsic motivations have been studied in Psychology for many decades and their biological substrates are now being elucidated by neuroscientists. In the last two decades, investigators in computational modelling, robotics and machine learning have proposed various mechanisms that capture certain aspects of IMs. However, we still lack models of IMs that attempt to integrate all key aspects of intrinsically motivated learning and behaviour while taking into account the relevant neurobiological constraints. This paper proposes a bio-constrained system-level model that contributes a major step towards this integration. The model focusses on three processes related to IMs and on the neural mechanisms underlying them: (a) the acquisition of action-outcome associations (internal models of the agent-environment interaction) driven by phasic dopamine signals caused by sudden, unexpected changes in the environment; (b) the transient focussing of visual gaze and actions on salient portions of the environment; (c) the subsequent recall of actions to pursue extrinsic rewards based on goal-directed reactivation of the representations of their outcomes. The tests of the model, including a series of selective lesions, show how the focussing processes lead to a faster learning of action-outcome associations, and how these associations can be recruited for accomplishing goal-directed behaviours. The model, together with the background knowledge reviewed in the paper

Renormalized action improvements

International Nuclear Information System (INIS)

Zachos, C.

1984-01-01

Finite lattice spacing artifacts are suppressed on the renormalized actions. The renormalized action trajectories of SU(N) lattice gauge theories are considered from the standpoint of the Migdal-Kadanoff approximation. The minor renormalized trajectories which involve representations invariant under the center are discussed and quantified. 17 references

A simulation of T-wave alternans vectocardiographic representation performed by changing the ventricular heart cells action potential duration.

Science.gov (United States)

Janusek, D; Kania, M; Zaczek, R; Zavala-Fernandez, H; Maniewski, R

2014-04-01

The presence of T wave alternans (TWA) in the surface ECG signals has been recognized as a marker of electrical instability, and is hypothesized to be related to patients at increased risk for ventricular arrhythmias. In this paper we present a TWA simulation study. The TWA phenomenon was simulated by changing the duration of the ventricular heart cells action potential. The magnitude was calculated in the surface ECG with the use of the time domain method. The spatially concordant TWA, where during one heart beat all ventricular cells display a short-duration action potential and during the next beat they exhibit a long-duration action potential, as well as the discordant TWA, where at least one region is out of phase, was simulated. The vectocardiographic representation was employed. The obtained results showed a high level of T-loop pattern and location disturbances connected to the discordant TWA simulation in contrast to the concordant one. This result may be explained by the spatial heterogeneity of the ventricular repolarization process, which could be higher for the discordant TWA than for the concordant TWA. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Representation and Imperialism in Edward Said

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Bruno Sciberras de Carvalho

2010-12-01

Full Text Available Based on the idea that culture and identities involve a politically built process, the importance of the concepts of representation and imperialism in the work of Edward Said is discussed. The article analyses two of the author’s general proposals. Firstly, the thesis of the centrality of cultural dimension in political relations, which leads to the review of postulates that consider culture as a mere reflection of a phenomena seen as essential or as a sphere isolated from the power practices. Secondly, the study examines how the author’s conception of imperialism is used as a means of identification that keep structures of authority and hegemony, which, in turn, may be defied by processes of resistance. Finally, the validity of the open character of Said’s political theory is debated, which encompasses both the power of representations and an action of political questioning.

Representation Learning of Logic Words by an RNN: From Word Sequences to Robot Actions

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Tatsuro Yamada

2017-12-01

Full Text Available An important characteristic of human language is compositionality. We can efficiently express a wide variety of real-world situations, events, and behaviors by compositionally constructing the meaning of a complex expression from a finite number of elements. Previous studies have analyzed how machine-learning models, particularly neural networks, can learn from experience to represent compositional relationships between language and robot actions with the aim of understanding the symbol grounding structure and achieving intelligent communicative agents. Such studies have mainly dealt with the words (nouns, adjectives, and verbs that directly refer to real-world matters. In addition to these words, the current study deals with logic words, such as “not,” “and,” and “or” simultaneously. These words are not directly referring to the real world, but are logical operators that contribute to the construction of meaning in sentences. In human–robot communication, these words may be used often. The current study builds a recurrent neural network model with long short-term memory units and trains it to learn to translate sentences including logic words into robot actions. We investigate what kind of compositional representations, which mediate sentences and robot actions, emerge as the network's internal states via the learning process. Analysis after learning shows that referential words are merged with visual information and the robot's own current state, and the logical words are represented by the model in accordance with their functions as logical operators. Words such as “true,” “false,” and “not” work as non-linear transformations to encode orthogonal phrases into the same area in a memory cell state space. The word “and,” which required a robot to lift up both its hands, worked as if it was a universal quantifier. The word “or,” which required action generation that looked apparently random, was represented as an

Generalized Hough transform based time invariant action recognition with 3D pose information

Science.gov (United States)

Muench, David; Huebner, Wolfgang; Arens, Michael

2014-10-01

Human action recognition has emerged as an important field in the computer vision community due to its large number of applications such as automatic video surveillance, content based video-search and human robot interaction. In order to cope with the challenges that this large variety of applications present, recent research has focused more on developing classifiers able to detect several actions in more natural and unconstrained video sequences. The invariance discrimination tradeoff in action recognition has been addressed by utilizing a Generalized Hough Transform. As a basis for action representation we transform 3D poses into a robust feature space, referred to as pose descriptors. For each action class a one-dimensional temporal voting space is constructed. Votes are generated from associating pose descriptors with their position in time relative to the end of an action sequence. Training data consists of manually segmented action sequences. In the detection phase valid human 3D poses are assumed as input, e.g. originating from 3D sensors or monocular pose reconstruction methods. The human 3D poses are normalized to gain view-independence and transformed into (i) relative limb-angle space to ensure independence of non-adjacent joints or (ii) geometric features. In (i) an action descriptor consists of the relative angles between limbs and their temporal derivatives. In (ii) the action descriptor consists of different geometric features. In order to circumvent the problem of time-warping we propose to use a codebook of prototypical 3D poses which is generated from sample sequences of 3D motion capture data. This idea is in accordance with the concept of equivalence classes in action space. Results of the codebook method are presented using the Kinect sensor and the CMU Motion Capture Database.

Converting biomolecular modelling data based on an XML representation.

Science.gov (United States)

Sun, Yudong; McKeever, Steve

2008-08-25

Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language). BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

Converting Biomolecular Modelling Data Based on an XML Representation

Directory of Open Access Journals (Sweden)

Sun Yudong

2008-06-01

Full Text Available Biomolecular modelling has provided computational simulation based methods for investigating biological processes from quantum chemical to cellular levels. Modelling such microscopic processes requires atomic description of a biological system and conducts in fine timesteps. Consequently the simulations are extremely computationally demanding. To tackle this limitation, different biomolecular models have to be integrated in order to achieve high-performance simulations. The integration of diverse biomolecular models needs to convert molecular data between different data representations of different models. This data conversion is often non-trivial, requires extensive human input and is inevitably error prone. In this paper we present an automated data conversion method for biomolecular simulations between molecular dynamics and quantum mechanics/molecular mechanics models. Our approach is developed around an XML data representation called BioSimML (Biomolecular Simulation Markup Language. BioSimML provides a domain specific data representation for biomolecular modelling which can effciently support data interoperability between different biomolecular simulation models and data formats.

Groupoid extensions of mapping class representations for bordered surfaces

DEFF Research Database (Denmark)

Andersen, Jørgen Ellegaard; Bene, Alex; Penner, Robert

2009-01-01

by explicit formulae depending upon six essential cases, and the kernel and image of the groupoid representation are computed. Furthermore, this provides groupoid extensions of any representation of the mapping class group that factors through its action on the fundamental group of the surface including...

A Description Logic Based Knowledge Representation Model for Concept Understanding

DEFF Research Database (Denmark)

Badie, Farshad

2017-01-01

This research employs Description Logics in order to focus on logical description and analysis of the phenomenon of ‘concept understanding’. The article will deal with a formal-semantic model for figuring out the underlying logical assumptions of ‘concept understanding’ in knowledge representation...... systems. In other words, it attempts to describe a theoretical model for concept understanding and to reflect the phenomenon of ‘concept understanding’ in terminological knowledge representation systems. Finally, it will design an ontology that schemes the structure of concept understanding based...

On functional representations of the conformal algebra

Energy Technology Data Exchange (ETDEWEB)

Rosten, Oliver J.

2017-07-15

Starting with conformally covariant correlation functions, a sequence of functional representations of the conformal algebra is constructed. A key step is the introduction of representations which involve an auxiliary functional. It is observed that these functionals are not arbitrary but rather must satisfy a pair of consistency equations corresponding to dilatation and special conformal invariance. In a particular representation, the former corresponds to the canonical form of the exact renormalization group equation specialized to a fixed point whereas the latter is new. This provides a concrete understanding of how conformal invariance is realized as a property of the Wilsonian effective action and the relationship to action-free formulations of conformal field theory. Subsequently, it is argued that the conformal Ward Identities serve to define a particular representation of the energy-momentum tensor. Consistency of this construction implies Polchinski's conditions for improving the energy-momentum tensor of a conformal field theory such that it is traceless. In the Wilsonian approach, the exactly marginal, redundant field which generates lines of physically equivalent fixed points is identified as the trace of the energy-momentum tensor. (orig.)

Energetic macroscopic representation and inversion-based control of a CVT-based HEV

NARCIS (Netherlands)

Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

2014-01-01

A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

Energetic macroscopic representation and inversion- based control of a CVT-based HEV

NARCIS (Netherlands)

Chouhou, M.; Grée, F.; Jivan, C.; Bouscayrol, A.; Hofman, T.

2013-01-01

A Continuous Variable Transmission (CVT) is introduced in the simulation model of a Hybrid Electric Vehicle (HEV). The CVT-based vehicle simulation and its control are deduced from the Energetic Macroscopic Representation (EMR). Simulations are provided to show the interest of the CVT in term of

Action, outcome, and value: a dual-system framework for morality.

Science.gov (United States)

Cushman, Fiery

2013-08-01

Dual-system approaches to psychology explain the fundamental properties of human judgment, decision making, and behavior across diverse domains. Yet, the appropriate characterization of each system is a source of debate. For instance, a large body of research on moral psychology makes use of the contrast between "emotional" and "rational/cognitive" processes, yet even the chief proponents of this division recognize its shortcomings. Largely independently, research in the computational neurosciences has identified a broad division between two algorithms for learning and choice derived from formal models of reinforcement learning. One assigns value to actions intrinsically based on past experience, while another derives representations of value from an internally represented causal model of the world. This division between action- and outcome-based value representation provides an ideal framework for a dual-system theory in the moral domain.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

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Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

Science.gov (United States)

Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Video based object representation and classification using multiple covariance matrices.

Science.gov (United States)

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.

A Representation System User Interface for Knowledge Base Designers

OpenAIRE

Fikes, Richard E.

1982-01-01

A major strength of frame-based knowledge representation languages is their ability to provide the knowledge base designer with a concise and intuitively appealing means expression. The claim of intuitive appeal is based on the observation that the object -centered style of description provided by these languages often closely matches a designer's understanding of the domain being modeled and therefore lessens the burden of reformulation involved in developing a formal description. To be effe...

[Municipal Health Councils: activity and representation of grassroots communities].

Science.gov (United States)

Gerschman, Silvia

2004-01-01

This article was based on the results of research concerning health policy in municipalities that achieved the most extensive development of decentralization and innovation in the State of Rio de Janeiro, Brazil. The study applied a questionnaire for health system users' representatives in Municipal Health Councils. The central issues were: the Councils' political role; social control by the Councils, viewed as surveillance by organized society over government actions; the nature of social representation exercised by the Council members; and the type of mandate they serve. Community representatives in the Councils reinforce aspects pertaining to the exercise of representation in unequal societies. There is a predominance of a differentiated elite consisting of older males with more schooling and higher income than the community average. The notion of "social control" as the basis for the Councils is difficult for the members to grasp. Exercise of representation is diffuse, occurring by way of designation by community associations, election in assemblies, or designation by institutional health policy agencies.

Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.

Science.gov (United States)

Shi, Jun; Liu, Xiao; Li, Yan; Zhang, Qi; Li, Yingjie; Ying, Shihui

2015-10-30

Electroencephalography (EEG) based sleep staging is commonly used in clinical routine. Feature extraction and representation plays a crucial role in EEG-based automatic classification of sleep stages. Sparse representation (SR) is a state-of-the-art unsupervised feature learning method suitable for EEG feature representation. Collaborative representation (CR) is an effective data coding method used as a classifier. Here we use CR as a data representation method to learn features from the EEG signal. A joint collaboration model is established to develop a multi-view learning algorithm, and generate joint CR (JCR) codes to fuse and represent multi-channel EEG signals. A two-stage multi-view learning-based sleep staging framework is then constructed, in which JCR and joint sparse representation (JSR) algorithms first fuse and learning the feature representation from multi-channel EEG signals, respectively. Multi-view JCR and JSR features are then integrated and sleep stages recognized by a multiple kernel extreme learning machine (MK-ELM) algorithm with grid search. The proposed two-stage multi-view learning algorithm achieves superior performance for sleep staging. With a K-means clustering based dictionary, the mean classification accuracy, sensitivity and specificity are 81.10 ± 0.15%, 71.42 ± 0.66% and 94.57 ± 0.07%, respectively; while with the dictionary learned using the submodular optimization method, they are 80.29 ± 0.22%, 71.26 ± 0.78% and 94.38 ± 0.10%, respectively. The two-stage multi-view learning based sleep staging framework outperforms all other classification methods compared in this work, while JCR is superior to JSR. The proposed multi-view learning framework has the potential for sleep staging based on multi-channel or multi-modality polysomnography signals. Copyright © 2015 Elsevier B.V. All rights reserved.

The Koslowski-Sahlmann representation: quantum configuration space

Science.gov (United States)

Campiglia, Miguel; Varadarajan, Madhavan

2014-09-01

The Koslowski-Sahlmann (KS) representation is a generalization of the representation underlying the discrete spatial geometry of loop quantum gravity (LQG), to accommodate states labelled by smooth spatial geometries. As shown recently, the KS representation supports, in addition to the action of the holonomy and flux operators, the action of operators which are the quantum counterparts of certain connection dependent functions known as ‘background exponentials’. Here we show that the KS representation displays the following properties which are the exact counterparts of LQG ones: (i) the abelian * algebra of SU(2) holonomies and ‘U(1)’ background exponentials can be completed to a C* algebra, (ii) the space of semianalytic SU(2) connections is topologically dense in the spectrum of this algebra, (iii) there exists a measure on this spectrum for which the KS Hilbert space is realized as the space of square integrable functions on the spectrum, (iv) the spectrum admits a characterization as a projective limit of finite numbers of copies of SU(2) and U(1), (v) the algebra underlying the KS representation is constructed from cylindrical functions and their derivations in exactly the same way as the LQG (holonomy-flux) algebra except that the KS cylindrical functions depend on the holonomies and the background exponentials, this extra dependence being responsible for the differences between the KS and LQG algebras. While these results are obtained for compact spaces, they are expected to be of use for the construction of the KS representation in the asymptotically flat case.

User-based representation of time-resolved multimodal public transportation networks.

Science.gov (United States)

Alessandretti, Laura; Karsai, Márton; Gauvin, Laetitia

2016-07-01

Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments.

Language, Gesture, Action! A Test of the Gesture as Simulated Action Framework

Science.gov (United States)

Hostetter, Autumn B.; Alibali, Martha W.

2010-01-01

The Gesture as Simulated Action (GSA) framework (Hostetter & Alibali, 2008) holds that representational gestures are produced when actions are simulated as part of thinking and speaking. Accordingly, speakers should gesture more when describing images with which they have specific physical experience than when describing images that are less…

Collective Memories of Portuguese Colonial Action in Africa: Representations of the Colonial Past among Mozambicans and Portuguese Youths

Directory of Open Access Journals (Sweden)

João Feijó

2010-05-01

Full Text Available Social representations of the colonization and decolonization processes among young people from a former European colonial power (Portugal and from an African ex-colony (Mozambique were investigated through surveys using open- and closed-ended questions about national history, focusing on the identity functions of collective memories. Hegemonic and contested representations were found of the most prominent events related to Portuguese colonization of Mozambique, arousing a range of collective emotions. A central place is occupied by memories of the Colonial War, which ended with the Carnation Revolution in Portugal and the subsequent independence of the Portuguese African colonies. Overall, the depiction of colonialism was more negative for Mozambican than for Portuguese participants. The violent effects of colonial action were very salient in Mozambican memories, which stressed the most oppressive aspects of the colonial period, associated with slave trade and brutal repression. On the Portuguese side, the idealization of the voyages of discovery persisted, obscuring the most violent effects of colonial expansion. However, collective memories of colonization of former colonizer and former colonized do not simply stand opposed. Both Mozambican and Portuguese participants reported ambivalent feelings towards the colonization process.

Refining the Construct of Classroom-Based Writing-from-Readings Assessment: The Role of Task Representation

Science.gov (United States)

Wolfersberger, Mark

2013-01-01

This article argues that task representation should be considered as part of the construct of classroom-based academic writing. Task representation is a process that writers move through when creating a unique mental model of the requirements for each new writing task they encounter. Writers' task representations evolve throughout the composing…

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Science.gov (United States)

Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun

2014-01-01

Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.

Locality constrained joint dynamic sparse representation for local matching based face recognition.

Directory of Open Access Journals (Sweden)

Jianzhong Wang

Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.

Characterising expert representations during real-time action : A Skill Theory application to soccer

NARCIS (Netherlands)

Den Hartigh, Ruud J. R.; Van Der Steen, Steffie; De Meij, Mart; Van Yperen, Nico W.; Gernigon, Christophe; Van Geert, Paul L. C.

2014-01-01

In various domains, experts are found to possess elaborate domain-specific representations they developed over years. In this study, we provide the first systematic attempt to characterise the short-term representations among individuals with different expertise levels. We showed videos of soccer

Everyday robotic action: Lessons from human action control

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Roy eDe Kleijn

2014-03-01

Full Text Available Robots are increasingly capable of performing everyday human activities such as cooking, cleaning, and doing the laundry. This requires the real-time planning and execution of complex, temporally-extended sequential actions under high degrees of uncertainty, which provides many challenges to traditional approaches to robot action control. We argue that important lessons in this respect can be learned from research on human action control. We provide a brief overview of available psychological insights into this issue and focus on four principles that we think could be particularly beneficial for robot control: the integration of symbolic and subsymbolic planning of action sequences, the integration of feedforward and feedback control, the clustering of complex actions into subcomponents, and the contextualization of action-control structures through goal representations.

Reexamining the language account of cross-national differences in base-10 number representations.

Science.gov (United States)

Vasilyeva, Marina; Laski, Elida V; Ermakova, Anna; Lai, Weng-Feng; Jeong, Yoonkyung; Hachigian, Amy

2015-01-01

East Asian students consistently outperform students from other nations in mathematics. One explanation for this advantage is a language account; East Asian languages, unlike most Western languages, provide cues about the base-10 structure of multi-digit numbers, facilitating the development of base-10 number representations. To test this view, the current study examined how kindergartners represented two-digit numbers using single unit-blocks and ten-blocks. The participants (N=272) were from four language groups (Korean, Mandarin, English, and Russian) that vary in the extent of "transparency" of the base-10 structure. In contrast to previous findings with older children, kindergartners showed no cross-language variability in the frequency of producing base-10 representations. Furthermore, they showed a pattern of within-language variability that was not consistent with the language account and was likely attributable to experiential factors. These findings suggest that language might not play as critical a role in the development of base-10 representations as suggested in earlier research. Copyright © 2014 Elsevier Inc. All rights reserved.

On knowledge representation for high energy physics control systems

International Nuclear Information System (INIS)

Huuskonen, P.; Kaarela, K.; Meri, M.; Le Goff, J.M.

1994-01-01

A framework for knowledge representation in the domain of high energy physics control systems is presented. Models of process equipment, controls, documents, information systems, functional dependencies, physical interconnections, and design decisions are necessary to allow for automated reasoning about such systems. A number of support systems can use these models: alarm processing, fault diagnosis, sensor validation, preventive maintenance, action analysis, information abstraction, intelligent help systems, and on-line documentation. Our aim is to achieve representations that would be understood by end users, could be constructed by domain experts, and would be powerful enough to function as a basis for these support systems. It is proposed to base these models on means-end-analysis, implemented through an entity-relationship type of representation and extended with the notion of contribution. The paper outlines class hierarchies and relation types to form a vocabulary for talking about this specific domain. A number of implementation concerns are raised and some examples of how these representations can be used in real cases are offered. The representations are likely to prove most useful for support systems that function in the user assisting mode, as opposed to fully autonomous systems. Intelligent help and information abstraction applications, in particular, are expected to benefit. The main focus of the work is that of the control information system concepts based on encapsulated real- time objects (CICERO) project at CERN, experiment controls, but the results are usable for accelerator control systems and for industrial control systems in general. (author). 37 refs., 7 figs

A Gloss Composition and Context Clustering Based Distributed Word Sense Representation Model

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Tao Chen

2015-08-01

Full Text Available In recent years, there has been an increasing interest in learning a distributed representation of word sense. Traditional context clustering based models usually require careful tuning of model parameters, and typically perform worse on infrequent word senses. This paper presents a novel approach which addresses these limitations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned representations outperform the publicly available embeddings on half of the metrics in the word similarity task, 6 out of 13 sub tasks in the analogical reasoning task, and gives the best overall accuracy in the word sense effect classification task, which shows the effectiveness of our proposed distributed distribution learning model.

Human action recognition with depth cameras

CERN Document Server

Wang, Jiang; Wu, Ying

2014-01-01

Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, includi

Multiple Kernel Sparse Representation based Orthogonal Discriminative Projection and Its Cost-Sensitive Extension.

Science.gov (United States)

Zhang, Guoqing; Sun, Huaijiang; Xia, Guiyu; Sun, Quansen

2016-07-07

Sparse representation based classification (SRC) has been developed and shown great potential for real-world application. Based on SRC, Yang et al. [10] devised a SRC steered discriminative projection (SRC-DP) method. However, as a linear algorithm, SRC-DP cannot handle the data with highly nonlinear distribution. Kernel sparse representation-based classifier (KSRC) is a non-linear extension of SRC and can remedy the drawback of SRC. KSRC requires the use of a predetermined kernel function and selection of the kernel function and its parameters is difficult. Recently, multiple kernel learning for SRC (MKL-SRC) [22] has been proposed to learn a kernel from a set of base kernels. However, MKL-SRC only considers the within-class reconstruction residual while ignoring the between-class relationship, when learning the kernel weights. In this paper, we propose a novel multiple kernel sparse representation-based classifier (MKSRC), and then we use it as a criterion to design a multiple kernel sparse representation based orthogonal discriminative projection method (MK-SR-ODP). The proposed algorithm aims at learning a projection matrix and a corresponding kernel from the given base kernels such that in the low dimension subspace the between-class reconstruction residual is maximized and the within-class reconstruction residual is minimized. Furthermore, to achieve a minimum overall loss by performing recognition in the learned low-dimensional subspace, we introduce cost information into the dimensionality reduction method. The solutions for the proposed method can be efficiently found based on trace ratio optimization method [33]. Extensive experimental results demonstrate the superiority of the proposed algorithm when compared with the state-of-the-art methods.

Ontological Representation of Light Wave Camera Data to Support Vision-Based AmI

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José Manuel Molina

2012-09-01

Full Text Available Recent advances in technologies for capturing video data have opened a vast amount of new application areas in visual sensor networks. Among them, the incorporation of light wave cameras on Ambient Intelligence (AmI environments provides more accurate tracking capabilities for activity recognition. Although the performance of tracking algorithms has quickly improved, symbolic models used to represent the resulting knowledge have not yet been adapted to smart environments. This lack of representation does not allow to take advantage of the semantic quality of the information provided by new sensors. This paper advocates for the introduction of a part-based representational level in cognitive-based systems in order to accurately represent the novel sensors’ knowledge. The paper also reviews the theoretical and practical issues in part-whole relationships proposing a specific taxonomy for computer vision approaches. General part-based patterns for human body and transitive part-based representation and inference are incorporated to an ontology-based previous framework to enhance scene interpretation in the area of video-based AmI. The advantages and new features of the model are demonstrated in a Social Signal Processing (SSP application for the elaboration of live market researches.

A Walk-based Semantically Enriched Tree Kernel Over Distributed Word Representations

DEFF Research Database (Denmark)

Srivastava, Shashank; Hovy, Dirk

2013-01-01

We propose a walk-based graph kernel that generalizes the notion of tree-kernels to continuous spaces. Our proposed approach subsumes a general framework for word-similarity, and in particular, provides a flexible way to incorporate distributed representations. Using vector representations......, such an approach captures both distributional semantic similarities among words as well as the structural relations between them (encoded as the structure of the parse tree). We show an efficient formulation to compute this kernel using simple matrix multiplication operations. We present our results on three...

A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory.

Energy Technology Data Exchange (ETDEWEB)

Johnson, J. D. (Prostat, Mesa, AZ); Oberkampf, William Louis; Helton, Jon Craig (Arizona State University, Tempe, AZ); Storlie, Curtis B. (North Carolina State University, Raleigh, NC)

2006-10-01

Evidence theory provides an alternative to probability theory for the representation of epistemic uncertainty in model predictions that derives from epistemic uncertainty in model inputs, where the descriptor epistemic is used to indicate uncertainty that derives from a lack of knowledge with respect to the appropriate values to use for various inputs to the model. The potential benefit, and hence appeal, of evidence theory is that it allows a less restrictive specification of uncertainty than is possible within the axiomatic structure on which probability theory is based. Unfortunately, the propagation of an evidence theory representation for uncertainty through a model is more computationally demanding than the propagation of a probabilistic representation for uncertainty, with this difficulty constituting a serious obstacle to the use of evidence theory in the representation of uncertainty in predictions obtained from computationally intensive models. This presentation describes and illustrates a sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory. Preliminary trials indicate that the presented strategy can be used to propagate uncertainty representations based on evidence theory in analysis situations where naive sampling-based (i.e., unsophisticated Monte Carlo) procedures are impracticable due to computational cost.

Body posture modulates action perception.

Science.gov (United States)

Zimmermann, Marius; Toni, Ivan; de Lange, Floris P

2013-04-03

Recent studies have highlighted cognitive and neural similarities between planning and perceiving actions. Given that action planning involves a simulation of potential action plans that depends on the actor's body posture, we reasoned that perceiving actions may also be influenced by one's body posture. Here, we test whether and how this influence occurs by measuring behavioral and cerebral (fMRI) responses in human participants predicting goals of observed actions, while manipulating postural congruency between their own body posture and postures of the observed agents. Behaviorally, predicting action goals is facilitated when the body posture of the observer matches the posture achieved by the observed agent at the end of his action (action's goal posture). Cerebrally, this perceptual postural congruency effect modulates activity in a portion of the left intraparietal sulcus that has previously been shown to be involved in updating neural representations of one's own limb posture during action planning. This intraparietal area showed stronger responses when the goal posture of the observed action did not match the current body posture of the observer. These results add two novel elements to the notion that perceiving actions relies on the same predictive mechanism as planning actions. First, the predictions implemented by this mechanism are based on the current physical configuration of the body. Second, during both action planning and action observation, these predictions pertain to the goal state of the action.

Integration of object-oriented knowledge representation with the CLIPS rule based system

Science.gov (United States)

Logie, David S.; Kamil, Hasan

1990-01-01

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Multi-Label Classification Based on Low Rank Representation for Image Annotation

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Qiaoyu Tan

2017-01-01

Full Text Available Annotating remote sensing images is a challenging task for its labor demanding annotation process and requirement of expert knowledge, especially when images can be annotated with multiple semantic concepts (or labels. To automatically annotate these multi-label images, we introduce an approach called Multi-Label Classification based on Low Rank Representation (MLC-LRR. MLC-LRR firstly utilizes low rank representation in the feature space of images to compute the low rank constrained coefficient matrix, then it adapts the coefficient matrix to define a feature-based graph and to capture the global relationships between images. Next, it utilizes low rank representation in the label space of labeled images to construct a semantic graph. Finally, these two graphs are exploited to train a graph-based multi-label classifier. To validate the performance of MLC-LRR against other related graph-based multi-label methods in annotating images, we conduct experiments on a public available multi-label remote sensing images (Land Cover. We perform additional experiments on five real-world multi-label image datasets to further investigate the performance of MLC-LRR. Empirical study demonstrates that MLC-LRR achieves better performance on annotating images than these comparing methods across various evaluation criteria; it also can effectively exploit global structure and label correlations of multi-label images.

A cross-talk between brain-damage patients and infants on action and language.

Science.gov (United States)

Papeo, Liuba; Hochmann, Jean-Remy

2012-06-01

Sensorimotor representations in the brain encode the sensory and motor aspects of one's own bodily activity. It is highly debated whether sensorimotor representations are the core basis for the representation of action-related knowledge and, in particular, action words, such as verbs. In this review, we will address this question by bringing to bear insights from the study of brain-damaged patients exhibiting language disorders and from the study of the mechanisms for language acquisition in infants. Cognitive neuropsychology studies have assessed how damage to representations supporting action production impacts patients' ability to process action-related words. While correlations between verbal and nonverbal (motor) impairments are very common in patients, damage to the representations for action production can leave the ability to understand action-words unaffected; likewise, actions can still be produced successfully in cases of impaired action-word understanding. Studies with infants have evaluated the relevance of sensorimotor information when infants learn to map a novel word onto an action that they are performing or perceiving. These results demonstrate that sensorimotor information is insufficient to fully account for the complexity of verb learning: in this process, infants seem to privilege abstract constructs such as goal, intentionality and causality, as well as syntactic constraints, over the perceptual and motor dimensions of an action. Altogether, the empirical data suggest that, while not crucial for verb learning and understanding, sensorimotor processes can contribute to solving the problem of symbol grounding and/or serve as a primary mechanism in social cognition, to learn about others' goals and intentions. By assessing the relevance of sensorimotor representations in the way action-related words are acquired and represented, we aim to provide a useful set of criteria for testing specific predictions made by different theories of concepts

Computational neuroanatomy: ontology-based representation of neural components and connectivity.

Science.gov (United States)

Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

2009-02-05

A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

Complementary and alternative medicine - representations in popular magazines.

Science.gov (United States)

Dunne, Alexandra; Phillips, Christine

2010-09-01

More than half the patients who use complementary and alternative medicine (CAM) in Australia do not discuss it with their doctors. Many consumers use popular media, especially women's magazines, to learn about CAM. To explore representations of CAM in popular Australian women's magazines. Content analysis of three Australian magazines: Australian Women's Weekly, Dolly and New Idea published from January to June 2008. Of 220 references to CAM (4-17 references per issue), most were to biologically based practices, particularly 'functional foods', which enhance health. Most representations of CAM were positive (81.3% positive, 16.4% neutral, 2.3% negative). Explanations of modes of action of CAM tended to be biological but relatively superficial. Australian magazines cast CAM as safe therapy which enhances patient engagement in healthcare, and works in ways analogous to orthodox medical treatments. General practitioners can use discussions with their patients about CAM to encourage health promoting practices.

Mirror representations innate versus determined by experience: a viewpoint from learning theory.

Science.gov (United States)

Giese, Martin A

2014-04-01

From the viewpoint of pattern recognition and computational learning, mirror neurons form an interesting multimodal representation that links action perception and planning. While it seems unlikely that all details of such representations are specified by the genetic code, robust learning of such complex representations likely requires an appropriate interplay between plasticity, generalization, and anatomical constraints of the underlying neural architecture.

Features based approach for indexation and representation of unstructured Arabic documents

Directory of Open Access Journals (Sweden)

Mohamed Salim El Bazzi

2017-06-01

Full Text Available The increase of textual information published in Arabic language on the internet, public libraries and administrations requires implementing effective techniques for the extraction of relevant information contained in large corpus of texts. The purpose of indexing is to create a document representation that easily find and identify the relevant information in a set of documents. However, mining textual data is becoming a complicated task, especially when taking semantic into consideration. In this paper, we will present an indexation system based on contextual representation that will take the advantage of semantic links given in a document. Our approach is based on the extraction of keyphrases. Then, each document is represented by its relevant keyphrases instead of its simple keywords. The experimental results confirms the effectiveness of our approach.

Effective Heart Disease Detection Based on Quantitative Computerized Traditional Chinese Medicine Using Representation Based Classifiers

Directory of Open Access Journals (Sweden)

Ting Shu

2017-01-01

Full Text Available At present, heart disease is the number one cause of death worldwide. Traditionally, heart disease is commonly detected using blood tests, electrocardiogram, cardiac computerized tomography scan, cardiac magnetic resonance imaging, and so on. However, these traditional diagnostic methods are time consuming and/or invasive. In this paper, we propose an effective noninvasive computerized method based on facial images to quantitatively detect heart disease. Specifically, facial key block color features are extracted from facial images and analyzed using the Probabilistic Collaborative Representation Based Classifier. The idea of facial key block color analysis is founded in Traditional Chinese Medicine. A new dataset consisting of 581 heart disease and 581 healthy samples was experimented by the proposed method. In order to optimize the Probabilistic Collaborative Representation Based Classifier, an analysis of its parameters was performed. According to the experimental results, the proposed method obtains the highest accuracy compared with other classifiers and is proven to be effective at heart disease detection.

76 FR 37291 - Representation Case Procedures

Science.gov (United States)

2011-06-27

... communications must include the following words on the Subject Line--``Request to Attend Public Meeting Regarding... NATIONAL LABOR RELATIONS BOARD 29 CFR Parts 101, 102, 103 RIN 3142-AAO8 Representation Case Procedures AGENCY: National Labor Relations Board. ACTION: Proposed rule; notice of meeting. SUMMARY: The...

HiTEC: a connectionist model of the interaction between perception and action planning.

Science.gov (United States)

Haazebroek, Pascal; Raffone, Antonino; Hommel, Bernhard

2017-11-01

Increasing evidence suggests that perception and action planning do not represent separable stages of a unidirectional processing sequence, but rather emerging properties of highly interactive processes. To capture these characteristics of the human cognitive system, we have developed a connectionist model of the interaction between perception and action planning: HiTEC, based on the Theory of Event Coding (Hommel et al. in Behav Brain Sci 24:849-937, 2001). The model is characterized by representations at multiple levels and by shared representations and processes. It complements available models of stimulus-response translation by providing a rationale for (1) how situation-specific meanings of motor actions emerge, (2) how and why some aspects of stimulus-response translation occur automatically and (3) how task demands modulate sensorimotor processing. The model is demonstrated to provide a unitary account and simulation of a number of key findings with multiple experimental paradigms on the interaction between perception and action such as the Simon effect, its inversion (Hommel in Psychol Res 55:270-279, 1993), and action-effect learning.

Representation of Students in Solving Simultaneous Linear Equation Problems Based on Multiple Intelligence

Science.gov (United States)

Yanti, Y. R.; Amin, S. M.; Sulaiman, R.

2018-01-01

This study described representation of students who have musical, logical-mathematic and naturalist intelligence in solving a problem. Subjects were selected on the basis of multiple intelligence tests (TPM) consists of 108 statements, with 102 statements adopted from Chislet and Chapman and 6 statements equal to eksistensial intelligences. Data were analyzed based on problem-solving tests (TPM) and interviewing. See the validity of the data then problem-solving tests (TPM) and interviewing is given twice with an analyzed using the representation indikator and the problem solving step. The results showed that: the stage of presenting information known, stage of devising a plan, and stage of carrying out the plan those three subjects were using same form of representation. While he stage of presenting information asked and stage of looking back, subject of logical-mathematic was using different forms of representation with subjects of musical and naturalist intelligence. From this research is expected to provide input to the teacher in determining the learning strategy that will be used by considering the representation of students with the basis of multiple intelligences.

Lawrence Berkeley Laboratory Affirmative Action Program. Revised

Energy Technology Data Exchange (ETDEWEB)

NONE

1995-06-01

The Lawrence Berkeley Laboratory`s Affirmative Action Program (AAP) serves as a working document that describes current policies, practices, and results in the area of affirmative action. It represents the Laboratory`s framework for an affirmative approach to increasing the representation of people of color and women in segments of our work force where they have been underrepresented and taking action to increase the employment of persons with disabilities and special disabled and Vietnam era veterans. The AAP describes the hierarchy of responsibility for Laboratory affirmative action, the mechanisms that exist for full Laboratory participation in the AAP, the policies and procedures governing recruitment at all levels, the Laboratory`s plan for monitoring, reporting, and evaluating affirmative action progress, and a description of special affirmative action programs and plans the Laboratory has used and will use in its efforts to increase the representation and retention of groups historically underrepresented in our work force.

Inadequacy representation of flamelet-based RANS model for turbulent non-premixed flame

Science.gov (United States)

Lee, Myoungkyu; Oliver, Todd; Moser, Robert

2017-11-01

Stochastic representations for model inadequacy in RANS-based models of non-premixed jet flames are developed and explored. Flamelet-based RANS models are attractive for engineering applications relative to higher-fidelity methods because of their low computational costs. However, the various assumptions inherent in such models introduce errors that can significantly affect the accuracy of computed quantities of interest. In this work, we develop an approach to represent the model inadequacy of the flamelet-based RANS model. In particular, we pose a physics-based, stochastic PDE for the triple correlation of the mixture fraction. This additional uncertain state variable is then used to construct perturbations of the PDF for the instantaneous mixture fraction, which is used to obtain an uncertain perturbation of the flame temperature. A hydrogen-air non-premixed jet flame is used to demonstrate the representation of the inadequacy of the flamelet-based RANS model. This work was supported by DARPA-EQUiPS(Enabling Quantification of Uncertainty in Physical Systems) program.

Representational Momentum in Older Adults

Science.gov (United States)

Piotrowski, Andrea S.; Jakobson, Lorna S.

2011-01-01

Humans have a tendency to perceive motion even in static images that simply "imply" movement. This tendency is so strong that our memory for actions depicted in static images is distorted in the direction of implied motion--a phenomenon known as representational momentum (RM). In the present study, we created an RM display depicting a pattern of…

Alternative approach to nuclear data representation

International Nuclear Information System (INIS)

Pruet, J.; Brown, D.; Beck, B.; McNabb, D.P.

2006-01-01

This paper considers an approach for representing nuclear data that is qualitatively different from the approach currently adopted by the nuclear science community. Specifically, we examine a representation in which complicated data is described through collections of distinct and self-contained simple data structures. This structure-based representation is compared with the ENDF and ENDL formats, which can be roughly characterized as dictionary-based representations. A pilot data representation for replacing the format currently used at LLNL is presented. Examples are given as is a discussion of promises and shortcomings associated with moving from traditional dictionary-based formats to a structure-rich or class-like representation

The role of representation in experience-based choice

Directory of Open Access Journals (Sweden)

Ben R. Newell

2009-12-01

Full Text Available Recently it has been observed that different choices can be made about structurally identical risky decisions depending on whether information about outcomes and their probabilities is learned by description or from experience. Current evidence is equivocal with respect to whether this choice ``gap'' is entirely an artefact of biased samples. The current experiment investigates whether a representational bias exists at the point of encoding by examining choice in light of decision makers' mental representations of the alternatives, measured with both verbal and nonverbal judgment probes. We found that, when estimates were gauged by the nonverbal probe, participants presented with information in description format (as opposed to experience had a greater tendency to overestimate rare events and underestimate common events. The choice gap, however, remained even when accounting for this judgment distortion and the effects of sampling bias. Indeed, participants' estimation of the outcome distribution did not mediate their subsequent choice. It appears that experience-based choices may derive from a process that does not explicitly use probability information.

Distinguishing Representations as Origin and Representations as Input: Roles for Individual Cells

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Jonathan C.W. Edwards

2016-09-01

Full Text Available It is widely perceived that there is a problem in giving a naturalistic account of mental representation that deals adequately with meaning, interpretation or significance (semantic content. It is suggested here that this problem may arise partly from the conflation of two vernacular senses of representation: representation-as-origin and representation-as-input. The flash of a neon sign may in one sense represent a popular drink, but to function as representation it must provide an input to a ‘consumer’ in the street. The arguments presented draw on two principles – the neuron doctrine and the need for a venue for ‘presentation’ or ‘reception’ of a representation at a specified site, consistent with the locality principle. It is also argued that domains of representation cannot be defined by signal traffic, since they can be expected to include ‘null’ elements based on non-firing cells. In this analysis, mental representations-as-origin are distributed patterns of cell firing. Each firing cell is given semantic value in its own right - some form of atomic propositional significance – since different axonal branches may contribute to integration with different populations of signals at different downstream sites. Representations-as-input are patterns of local co-arrival of signals in the form of synaptic potentials in dendrites. Meaning then draws on the relationships between active and null inputs, forming ‘scenarios’ comprising a molecular combination of ‘premises’ from which a new output with atomic propositional significance is generated. In both types of representation, meaning, interpretation or significance pivots on events in an individual cell. (This analysis only applies to ‘occurrent’ representations based on current neural activity. The concept of representations-as-input emphasises the need for a ‘consumer’ of a representation and the dependence of meaning on the co-relationships involved in an

75 FR 32273 - Representation Election Procedure

Science.gov (United States)

2010-06-08

... Representation Election Procedure AGENCY: National Mediation Board. ACTION: Final rule; delay of effective date. SUMMARY: The National Mediation Board (NMB) is delaying the effective date of its rule regarding... participants under the Railway Labor Act (RLA) that the rule will apply to applications filed on or after June...

Translating working memory into action: behavioral and neural evidence for using motor representations in encoding visuo-spatial sequences.

Science.gov (United States)

Langner, Robert; Sternkopf, Melanie A; Kellermann, Tanja S; Grefkes, Christian; Kurth, Florian; Schneider, Frank; Zilles, Karl; Eickhoff, Simon B

2014-07-01

The neurobiological organization of action-oriented working memory is not well understood. To elucidate the neural correlates of translating visuo-spatial stimulus sequences into delayed (memory-guided) sequential actions, we measured brain activity using functional magnetic resonance imaging while participants encoded sequences of four to seven dots appearing on fingers of a left or right schematic hand. After variable delays, sequences were to be reproduced with the corresponding fingers. Recall became less accurate with longer sequences and was initiated faster after long delays. Across both hands, encoding and recall activated bilateral prefrontal, premotor, superior and inferior parietal regions as well as the basal ganglia, whereas hand-specific activity was found (albeit to a lesser degree during encoding) in contralateral premotor, sensorimotor, and superior parietal cortex. Activation differences after long versus short delays were restricted to motor-related regions, indicating that rehearsal during long delays might have facilitated the conversion of the memorandum into concrete motor programs at recall. Furthermore, basal ganglia activity during encoding selectively predicted correct recall. Taken together, the results suggest that to-be-reproduced visuo-spatial sequences are encoded as prospective action representations (motor intentions), possibly in addition to retrospective sensory codes. Overall, our study supports and extends multi-component models of working memory, highlighting the notion that sensory input can be coded in multiple ways depending on what the memorandum is to be used for. Copyright © 2013 Wiley Periodicals, Inc.

Some nonunitary, indecomposable representations of the Euclidean algebra e(3)

International Nuclear Information System (INIS)

Douglas, Andrew; De Guise, Hubert

2010-01-01

The Euclidean group E(3) is the noncompact, semidirect product group E(3)≅R 3 x SO(3). It is the Lie group of orientation-preserving isometries of three-dimensional Euclidean space. The Euclidean algebra e(3) is the complexification of the Lie algebra of E(3). We construct three distinct families of finite-dimensional, nonunitary representations of e(3) and show that each representation is indecomposable. The representations of the first family are explicitly realized as subspaces of the polynomial ring F[X,Y,Z] with the action of e(3) given by differential operators. The other families are constructed via duals and tensor products of the representations within the first family. We describe subrepresentations, quotients and duals of these indecomposable representations.

Video rate morphological processor based on a redundant number representation

Science.gov (United States)

Kuczborski, Wojciech; Attikiouzel, Yianni; Crebbin, Gregory A.

1992-03-01

This paper presents a video rate morphological processor for automated visual inspection of printed circuit boards, integrated circuit masks, and other complex objects. Inspection algorithms are based on gray-scale mathematical morphology. Hardware complexity of the known methods of real-time implementation of gray-scale morphology--the umbra transform and the threshold decomposition--has prompted us to propose a novel technique which applied an arithmetic system without carrying propagation. After considering several arithmetic systems, a redundant number representation has been selected for implementation. Two options are analyzed here. The first is a pure signed digit number representation (SDNR) with the base of 4. The second option is a combination of the base-2 SDNR (to represent gray levels of images) and the conventional twos complement code (to represent gray levels of structuring elements). Operation principle of the morphological processor is based on the concept of the digit level systolic array. Individual processing units and small memory elements create a pipeline. The memory elements store current image windows (kernels). All operation primitives of processing units apply a unified direction of digit processing: most significant digit first (MSDF). The implementation technology is based on the field programmable gate arrays by Xilinx. This paper justified the rationality of a new approach to logic design, which is the decomposition of Boolean functions instead of Boolean minimization.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

Science.gov (United States)

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

Sinusoidal Representation of Acoustic Signals

Science.gov (United States)

Honda, Masaaki

Sinusoidal representation of acoustic signals has been an important tool in speech and music processing like signal analysis, synthesis and time scale or pitch modifications. It can be applicable to arbitrary signals, which is an important advantage over other signal representations like physical modeling of acoustic signals. In sinusoidal representation, acoustic signals are composed as sums of sinusoid (sine wave) with different amplitudes, frequencies and phases, which is based on the timedependent short-time Fourier transform (STFT). This article describes the principles of acoustic signal analysis/synthesis based on a sinusoid representation with focus on sine waves with rapidly varying frequency.

Once Upon a Time, There Were a Princess and a Prince...: Gender Representations in Children’s Narratives

Directory of Open Access Journals (Sweden)

Constantina Xavier Filha

2011-01-01

Full Text Available Gender representations in fairy tales were the focus of an action research with public school children in Campo Grande, Brazil. This paper is part of a larger study, funded by CNPq, which involves two moments: bibliographical reasearch for the selectio and analysis of children’s books dealing with sexuality, gender and diversity, and the action research with children and adolescents. In this second moment, the emphasis is on the discussion of narrative and pictorial texts produced by the children and on the reading of the books selected. This paper presents some of the data collected in the second moment of the project. We seek to understand how they construct gender representations based on the physical and behavioral descriptions of princesses and princes in classical fairy tales. We have observed that the representations are connected to socially hegemonic ideals of masculinity and femininity. Some resistance appears in the textual productions of the boys. The girls seem to conform to gender norms as ideal and desirable for their personal identities.

Multi-Frequency Polarimetric SAR Classification Based on Riemannian Manifold and Simultaneous Sparse Representation

Directory of Open Access Journals (Sweden)

Fan Yang

2015-07-01

Full Text Available Normally, polarimetric SAR classification is a high-dimensional nonlinear mapping problem. In the realm of pattern recognition, sparse representation is a very efficacious and powerful approach. As classical descriptors of polarimetric SAR, covariance and coherency matrices are Hermitian semidefinite and form a Riemannian manifold. Conventional Euclidean metrics are not suitable for a Riemannian manifold, and hence, normal sparse representation classification cannot be applied to polarimetric SAR directly. This paper proposes a new land cover classification approach for polarimetric SAR. There are two principal novelties in this paper. First, a Stein kernel on a Riemannian manifold instead of Euclidean metrics, combined with sparse representation, is employed for polarimetric SAR land cover classification. This approach is named Stein-sparse representation-based classification (SRC. Second, using simultaneous sparse representation and reasonable assumptions of the correlation of representation among different frequency bands, Stein-SRC is generalized to simultaneous Stein-SRC for multi-frequency polarimetric SAR classification. These classifiers are assessed using polarimetric SAR images from the Airborne Synthetic Aperture Radar (AIRSAR sensor of the Jet Propulsion Laboratory (JPL and the Electromagnetics Institute Synthetic Aperture Radar (EMISAR sensor of the Technical University of Denmark (DTU. Experiments on single-band and multi-band data both show that these approaches acquire more accurate classification results in comparison to many conventional and advanced classifiers.

Perceptual-cognitive changes during motor learning: The influence of mental and physical practice on mental representation, gaze behavior, and performance of a complex action

Directory of Open Access Journals (Sweden)

Cornelia eFrank

2016-01-01

Full Text Available Despite the wealth of research on differences between experts and novices with respect to their perceptual-cognitive background (e.g., mental representations, gaze behavior, little is known about the change of these perceptual-cognitive components over the course of motor learning. In the present study, changes in one’s mental representation, quiet eye behavior, and outcome performance were examined over the course of skill acquisition as it related to physical and mental practice. Novices (N = 45 were assigned to one of three conditions: physical practice, physical practice plus mental practice, and no practice. Participants in the practice groups trained on a golf putting task over the course of three days, either by repeatedly executing the putt, or by both executing and imaging the putt. Findings revealed improvements in putting performance across both practice conditions. Regarding the perceptual-cognitive changes, participants practicing mentally and physically revealed longer quiet eye durations as well as more elaborate representation structures in comparison to the control group, while this was not the case for participants who underwent physical practice only. Thus, in the present study, combined mental and physical practice led to both formation of mental representations in long-term memory and longer quiet eye durations. Interestingly, the length of the quiet eye directly related to the degree of elaborateness of the underlying mental representation, supporting the notion that the quiet eye reflects cognitive processing. This study is the first to show that the quiet eye becomes longer in novices practicing a motor action. Moreover, the findings of the present study suggest that perceptual and cognitive adaptations co-occur over the course of motor learning.

Enhancing students’ mathematical representation and selfefficacy through situation-based learning assisted by geometer’s sketchpad program

Science.gov (United States)

Sowanto; Kusumah, Y. S.

2018-05-01

This research was conducted based on the problem of a lack of students’ mathematical representation ability as well as self-efficacy in accomplishing mathematical tasks. To overcome this problem, this research used situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP). This research investigated students’ improvement of mathematical representation ability who were taught under situation-based learning (SBL) assisted by geometer’s sketchpad program (GSP) and regular method that viewed from the whole students’ prior knowledge (high, average, and low level). In addition, this research investigated the difference of students’ self-efficacy after learning was given. This research belongs to quasi experiment research using non-equivalent control group design with purposive sampling. The result of this research showed that students’ enhancement in their mathematical representation ability taught under SBL assisted by GSP was better than the regular method. Also, there was no interaction between learning methods and students prior knowledge in student’ enhancement of mathematical representation ability. There was significant difference of students’ enhancement of mathematical representation ability taught under SBL assisted by GSP viewed from students’ prior knowledge. Furthermore, there was no significant difference in terms of self-efficacy between those who were taught by SBL assisted by GSP with the regular method.

Specialization of the left supramarginal gyrus for hand-independent praxis representation is not related to hand dominance

Science.gov (United States)

Króliczak, Gregory; Piper, Brian J.; Frey, Scott H.

2016-01-01

Data from focal brain injury and functional neuroimaging studies implicate a distributed network of parieto-fronto-temporal areas in the human left cerebral hemisphere as playing distinct roles in the representation of meaningful actions (praxis). Because these data come primarily from right-handed individuals, the relationship between left cerebral specialization for praxis representation and hand dominance remains unclear. We used functional magnetic resonance imaging (fMRI) to evaluate the hypothesis that strongly left-handed (right hemisphere motor dominant) adults also exhibit this left cerebral specialization. Participants planned familiar actions for subsequent performance with the left or right hand in response to transitive (e.g., “pounding”) or intransitive (e.g. “waving”) action words. In linguistic control trials, cues denoted non-physical actions (e.g., “believing”). Action planning was associated with significant, exclusively left-lateralized and extensive increases of activity in the supramarginal gyrus (SMg), and more focal modulations in the left caudal middle temporal gyrus (cMTg). This activity was hand- and gesture-independent, i.e., unaffected by the hand involved in subsequent action performance, and the type of gesture (i.e., transitive or intransitive). Compared directly with right-handers, left-handers exhibited greater involvement of the right angular gyrus (ANg) and dorsal premotor cortex (dPMC), which is indicative of a less asymmetric functional architecture for praxis representation. We therefore conclude that the organization of mechanisms involved in planning familiar actions is influenced by one’s motor dominance. However, independent of hand dominance, the left SMg and cMTg are specialized for ideomotor transformations—the integration of conceptual knowledge and motor representations into meaningful actions. These findings support the view that higher-order praxis representation and lower-level motor dominance rely

Spontaneous Action Representation in Smokers when Watching Movie Characters Smoke

OpenAIRE

Wagner, Dylan D.; Cin, Sonya Dal; Sargent, James D.; Kelley, William M.; Heatherton, Todd F.

2011-01-01

Do smokers simulate smoking when they see someone else smoke? For regular smokers, smoking is such a highly practiced motor skill that it often occurs automatically, without conscious awareness. Research on the brain basis of action observation has delineated a frontopareital network that is commonly recruited when people observe, plan or imitate actions. Here, we investigated whether this action observation network would be preferentially recruited in smokers when viewing complex smoking cue...

Democratization or asymmetry of representation: notes on State Councils for Food and Nutrition Safety

Directory of Open Access Journals (Sweden)

Joana Tereza Vaz de Moura

2010-05-01

Full Text Available Councils are a key institutional innovation within the Brazilian post-1988 constitutional framework. They are structured so as to include representatives of civil society and the State within the same arena. The aim of this article is to engage in critical discussion on the representation of social organizations within these arenas. Our hypothesis suggests that representatives often distance themselves so much from their social base that they actually become a sort of elite. Thus, we raise the issue of whether the formal democratic structure and mechanisms that these councils incorporate are enough to guarantee a diversity of representatives and representational practices, or if, through the social and political resources that representatives hold, gaps between constituents’ demands and representatives’ actions re-emerge, notwithstanding the normative precepts of equality that the councils themselves advocate. Keywords: councils, elites, representation.

Facial expression recognition based on weber local descriptor and sparse representation

Science.gov (United States)

Ouyang, Yan

2018-03-01

Automatic facial expression recognition has been one of the research hotspots in the area of computer vision for nearly ten years. During the decade, many state-of-the-art methods have been proposed which perform very high accurate rate based on the face images without any interference. Nowadays, many researchers begin to challenge the task of classifying the facial expression images with corruptions and occlusions and the Sparse Representation based Classification framework has been wildly used because it can robust to the corruptions and occlusions. Therefore, this paper proposed a novel facial expression recognition method based on Weber local descriptor (WLD) and Sparse representation. The method includes three parts: firstly the face images are divided into many local patches, and then the WLD histograms of each patch are extracted, finally all the WLD histograms features are composed into a vector and combined with SRC to classify the facial expressions. The experiment results on the Cohn-Kanade database show that the proposed method is robust to occlusions and corruptions.

Representation Discovery using Harmonic Analysis

CERN Document Server

Mahadevan, Sridhar

2008-01-01

Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particu

Social representations of climate change

International Nuclear Information System (INIS)

BOY, D.

2013-01-01

Each year since 2000, the French 'ADEME' (Agency for Environment and Energy Management) conducts a survey on the social representations of greenhouse effect and global warming. This survey is administered by telephone to a representative sample of the French population. The information gathered in the database can answer a series of basic questions concerning public perception in this area. What do the concepts of 'greenhouse effect' and 'global warming' mean for the public? To what extent do people think there is a consensus among scientists to explain these phenomena? Is responsibility for human action clearly established? What kind of solutions, based on public regulation or private initiative can help to remedy this situation? Finally, what were the major changes in public opinion over this 12 years period? (author)

Emergent Intentionality in Perception-Action Subsumption Hierarchies

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David Windridge

2017-08-01

Full Text Available A cognitively autonomous artificial agent may be defined as one able to modify both its external world-model and the framework by which it represents the world, requiring two simultaneous optimization objectives. This presents deep epistemological issues centered on the question of how a framework for representation (as opposed to the entities it represents may be objectively validated. In this article, formalizing previous work in this field, it is argued that subsumptive perception-action learning has the capacity to resolve these issues by (a building the perceptual hierarchy from the bottom up so as to ground all proposed representations and (b maintaining a bijective coupling between proposed percepts and projected action possibilities to ensure empirical falsifiability of these grounded representations. In doing so, we will show that such subsumptive perception-action learners intrinsically incorporate a model for how intentionality emerges from randomized exploratory activity in the form of “motor babbling.” Moreover, such a model of intentionality also naturally translates into a model for human–computer interfacing that makes minimal assumptions as to cognitive states.

Everyday representations of young people about peripheral areas.

Science.gov (United States)

Oliveira, Elda de; Soares, Cassia Baldini; Batista, Leandro Leonardo

2016-01-01

to understand everyday representations of young people about the peripheral areas, with the purpose of establishing topics to drug education media programs. Marxist approach, with emancipatory action research and the participation in workshops of 13 youngsters from a public school of the peripheral area of São Paulo. there are contradictory everyday representations about the State's role, which, on the one hand, does not guarantee social rights and exert social control over the peripheral areas and, on the other hand, is considered the privileged interlocutor for the improvement of life and work conditions. the action research discussed mainly topics related to social rights context, claim of the young participants. It is necessary to expand the discussion beyond the citizenship rights sphere, which is only part of the debate about social inequalities inherent in capitalist exploitation and the necessary transformations to build equality policies.

Understanding representations in design

DEFF Research Database (Denmark)

Bødker, Susanne

1998-01-01

Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work situations...... and computer applications. It suggests that representations are primarily containers of ideas and that representation is situated at the same time as representations are crossing boundaries between various design and use activities. As such, representations should be carriers of their own contexts regarding...

Reactor Emergency Action Level Monitor

International Nuclear Information System (INIS)

Touchton, R.A.

1987-01-01

The Reactor Emergency Action Level Monitor (REALM) Expert System is designed to provide assistance in the identification of a nuclear power plant emergency situation and the determination of its severity. REALM has been developed to operate in a real-time processing environment. REALM embodies a hybrid architecture utilizing both rule-based reasoning and object-oriented programming techniques borrowed from the Artificial Intelligence discipline of Computer Sciences. The rulebase consists of event-based rules and symptom-based rules. The symptom-based rules go beyond the current EAL structure to address the more problematic scenarios and entail a more symbolic representation of the plant information. The results to date have been encouraging that expert system technology can provide improved emergency decision-making capability in nuclear power plants

A kernel-based multi-feature image representation for histopathology image classification

International Nuclear Information System (INIS)

Moreno J; Caicedo J Gonzalez F

2010-01-01

This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of latent semantic analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, support vector machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that; the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

A KERNEL-BASED MULTI-FEATURE IMAGE REPRESENTATION FOR HISTOPATHOLOGY IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

J Carlos Moreno

2010-09-01

Full Text Available This paper presents a novel strategy for building a high-dimensional feature space to represent histopathology image contents. Histogram features, related to colors, textures and edges, are combined together in a unique image representation space using kernel functions. This feature space is further enhanced by the application of Latent Semantic Analysis, to model hidden relationships among visual patterns. All that information is included in the new image representation space. Then, Support Vector Machine classifiers are used to assign semantic labels to images. Processing and classification algorithms operate on top of kernel functions, so that, the structure of the feature space is completely controlled using similarity measures and a dual representation. The proposed approach has shown a successful performance in a classification task using a dataset with 1,502 real histopathology images in 18 different classes. The results show that our approach for histological image classification obtains an improved average performance of 20.6% when compared to a conventional classification approach based on SVM directly applied to the original kernel.

Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

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Yidong Tang

2016-01-01

Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

Training data representation in a neural based robot position estimation system

International Nuclear Information System (INIS)

Taraglio, S.; Di Fonzo, F.; Burrascano, P.

1997-03-01

The vision subsystem of an autonomous vehicle is studies. It is based on a multi layer perceptron that uses TV images to estimate the position of the vehicle. A comparative study of the effects of output data representation and input data processing is presented and discussed

Human Behaviour Representation in Constructive Modelling (Representation du comportement humain dans des modelisations creatives)

Science.gov (United States)

2009-09-01

Resources and Performance. Action Group 19. Representation of Human Behavior. Lanchester , F. W. (1916). Aircraft in warfare . The dawn of the fourth...Operations and non-kinetic warfare . The second keynote presentation, by Mr. Mike Greenley, CAE Inc. provided an industry perspective, noting the need for...concentrated on tactical-conventional warfare and the emergence of world-wide “irregular warfare ” and “small wars” drive the present and future need

Science Divulgation: The Social Representations of Brazilian Researchers Working in the Field of Astronomy

Science.gov (United States)

Carneiro, Dalira Lúcia Cunha Maradei; Longhini, Marcos Daniel

2015-12-01

This article addresses the role of scientific divulgation in the interaction between science and society, debating the importance of Astronomy as a prime starter of the scientific divulgation. In the light of Moscovici’s Social Representations Theory, the social representations on scientific divulgation of Brazilian researchers that work in the field of Astronomy are studied. Individuals from different educational trajectories ansewered semi-structured interviews, which were analyzed according to Spink. The results indicate two representations: one for the society at large, moved by passion, based on values and beliefs, and on the satisfaction of seeing the results of their actions on people’s life; and another for their peers. In the first representation, gaps that obstruct the science divulgation emerge, such as the lack of training and the difficulty to use a plain language, the bureaucracy required for the projects’ execution and its negative representation in the media. Other inferences are that Astronomy is neither part of a systematic teaching nor a part of the media at large, and it often presents conceptual mistakes. Those representations find an echo in the theoretical framework, showing that, despite their advances, scientific divulgation and Astronomy Education are in a context of social fragility.

Emotional Actions Are Coded Via Two Mechanisms: With And Without Identity

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Joanna eWincenciak

2016-05-01

Full Text Available Accurate perception of an individual’s identity and emotion derived from their actions and behavior is essential for successful social functioning. Here we determined the role of identity in the representation of emotional whole-body actions using visual adaptation paradigms. Participants adapted to actors performing different whole-body actions in a happy and sad fashion. Following adaptation subsequent neutral actions appeared to convey the opposite emotion. We demonstrate two different emotional action aftereffects showing distinctive adaptation characteristics. For one short-lived aftereffect, adaptation to the emotion expressed by an individual resulted in biases in the perception of the expression of emotion by other individuals, indicating an identity-independent representation of emotional actions. A second, longer lasting, aftereffect was observed where adaptation to the emotion expressed by an individual resulted in longer-term biases in the perception of the expressions of emotion only by the same individual; this indicated an additional identity-dependent representation of emotional actions. Together, the presence of these two aftereffects indicates the existence of two mechanisms for coding emotional actions, only one of which takes into account the actor’s identity. The results that we observe might parallel processing of emotion from face and voice.

Value representations: a value based dialogue tool

DEFF Research Database (Denmark)

Petersen, Marianne Graves; Rasmussen, Majken Kirkegaard

2011-01-01

Stereotypic presumptions about gender affect the design process, both in relation to how users are understood and how products are designed. As a way to decrease the influence of stereotypic presumptions in design process, we propose not to disregard the aspect of gender in the design process......, as the perspective brings valuable insights on different approaches to technology, but instead to view gender through a value lens. Contributing to this perspective, we have developed Value Representations as a design-oriented instrument for staging a reflective dialogue with users. Value Representations...

Studies on representation of the Lorentz group and gauge theory

International Nuclear Information System (INIS)

Hanitriarivo, R.

2002-01-01

This work is focused on studies about the representation of the Lorentz group and gauge theory. The mathematical tools required for the different studies are presented, as well as for the representation of the Lorentz group and for the gauge theory. Representation of the Lorentz group gives the possible types of fields and wave functions that describe particles: fermions are described by spinors and bosons are described by scalar or vector. Each of these entities (spinors, scalars, vectors) are characterized by their behavior under the action of Lorentz transformations.Gauge theory is used to describe the interactions between particles. [fr

Action understanding as inverse planning.

Science.gov (United States)

Baker, Chris L; Saxe, Rebecca; Tenenbaum, Joshua B

2009-12-01

Humans are adept at inferring the mental states underlying other agents' actions, such as goals, beliefs, desires, emotions and other thoughts. We propose a computational framework based on Bayesian inverse planning for modeling human action understanding. The framework represents an intuitive theory of intentional agents' behavior based on the principle of rationality: the expectation that agents will plan approximately rationally to achieve their goals, given their beliefs about the world. The mental states that caused an agent's behavior are inferred by inverting this model of rational planning using Bayesian inference, integrating the likelihood of the observed actions with the prior over mental states. This approach formalizes in precise probabilistic terms the essence of previous qualitative approaches to action understanding based on an "intentional stance" [Dennett, D. C. (1987). The intentional stance. Cambridge, MA: MIT Press] or a "teleological stance" [Gergely, G., Nádasdy, Z., Csibra, G., & Biró, S. (1995). Taking the intentional stance at 12 months of age. Cognition, 56, 165-193]. In three psychophysical experiments using animated stimuli of agents moving in simple mazes, we assess how well different inverse planning models based on different goal priors can predict human goal inferences. The results provide quantitative evidence for an approximately rational inference mechanism in human goal inference within our simplified stimulus paradigm, and for the flexible nature of goal representations that human observers can adopt. We discuss the implications of our experimental results for human action understanding in real-world contexts, and suggest how our framework might be extended to capture other kinds of mental state inferences, such as inferences about beliefs, or inferring whether an entity is an intentional agent.

SAR and Infrared Image Fusion in Complex Contourlet Domain Based on Joint Sparse Representation

Directory of Open Access Journals (Sweden)

Wu Yiquan

2017-08-01

Full Text Available To investigate the problems of the large grayscale difference between infrared and Synthetic Aperture Radar (SAR images and their fusion image not being fit for human visual perception, we propose a fusion method for SAR and infrared images in the complex contourlet domain based on joint sparse representation. First, we perform complex contourlet decomposition of the infrared and SAR images. Then, we employ the KSingular Value Decomposition (K-SVD method to obtain an over-complete dictionary of the low-frequency components of the two source images. Using a joint sparse representation model, we then generate a joint dictionary. We obtain the sparse representation coefficients of the low-frequency components of the source images in the joint dictionary by the Orthogonal Matching Pursuit (OMP method and select them using the selection maximization strategy. We then reconstruct these components to obtain the fused low-frequency components and fuse the high-frequency components using two criteria——the coefficient of visual sensitivity and the degree of energy matching. Finally, we obtain the fusion image by the inverse complex contourlet transform. Compared with the three classical fusion methods and recently presented fusion methods, e.g., that based on the Non-Subsampled Contourlet Transform (NSCT and another based on sparse representation, the method we propose in this paper can effectively highlight the salient features of the two source images and inherit their information to the greatest extent.

The Role of Familiarity for Representations in Norm-Based Face Space.

Science.gov (United States)

Faerber, Stella J; Kaufmann, Jürgen M; Leder, Helmut; Martin, Eva Maria; Schweinberger, Stefan R

2016-01-01

According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

The Role of Familiarity for Representations in Norm-Based Face Space.

Directory of Open Access Journals (Sweden)

Stella J Faerber

Full Text Available According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991, any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face should be equidistant to a hypothetical prototype face (norm, such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV, and distinctiveness (face in the crowd: FITC for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV. In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1 that familiarity needs to be considered in studies of mental representations of faces, and (2 that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations.

Improving Conceptual Understanding and Representation Skills Through Excel-Based Modeling

Science.gov (United States)

Malone, Kathy L.; Schunn, Christian D.; Schuchardt, Anita M.

2018-02-01

The National Research Council framework for science education and the Next Generation Science Standards have developed a need for additional research and development of curricula that is both technologically model-based and includes engineering practices. This is especially the case for biology education. This paper describes a quasi-experimental design study to test the effectiveness of a model-based curriculum focused on the concepts of natural selection and population ecology that makes use of Excel modeling tools (Modeling Instruction in Biology with Excel, MBI-E). The curriculum revolves around the bio-engineering practice of controlling an invasive species. The study takes place in the Midwest within ten high schools teaching a regular-level introductory biology class. A post-test was designed that targeted a number of common misconceptions in both concept areas as well as representational usage. The results of a post-test demonstrate that the MBI-E students significantly outperformed the traditional classes in both natural selection and population ecology concepts, thus overcoming a number of misconceptions. In addition, implementing students made use of more multiple representations as well as demonstrating greater fascination for science.

Influence of verbal instructions on effect-based action control.

Science.gov (United States)

Eder, Andreas B; Dignath, David

2017-03-01

According to ideomotor theory, people use bidirectional associations between movements and their effects for action selection and initiation. Our experiments examined how verbal instructions of action effects influence response selection without prior experience of action effects in a separate acquisition phase. Instructions for different groups of participants specified whether they should ignore, attend, learn, or intentionally produce acoustic effects produced by button presses. Results showed that explicit instructions of action-effect relations trigger effect-congruent action tendencies in the first trials following the instruction; in contrast, no evidence for effect-based action control was observed in these trials when instructions were to ignore or to attend to the action effects. These findings show that action-effect knowledge acquired through verbal instruction and direct experience is similarly effective for effect-based action control as long as the relation between the movement and the effect is clearly spelled out in the instruction.

On a microscopic representation of space-time

International Nuclear Information System (INIS)

Dahm, R.

2012-01-01

We start from a noncompact Lie algebra isomorphic to the Dirac algebra and relate this Lie algebra in a brief review to low-energy hadron physics described by the compact group SU(4). This step permits an overall physical identification of the operator actions. Then we discuss the geometrical origin of this noncompact Lie algebra and “reduce” the geometry in order to introduce in each of these steps coordinate definitions which can be related to an algebraic representation in terms of the spontaneous symmetry breakdown along the Lie algebra chain su*(4) → usp(4) → su(2) × u(1). Standard techniques of Lie algebra decomposition(s) as well as the (physical) operator identification give rise to interesting physical aspects and lead to a rank-1 Riemannian space which provides an analytic representation and leads to a 5-dimensional hyperbolic space H 5 with SO(5, 1) isometries. The action of the (compact) symplectic group decomposes this (globally) hyperbolic space into H 2 ⊕ H 3 with SO(2, 1) and SO(3, 1) isometries, respectively, which we relate to electromagnetic (dynamically broken SU(2) isospin) and Lorentz transformations. Last not least, we attribute this symmetry pattern to the algebraic representation of a projective geometry over the division algebra H and subsequent coordinate restrictions.

Introduction: evidence-based action in humanitarian crises

NARCIS (Netherlands)

Dijkzeul, D.; Hilhorst, D.; Walker, P.

2013-01-01

This introductory paper sets the stage for this special issue of Disasters on evidence-based action in humanitarian crises. It reviews definition(s) of evidence and it examines the different disciplinary and methodological approaches to collecting and analysing evidence. In humanitarian action, the

A knowledge representation meta-model for rule-based modelling of signalling networks

Directory of Open Access Journals (Sweden)

Adrien Basso-Blandin

2016-03-01

Full Text Available The study of cellular signalling pathways and their deregulation in disease states, such as cancer, is a large and extremely complex task. Indeed, these systems involve many parts and processes but are studied piecewise and their literatures and data are consequently fragmented, distributed and sometimes—at least apparently—inconsistent. This makes it extremely difficult to build significant explanatory models with the result that effects in these systems that are brought about by many interacting factors are poorly understood. The rule-based approach to modelling has shown some promise for the representation of the highly combinatorial systems typically found in signalling where many of the proteins are composed of multiple binding domains, capable of simultaneous interactions, and/or peptide motifs controlled by post-translational modifications. However, the rule-based approach requires highly detailed information about the precise conditions for each and every interaction which is rarely available from any one single source. Rather, these conditions must be painstakingly inferred and curated, by hand, from information contained in many papers—each of which contains only part of the story. In this paper, we introduce a graph-based meta-model, attuned to the representation of cellular signalling networks, which aims to ease this massive cognitive burden on the rule-based curation process. This meta-model is a generalization of that used by Kappa and BNGL which allows for the flexible representation of knowledge at various levels of granularity. In particular, it allows us to deal with information which has either too little, or too much, detail with respect to the strict rule-based meta-model. Our approach provides a basis for the gradual aggregation of fragmented biological knowledge extracted from the literature into an instance of the meta-model from which we can define an automated translation into executable Kappa programs.

Towards peer education prevention of school dropout: An exploratory analysis of an action-research study

Directory of Open Access Journals (Sweden)

Colucci Gabriella

2017-01-01

Full Text Available This paper presents the exploratory analysis of an action-research into dropout prevention in an Italian secondary school. By taking into account the representations of teachers, students and parents, different activities of peer education have been implemented during the school year in a city of Sardinia in order to promote school success. The study is based on a mixed-methods design, including focus groups with teachers, students and parents, as well as classroom observations. The action-research consists of different interventions: firstly, the participants’ representations of school dropout have been collected; then, a specific program of peer education has been proposed through activities of role-playing, simulations, brainstorming, and improvement of life skills (during training meetings with the participants. Thereafter, the action-research has been qualitatively analysed, with the findings indicating possible directions of re-creating school practices that could have potential benefits in preventing dropout.

Example-Based Image Colorization Using Locality Consistent Sparse Representation.

Science.gov (United States)

Bo Li; Fuchen Zhao; Zhuo Su; Xiangguo Liang; Yu-Kun Lai; Rosin, Paul L

2017-11-01

Image colorization aims to produce a natural looking color image from a given gray-scale image, which remains a challenging problem. In this paper, we propose a novel example-based image colorization method exploiting a new locality consistent sparse representation. Given a single reference color image, our method automatically colorizes the target gray-scale image by sparse pursuit. For efficiency and robustness, our method operates at the superpixel level. We extract low-level intensity features, mid-level texture features, and high-level semantic features for each superpixel, which are then concatenated to form its descriptor. The collection of feature vectors for all the superpixels from the reference image composes the dictionary. We formulate colorization of target superpixels as a dictionary-based sparse reconstruction problem. Inspired by the observation that superpixels with similar spatial location and/or feature representation are likely to match spatially close regions from the reference image, we further introduce a locality promoting regularization term into the energy formulation, which substantially improves the matching consistency and subsequent colorization results. Target superpixels are colorized based on the chrominance information from the dominant reference superpixels. Finally, to further improve coherence while preserving sharpness, we develop a new edge-preserving filter for chrominance channels with the guidance from the target gray-scale image. To the best of our knowledge, this is the first work on sparse pursuit image colorization from single reference images. Experimental results demonstrate that our colorization method outperforms the state-of-the-art methods, both visually and quantitatively using a user study.

Risk, responsibility and political action

DEFF Research Database (Denmark)

Halskov Jensen, Elisabeth

2004-01-01

action was transformed into a moral respon-sibility on the part of the national and European politicians, constrained by economic and technical-scientific reality and represented as taking place only in the public sphere. KEY WORDS: CDA, World Risk Society, argumentation, media discourse, argumentation......ABSTRACT. This paper presents an argumentative case study of the discursive representation of risk, responsibility and political action in the Spanish media. The study uses a critical discourse analytical approach combined with theories on risk, agency and political communication in the media....... It is argued that an application of the Toulmin model is useful for eliciting systematic overall repre-sentations of responsibility and agency in environmental crises such as the mad cow crisis as well as for revealing relationships between social domains such as moral, politics, economics and science...

The Representation of Action Plans in Long Term Memory

Science.gov (United States)

Fussfeld, G. N.; Koenig, W.; Karis, D.

1984-01-01

A sequence of experiments conducted on a two hand chord typewriter, to compare the efficiency of different coding principles employed to associate letters with their chord productions is described. This keyboard represents an effort to identify effective alternatives to the existing typewriter. It consists of two seperate 5-key panels (one for each hand), and letters are entered by typing chords composed of one to five fingers. Each panel is capable of producing the full alphabet. One group of experiments was designed to separate between perceptual and motor factors in the acivation of single letter chords. The results underline the importance of perceptual factors in the activation of motor plans. The complexity of the patterns employed to represent letters was shown to account for 50 percent of variance in the typing speeds of single letters. The theoretical implications of these results are discussed in relation to a vision based theory of action plans.

[The fragmentation of representational space in schizophrenia].

Science.gov (United States)

Plagnol, A; Oïta, M; Montreuil, M; Granger, B; Lubart, T

2003-01-01

Existent neurocognitive models of schizophrenia converge towards a core of impairments involving working memory, context processing, action planning, controlled and intentional processing. However, the emergence of this core remains itself difficult to explain and more specific hypotheses do not explain the heterogeneity of schizophrenia. To overcome these limits, we propose a new paradigm based on representational theory from cognitive science. Some recent developments of this theory enable us to describe a subjective universe as a representational space which is displayed from memory. We outline a conceptual framework to construct such a representational space from analogical -representations that can be activated in working memory and are connected to a network of symbolic structures. These connections are notably made through an analytic process of the analogical fragments, which involves the attentional focus. This framework allows us to define rigorously some defense processes in response to traumatic tensions that are expressed on the representational space. The fragmentation of representational space is a consequence of a defensive denial based on an impairment of the analytic process. The fragmentation forms some parasitic areas in memory which are excluded from the main part of the representational space and disturb information processing. The key clinical concepts of paranoid syndromes can be defined in this conceptual framework: mental automatism, delusional intuition, acute destructuration, psychotic dissociation, and autistic withdrawal. We show that these syndromes imply each other, which in return increases the fragmentation of the representational space. Some new concepts emerge naturally in this framework, such as the concept of "suture" which is defined as a link between a parasitic area and the main representational space. Schizophrenia appears as a borderline case of fragmentation of the representational space. This conceptual framework is

Attention-spreading based on hierarchical spatial representations for connected objects.

Science.gov (United States)

Kasai, Tetsuko

2010-01-01

Attention selects objects or groups as the most fundamental unit, and this may be achieved through a process in which attention automatically spreads throughout their entire region. Previously, we found that a lateralized potential relative to an attended hemifield at occipito-temporal electrode sites reflects attention-spreading in response to connected bilateral stimuli [Kasai, T., & Kondo, M. Electrophysiological correlates of attention-spreading in visual grouping. NeuroReport, 18, 93-98, 2007]. The present study examined the nature of object representations by manipulating the extent of grouping through connectedness, while controlling the symmetrical structure of bilateral stimuli. The electrophysiological results of two experiments consistently indicated that attention was guided twice in association with perceptual grouping in the early phase (N1, 150-200 msec poststimulus) and with the unity of an object in the later phase (N2pc, 310/330-390 msec). This suggests that there are two processes in object-based spatial selection, and these are discussed with regard to their cognitive mechanisms and object representations.

Fourier transform methods for calculating action variables and semiclassical eigenvalues for coupled oscillator systems

International Nuclear Information System (INIS)

Eaker, C.W.; Schatz, G.C.; De Leon, N.; Heller, E.J.

1984-01-01

Two methods for calculating the good action variables and semiclassical eigenvalues for coupled oscillator systems are presented, both of which relate the actions to the coefficients appearing in the Fourier representation of the normal coordinates and momenta. The two methods differ in that one is based on the exact expression for the actions together with the EBK semiclassical quantization condition while the other is derived from the Sorbie--Handy (SH) approximation to the actions. However, they are also very similar in that the actions in both methods are related to the same set of Fourier coefficients and both require determining the perturbed frequencies in calculating actions. These frequencies are also determined from the Fourier representations, which means that the actions in both methods are determined from information entirely contained in the Fourier expansion of the coordinates and momenta. We show how these expansions can very conveniently be obtained from fast Fourier transform (FFT) methods and that numerical filtering methods can be used to remove spurious Fourier components associated with the finite trajectory integration duration. In the case of the SH based method, we find that the use of filtering enables us to relax the usual periodicity requirement on the calculated trajectory. Application to two standard Henon--Heiles models is considered and both are shown to give semiclassical eigenvalues in good agreement with previous calculations for nondegenerate and 1:1 resonant systems. In comparing the two methods, we find that although the exact method is quite general in its ability to be used for systems exhibiting complex resonant behavior, it converges more slowly with increasing trajectory integration duration and is more sensitive to the algorithm for choosing perturbed frequencies than the SH based method

Tensor and Spin Representations of SO(4) and Discrete Quantum Gravity

Science.gov (United States)

Lorente, M.; Kramer, P.

Starting from the defining transformations of complex matrices for the SO(4) group, we construct the fundamental representation and the tensor and spinor representations of the group SO(4). Given the commutation relations for the corresponding algebra, the unitary representations of the group in terms of the generalized Euler angles are constructed. These mathematical results help us to a more complete description of the Barret-Crane model in Quantum Gravity. In particular a complete realization of the weight function for the partition function is given and a new geometrical interpretation of the asymptotic limit for the Regge action is presented.

Modeling and representation of a computer-aided conceptual design system

Energy Technology Data Exchange (ETDEWEB)

Li, Bing; Zhang, Ju Fan [Harbin Institute of Technology, Shenzhen (China); Chen, Yuan [Shandong Univ. at Weihai, Weihai (China); Hu, Ying [The Chinese Univ. of Hong Kong, Hong Kong (China)

2012-11-15

A novel hierarchical function action behavior mechanism (FABM) modeling framework is proposed to conduct intelligent mapping from the overall function to the principle solution, according to the requirements of customers. Based on the hierarchical modeling framework, an object oriented representation method is developed to express the inheritance and the interconnecting characteristics between any two objects. In addition, the rules of expansion and modification in demand behavior are proposed to solve the combinational explosion problem, and the combinational rules in the mechanism behavior are developed to extend the innovation of the principle solution. A case study on the pan mechanism design for a cooking robot is presented to demonstrate the implementation of intelligent reasoning based on the FABM model.

Modeling and representation of a computer-aided conceptual design system

International Nuclear Information System (INIS)

Li, Bing; Zhang, Ju Fan; Chen, Yuan; Hu, Ying

2012-01-01

A novel hierarchical function action behavior mechanism (FABM) modeling framework is proposed to conduct intelligent mapping from the overall function to the principle solution, according to the requirements of customers. Based on the hierarchical modeling framework, an object oriented representation method is developed to express the inheritance and the interconnecting characteristics between any two objects. In addition, the rules of expansion and modification in demand behavior are proposed to solve the combinational explosion problem, and the combinational rules in the mechanism behavior are developed to extend the innovation of the principle solution. A case study on the pan mechanism design for a cooking robot is presented to demonstrate the implementation of intelligent reasoning based on the FABM model

Representations of coherent states in non-orthogonal bases

International Nuclear Information System (INIS)

Ali, S Twareque; Roknizadeh, R; Tavassoly, M K

2004-01-01

Starting with the canonical coherent states, we demonstrate that all the so-called nonlinear coherent states, used in the physical literature, as well as large classes of other generalized coherent states, can be obtained by changes of bases in the underlying Hilbert space. This observation leads to an interesting duality between pairs of generalized coherent states, bringing into play a Gelfand triple of (rigged) Hilbert spaces. Moreover, it is shown that in each dual pair of families of nonlinear coherent states, at least one family is related to a (generally) non-unitary projective representation of the Weyl-Heisenberg group, which can then be thought of as characterizing the dual pair

Bridging the Gap: Possible Roles and Contributions of Representational Momentum

Directory of Open Access Journals (Sweden)

Timothy L. Hubbard

2006-01-01

Full Text Available Memory for the position of a moving target is often displaced in the direction of anticipated motion, and this has been referred to as representational momentum. Such displacement might aid spatial localization by bridging the gap between perception and action, and might reflect a second-order isomorphism between subjective consequences of environmentally invariant physical principles and the functional architecture of mental representation that can be modulated by an observer’s expectations (e.g., that a moving target will change its heading or by the presence of nontarget stimuli (e.g., landmarks. Representational momentum and related types of displacement reflect properties of the world and properties of mental representation, and so a consideration of representational momentum and related types of displacement contribute an important component of contemporary psychophysics, and also broaden the reach of psychophysics to include numerous topics not usually considered within psychophysics (e.g., naive physics, boundary extension, flash-lag effect, aesthetics, mental imagery.

Processes and Reasoning in Representations of Linear Functions

Science.gov (United States)

Adu-Gyamfi, Kwaku; Bossé, Michael J.

2014-01-01

This study examined student actions, interpretations, and language in respect to questions raised regarding tabular, graphical, and algebraic representations in the context of functions. The purpose was to investigate students' interpretations and specific ways of working within table, graph, and the algebraic on notions fundamental to a…

Spatial Working Memory Is Necessary for Actions to Guide Thought

Science.gov (United States)

Thomas, Laura E.

2013-01-01

Directed actions can play a causal role in cognition, shaping thought processes. What drives this cross-talk between action and thought? I investigated the hypothesis that representations in spatial working memory mediate interactions between directed actions and problem solving. Participants attempted to solve an insight problem while…

Adaboost-based algorithm for human action recognition

KAUST Repository

Zerrouki, Nabil

2017-11-28

This paper presents a computer vision-based methodology for human action recognition. First, the shape based pose features are constructed based on area ratios to identify the human silhouette in images. The proposed features are invariance to translation and scaling. Once the human body features are extracted from videos, different human actions are learned individually on the training frames of each class. Then, we apply the Adaboost algorithm for the classification process. We assessed the proposed approach using the UR Fall Detection dataset. In this study six classes of activities are considered namely: walking, standing, bending, lying, squatting, and sitting. Results demonstrate the efficiency of the proposed methodology.

Adaboost-based algorithm for human action recognition

KAUST Repository

Zerrouki, Nabil; Harrou, Fouzi; Sun, Ying; Houacine, Amrane

2017-01-01

This paper presents a computer vision-based methodology for human action recognition. First, the shape based pose features are constructed based on area ratios to identify the human silhouette in images. The proposed features are invariance to translation and scaling. Once the human body features are extracted from videos, different human actions are learned individually on the training frames of each class. Then, we apply the Adaboost algorithm for the classification process. We assessed the proposed approach using the UR Fall Detection dataset. In this study six classes of activities are considered namely: walking, standing, bending, lying, squatting, and sitting. Results demonstrate the efficiency of the proposed methodology.

Representations of Patients' Experiences of Autonomy in Graphic Medicine.

Science.gov (United States)

Tschaepe, Mark

2018-02-01

I advocate using graphic medicine in introductory medical ethics courses to help trainees learn about patients' experiences of autonomy. Graphic narratives about this content offer trainees opportunities to gain insights into making diagnoses and recommending treatments. Graphic medicine can also illuminate aspects of patients' experiences of autonomy differently than other genres. Specifically, comics allow readers to consider visual and text-based representations of a patient's actions, speech, thoughts, and emotions. Here, I use Ellen Forney's Marbles: Mania, Depression, Michelangelo, and Me: A Graphic Memoir and Peter Dunlap-Shohl's My Degeneration: A Journey Through Parkinson's as two examples that can serve as pedagogical resources. © 2018 American Medical Association. All Rights Reserved.

Top-down attention based on object representation and incremental memory for knowledge building and inference.

Science.gov (United States)

Kim, Bumhwi; Ban, Sang-Woo; Lee, Minho

2013-10-01

Humans can efficiently perceive arbitrary visual objects based on an incremental learning mechanism with selective attention. This paper proposes a new task specific top-down attention model to locate a target object based on its form and color representation along with a bottom-up saliency based on relativity of primitive visual features and some memory modules. In the proposed model top-down bias signals corresponding to the target form and color features are generated, which draw the preferential attention to the desired object by the proposed selective attention model in concomitance with the bottom-up saliency process. The object form and color representation and memory modules have an incremental learning mechanism together with a proper object feature representation scheme. The proposed model includes a Growing Fuzzy Topology Adaptive Resonance Theory (GFTART) network which plays two important roles in object color and form biased attention; one is to incrementally learn and memorize color and form features of various objects, and the other is to generate a top-down bias signal to localize a target object by focusing on the candidate local areas. Moreover, the GFTART network can be utilized for knowledge inference which enables the perception of new unknown objects on the basis of the object form and color features stored in the memory during training. Experimental results show that the proposed model is successful in focusing on the specified target objects, in addition to the incremental representation and memorization of various objects in natural scenes. In addition, the proposed model properly infers new unknown objects based on the form and color features of previously trained objects. Copyright © 2013 Elsevier Ltd. All rights reserved.

Interference, reduced action, and trajectories

OpenAIRE

Floyd, Edward R.

2006-01-01

Instead of investigating the interference between two stationary, rectilinear wave functions in a trajectory representation by examining the two rectilinear wave functions individually, we examine a dichromatic wave function that is synthesized from the two interfering wave functions. The physics of interference is contained in the reduced action for the dichromatic wave function. As this reduced action is a generator of the motion for the dichromatic wave function, it determines the dichroma...

Intelligent Fault Diagnosis of Rotary Machinery Based on Unsupervised Multiscale Representation Learning

Science.gov (United States)

Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun

2017-11-01

The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.

A Knowledge-Based Representation Scheme for Environmental Science Models

Science.gov (United States)

Keller, Richard M.; Dungan, Jennifer L.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

One of the primary methods available for studying environmental phenomena is the construction and analysis of computational models. We have been studying how artificial intelligence techniques can be applied to assist in the development and use of environmental science models within the context of NASA-sponsored activities. We have identified several high-utility areas as potential targets for research and development: model development; data visualization, analysis, and interpretation; model publishing and reuse, training and education; and framing, posing, and answering questions. Central to progress on any of the above areas is a representation for environmental models that contains a great deal more information than is present in a traditional software implementation. In particular, a traditional software implementation is devoid of any semantic information that connects the code with the environmental context that forms the background for the modeling activity. Before we can build AI systems to assist in model development and usage, we must develop a representation for environmental models that adequately describes a model's semantics and explicitly represents the relationship between the code and the modeling task at hand. We have developed one such representation in conjunction with our work on the SIGMA (Scientists' Intelligent Graphical Modeling Assistant) environment. The key feature of the representation is that it provides a semantic grounding for the symbols in a set of modeling equations by linking those symbols to an explicit representation of the underlying environmental scenario.

Highest weight representations of the quantum algebra Uh(gl∞)

International Nuclear Information System (INIS)

Palev, T.D.; Stoilova, N.I.

1997-04-01

A class of highest weight irreducible representations of the quantum algebra U h (gl-∞) is constructed. Within each module a basis is introduced and the transformation relations of the basis under the action of the Chevalley generators are explicitly written. (author). 16 refs

Response actions influence the categorization of directions in auditory space

Directory of Open Access Journals (Sweden)

Marcella de Castro Campos Velten

2015-08-01

Full Text Available Spatial region concepts such as front, back, left and right reflect our typical interaction with space, and the corresponding surrounding regions have different statuses in memory. We examined the representation of spatial directions in the auditory space, specifically in how far natural response actions, such as orientation movements towards a sound source, would affect the categorization of egocentric auditory space. While standing in the middle of a circle with 16 loudspeakers, participants were presented acoustic stimuli coming from the loudspeakers in randomized order, and verbally described their directions by using the concept labels front, back, left, right, front-right, front-left, back-right and back-left. Response actions varied in three blocked conditions: 1 facing front, 2 turning the head and upper body to face the stimulus, and 3 turning the head and upper body plus pointing with the hand and outstretched arm towards the stimulus. In addition to a protocol of the verbal utterances, motion capture and video recording generated a detailed corpus for subsequent analysis of the participants’ behavior. Chi-square tests revealed an effect of response condition for directions within the left and right sides. We conclude that movement-based response actions influence the representation of auditory space, especially within the sides’ regions.

Knowledge Representation in Patient Safety Reporting: An Ontological Approach

Directory of Open Access Journals (Sweden)

Liang Chen

2016-10-01

Full Text Available Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage. Findings: We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement. Research limitations: The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology. Practical implications: The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods. Originality/value: The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

The cognitive nature of action - functional links between cognitive psychology, movement science, and robotics.

Science.gov (United States)

Schack, Thomas; Ritter, Helge

2009-01-01

This paper examines the cognitive architecture of human action, showing how it is organized over several levels and how it is built up. Basic action concepts (BACs) are identified as major building blocks on a representation level. These BACs are cognitive tools for mastering the functional demands of movement tasks. Results from different lines of research showed that not only the structure formation of mental representations in long-term memory but also chunk formation in working memory are built up on BACs and relate systematically to movement structures. It is concluded that such movement representations might provide the basis for action implementation and action control in skilled voluntary movements in the form of cognitive reference structures. To simulate action implementation we discuss challenges and issues that arise when we try to replicate complex movement abilities in robots. Among the key issues to be addressed is the question how structured representations can arise during skill acquisition and how the underlying processes can be understood sufficiently succinctly to replicate them on robot platforms. Working towards this goal, we translate our findings in studies of motor control in humans into models that can guide the implementation of cognitive robot architectures. Focusing on the issue of manual action control, we illustrate some results in the context of grasping with a five-fingered anthropomorphic robot hand.

Relative Contributions of Goal Representation and Kinematic Information to Self-Monitoring by Chimpanzees and Humans

Science.gov (United States)

Kaneko, Takaaki; Tomonaga, Masaki

2012-01-01

It is important to monitor feedback related to the intended result of an action while executing that action. This monitoring process occurs hierarchically; that is, sensorimotor processing occurs at a lower level, and conceptual representation of action goals occurs at a higher level. Although the hierarchical nature of self-monitoring may derive…

Procedural Media Representation

OpenAIRE

Henrysson, Anders

2002-01-01

We present a concept for using procedural techniques to represent media. Procedural methods allow us to represent digital media (2D images, 3D environments etc.) with very little information and to render it photo realistically. Since not all kind of content can be created procedurally, traditional media representations (bitmaps, polygons etc.) must be used as well. We have adopted an object-based media representation where an object can be represented either with a procedure or with its trad...

INVESTIGATING SHAPE REPRESENTATION USING SENSITIVITY TO PART- AND AXIS-BASED TRANSFORMATIONS

OpenAIRE

Denisova, Kristina; Feldman, Jacob; Su, Xiaotao; Singh, Manish

2016-01-01

Part -and axis-based approaches organize shape representations in terms of simple parts and their spatial relationships. Shape transformations that alter qualitative part structure have been shown to be more detectable than those that preserve it. We compared sensitivity to various transformations that change quantitative properties of parts and their spatial relationships, while preserving qualitative part structure. Shape transformations involving changes in length, width, curvature, orient...

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

Directory of Open Access Journals (Sweden)

Makoto Ito

2015-11-01

Full Text Available Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS, the dorsomedial striatum (DMS, and the ventral striatum (VS identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

Parallel Representation of Value-Based and Finite State-Based Strategies in the Ventral and Dorsal Striatum.

Science.gov (United States)

Ito, Makoto; Doya, Kenji

2015-11-01

Previous theoretical studies of animal and human behavioral learning have focused on the dichotomy of the value-based strategy using action value functions to predict rewards and the model-based strategy using internal models to predict environmental states. However, animals and humans often take simple procedural behaviors, such as the "win-stay, lose-switch" strategy without explicit prediction of rewards or states. Here we consider another strategy, the finite state-based strategy, in which a subject selects an action depending on its discrete internal state and updates the state depending on the action chosen and the reward outcome. By analyzing choice behavior of rats in a free-choice task, we found that the finite state-based strategy fitted their behavioral choices more accurately than value-based and model-based strategies did. When fitted models were run autonomously with the same task, only the finite state-based strategy could reproduce the key feature of choice sequences. Analyses of neural activity recorded from the dorsolateral striatum (DLS), the dorsomedial striatum (DMS), and the ventral striatum (VS) identified significant fractions of neurons in all three subareas for which activities were correlated with individual states of the finite state-based strategy. The signal of internal states at the time of choice was found in DMS, and for clusters of states was found in VS. In addition, action values and state values of the value-based strategy were encoded in DMS and VS, respectively. These results suggest that both the value-based strategy and the finite state-based strategy are implemented in the striatum.

Structure-reactivity modeling using mixture-based representation of chemical reactions.

Science.gov (United States)

Polishchuk, Pavel; Madzhidov, Timur; Gimadiev, Timur; Bodrov, Andrey; Nugmanov, Ramil; Varnek, Alexandre

2017-09-01

We describe a novel approach of reaction representation as a combination of two mixtures: a mixture of reactants and a mixture of products. In turn, each mixture can be encoded using an earlier reported approach involving simplex descriptors (SiRMS). The feature vector representing these two mixtures results from either concatenated product and reactant descriptors or the difference between descriptors of products and reactants. This reaction representation doesn't need an explicit labeling of a reaction center. The rigorous "product-out" cross-validation (CV) strategy has been suggested. Unlike the naïve "reaction-out" CV approach based on a random selection of items, the proposed one provides with more realistic estimation of prediction accuracy for reactions resulting in novel products. The new methodology has been applied to model rate constants of E2 reactions. It has been demonstrated that the use of the fragment control domain applicability approach significantly increases prediction accuracy of the models. The models obtained with new "mixture" approach performed better than those required either explicit (Condensed Graph of Reaction) or implicit (reaction fingerprints) reaction center labeling.

Knowledge Representation and Ontologies

Science.gov (United States)

Grimm, Stephan

Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

Uniformly bounded representations of the Lorentz groups

International Nuclear Information System (INIS)

Brega, A.O.

1982-01-01

For the Lorentz group G = SO/sub e/(n + 1, 1)(ngreater than or equal to 2) the author constructs a family of uniformly bounded representations by means of analytically continuing a certain normalization of the unitary principal series. The method the author uses relies on an analysis of various operators under a Mellin transform and extends earlier work of E.N. Wilson. In a series of papers Kunze and Stein initiated the theory of uniformly bounded representations of semisimple Lie groups; the starting point is the unitary principal series T(sigma,s) obtained in a certain subgroup M of G and a purely imaginary number s. From there Kunze and Stein constructed families of representations R(sigma,s) depending analytically on a parameter s in a domain D of C containing the imaginary axis which are unitarily equilvalent to T(sigma,s) for s contained in the set of imaginary numbers and whose operator norms are uniformly bounded for each s in D. In the case of the Lorentz groups SO/sub e/(n + 1, 1)(ngreater than or equal to2) and the trivial representation 1 of M, E.N. Wilson obtained such a family R(1,s) for the domain D = [s contained in the set of C: absolute value Re(s) Vertical Bar2]. For this domain D and for any representation sigma of M the author provides a family R(sigma,s) of uniformly bounded representations analytically continuing T(sigma,s), thereby generalizing Wilson's work. The author has also investigated certain symmetry properties of the representations R(sigma,s) under the action of the Weyl group. The trivial representation is Weyl group invariant and the family R(1,s) obtained by Wilson satisfies R(1,s) = R(1,-s) reflecting this. Obtained was the analogous result R(sigma,s) = R(sigma,-s) for some well known representations sigma that are Weyl group invariant. This involves the explicit computation of certain constants arising in the Fourier transforms of intertwining operators

A survey on vision-based human action recognition

NARCIS (Netherlands)

Poppe, Ronald Walter

Vision-based human action recognition is the process of labeling image sequences with action labels. Robust solutions to this problem have applications in domains such as visual surveillance, video retrieval and human–computer interaction. The task is challenging due to variations in motion

Care for women in domestic violence situation: representations of hospital nurses

Directory of Open Access Journals (Sweden)

Daniele Ferreira Acosta

2017-11-01

Full Text Available Our study aimed to analyze the structure and contents of nurses’ social representations about the care provided to the victim of domestic violence. Nurses from two medium size public hospitals at Rio Grande/RS participated in the study. We collected data through free evocations of the inductor term “care for the victim” and analyzed them by software. The nurses had representations centered in the psychosocial care demonstrated by the terms present in the central nucleus. We inferred the presence of a subgroup in the contrast zone that acknowledges the importance of the physical care, without limiting to the actions of technicians. In the periphery, we inferred the work is evident when facing terms of assistance and orientation. The professionalism reveals the need to address the object, based on the reified knowledge. Because this is a theme with a considered emotional load, added to the hospitalization and the fragility of the victim, the psychosocial focus is more significant in the care context.

Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging

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Xiaodong Zhang

2016-01-01

Full Text Available Segmentation of infarcts at hyperacute stage is challenging as they exhibit substantial variability which may even be hard for experts to delineate manually. In this paper, a sparse representation based classification method is explored. For each patient, four volumetric data items including three volumes of diffusion weighted imaging and a computed asymmetry map are employed to extract patch features which are then fed to dictionary learning and classification based on sparse representation. Elastic net is adopted to replace the traditional L0-norm/L1-norm constraints on sparse representation to stabilize sparse code. To decrease computation cost and to reduce false positives, regions-of-interest are determined to confine candidate infarct voxels. The proposed method has been validated on 98 consecutive patients recruited within 6 hours from onset. It is shown that the proposed method could handle well infarcts with intensity variability and ill-defined edges to yield significantly higher Dice coefficient (0.755 ± 0.118 than the other two methods and their enhanced versions by confining their segmentations within the regions-of-interest (average Dice coefficient less than 0.610. The proposed method could provide a potential tool to quantify infarcts from diffusion weighted imaging at hyperacute stage with accuracy and speed to assist the decision making especially for thrombolytic therapy.

Vietnamese Document Representation and Classification

Science.gov (United States)

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.

Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning

NARCIS (Netherlands)

Miao, Yongwu; Burgos, Daniel; Griffiths, David; Koper, Rob

2007-01-01

Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and

Being present in action: a theoretical model about the interlocking between intentions and environmental affordances

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Stefano eTriberti

2016-01-01

Full Text Available Recent neuropsychological evidence suggest that a key role in linking perceptions and intentions is played by sense of presence. Despite this phenomenon having been studied primarily in the field of virtual reality (conceived as the illusion of being in the virtual space, recent research highlighted that it is a fundamental feature of everyday experience. Specifically, the function of presence as a cognitive process is to locate the Self in a physical space or situation, based on the perceived possibility to act in it; so, the variations in sense of presence allow one to continuously adapt his own action to the external environment. Indeed intentions, as the cognitive antecedents of action, are not static representations of the desired outcomes, but dynamic processes able to adjust their own representational content according to the opportunities/restrictions emerging in the environment. Focusing on the peculiar context of action mediated by interactive technologies, we here propose a theoretical model showing how each level of an intentional hierarchy (future-directed; present directed; and motor intentions can interlock with environmental affordances in order to promote a continuous stream of action and activity.

Viewpoint Manifolds for Action Recognition

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Souvenir Richard

2009-01-01

Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

Unsupervised Learning of Action Primitives

DEFF Research Database (Denmark)

Baby, Sanmohan; Krüger, Volker; Kragic, Danica

2010-01-01

and scale, the use of the object can provide a strong invariant for the detection of motion primitives. In this paper we propose an unsupervised learning approach for action primitives that makes use of the human movements as well as the object state changes. We group actions according to the changes......Action representation is a key issue in imitation learning for humanoids. With the recent finding of mirror neurons there has been a growing interest in expressing actions as a combination meaningful subparts called primitives. Primitives could be thought of as an alphabet for the human actions....... In this paper we observe that human actions and objects can be seen as being intertwined: we can interpret actions from the way the body parts are moving, but as well from how their effect on the involved object. While human movements can look vastly different even under minor changes in location, orientation...

Internal representations for face detection: an application of noise-based image classification to BOLD responses.

Science.gov (United States)

Nestor, Adrian; Vettel, Jean M; Tarr, Michael J

2013-11-01

What basic visual structures underlie human face detection and how can we extract such structures directly from the amplitude of neural responses elicited by face processing? Here, we address these issues by investigating an extension of noise-based image classification to BOLD responses recorded in high-level visual areas. First, we assess the applicability of this classification method to such data and, second, we explore its results in connection with the neural processing of faces. To this end, we construct luminance templates from white noise fields based on the response of face-selective areas in the human ventral cortex. Using behaviorally and neurally-derived classification images, our results reveal a family of simple but robust image structures subserving face representation and detection. Thus, we confirm the role played by classical face selective regions in face detection and we help clarify the representational basis of this perceptual function. From a theory standpoint, our findings support the idea of simple but highly diagnostic neurally-coded features for face detection. At the same time, from a methodological perspective, our work demonstrates the ability of noise-based image classification in conjunction with fMRI to help uncover the structure of high-level perceptual representations. Copyright © 2012 Wiley Periodicals, Inc.

Representations for Supporting Students' Context Awareness

DEFF Research Database (Denmark)

Demetriadis, Stavros N.; Papadopoulos, Pantelis M.

2005-01-01

The context of the specific situation where knowledge is applied affects significantly the problem solving process by forcing people to negotiate and reconsider the priorities of their mental representations and problem solving operators, in relation to this process. In this work we argue...... that students’ context awareness can significantly be enhanced by the use of appropriate external representations which guide them to activate context inducing cognitive processes. By embedding such representations in a case based learning environment we expect to guide students’ processing of the rich...... in contextual information material, in a way that improves both their context awareness and metacontextual competence. After presenting a context model, we discuss the design of such representations based on this model and explain why we expect that their use in a learning situation would enhance context...

Exploring the Structure of Spatial Representations

Science.gov (United States)

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

Experience-driven formation of parts-based representations in a model of layered visual memory

Directory of Open Access Journals (Sweden)

Jenia Jitsev

2009-09-01

Full Text Available Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces.

A Nakanishi-based model illustrating the covariant extension of the pion GPD overlap representation and its ambiguities

Science.gov (United States)

Chouika, N.; Mezrag, C.; Moutarde, H.; Rodríguez-Quintero, J.

2018-05-01

A systematic approach for the model building of Generalized Parton Distributions (GPDs), based on their overlap representation within the DGLAP kinematic region and a further covariant extension to the ERBL one, is applied to the valence-quark pion's case, using light-front wave functions inspired by the Nakanishi representation of the pion Bethe-Salpeter amplitudes (BSA). This simple but fruitful pion GPD model illustrates the general model building technique and, in addition, allows for the ambiguities related to the covariant extension, grounded on the Double Distribution (DD) representation, to be constrained by requiring a soft-pion theorem to be properly observed.

(Self)-representations on youtube

DEFF Research Database (Denmark)

Simonsen, Thomas Mosebo

This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can...... be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how certain forms of representation can be identified as representations of the self (Turkle 1995, Scannell...... 1996, Walker 2005) and further how these forms must be comprehended within a context of technological constrains, institutional structures and social as well as economical practices on YouTube (Burgess and Green 2009, Van Dijck 2009). It is argued that these different contexts play a vital part...

Computability and Representations of the Zero Set

NARCIS (Netherlands)

P.J. Collins (Pieter)

2008-01-01

htmlabstractIn this note we give a new representation for closed sets under which the robust zero set of a function is computable. We call this representation the component cover representation. The computation of the zero set is based on topological index theory, the most powerful tool for finding

Impossibility Theorem in Proportional Representation Problem

International Nuclear Information System (INIS)

Karpov, Alexander

2010-01-01

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).

Metaphysics of the principle of least action

Science.gov (United States)

Terekhovich, Vladislav

2018-05-01

Despite the importance of the variational principles of physics, there have been relatively few attempts to consider them for a realistic framework. In addition to the old teleological question, this paper continues the recent discussion regarding the modal involvement of the principle of least action and its relations with the Humean view of the laws of nature. The reality of possible paths in the principle of least action is examined from the perspectives of the contemporary metaphysics of modality and Leibniz's concept of essences or possibles striving for existence. I elaborate a modal interpretation of the principle of least action that replaces a classical representation of a system's motion along a single history in the actual modality by simultaneous motions along an infinite set of all possible histories in the possible modality. This model is based on an intuition that deep ontological connections exist between the possible paths in the principle of least action and possible quantum histories in the Feynman path integral. I interpret the action as a physical measure of the essence of every possible history. Therefore only one actual history has the highest degree of the essence and minimal action. To address the issue of necessity, I assume that the principle of least action has a general physical necessity and lies between the laws of motion with a limited physical necessity and certain laws with a metaphysical necessity.

A Policy Representation Using Weighted Multiple Normal Distribution

Science.gov (United States)

Kimura, Hajime; Aramaki, Takeshi; Kobayashi, Shigenobu

In this paper, we challenge to solve a reinforcement learning problem for a 5-linked ring robot within a real-time so that the real-robot can stand up to the trial and error. On this robot, incomplete perception problems are caused from noisy sensors and cheap position-control motor systems. This incomplete perception also causes varying optimum actions with the progress of the learning. To cope with this problem, we adopt an actor-critic method, and we propose a new hierarchical policy representation scheme, that consists of discrete action selection on the top level and continuous action selection on the low level of the hierarchy. The proposed hierarchical scheme accelerates learning on continuous action space, and it can pursue the optimum actions varying with the progress of learning on our robotics problem. This paper compares and discusses several learning algorithms through simulations, and demonstrates the proposed method showing application for the real robot.

Familiarity and Voice Representation: From Acoustic-Based Representation to Voice Averages

Directory of Open Access Journals (Sweden)

Maureen Fontaine

2017-07-01

Full Text Available The ability to recognize an individual from their voice is a widespread ability with a long evolutionary history. Yet, the perceptual representation of familiar voices is ill-defined. In two experiments, we explored the neuropsychological processes involved in the perception of voice identity. We specifically explored the hypothesis that familiar voices (trained-to-familiar (Experiment 1, and famous voices (Experiment 2 are represented as a whole complex pattern, well approximated by the average of multiple utterances produced by a single speaker. In experiment 1, participants learned three voices over several sessions, and performed a three-alternative forced-choice identification task on original voice samples and several “speaker averages,” created by morphing across varying numbers of different vowels (e.g., [a] and [i] produced by the same speaker. In experiment 2, the same participants performed the same task on voice samples produced by familiar speakers. The two experiments showed that for famous voices, but not for trained-to-familiar voices, identification performance increased and response times decreased as a function of the number of utterances in the averages. This study sheds light on the perceptual representation of familiar voices, and demonstrates the power of average in recognizing familiar voices. The speaker average captures the unique characteristics of a speaker, and thus retains the information essential for recognition; it acts as a prototype of the speaker.

25 CFR 16.3 - Legal representation in State courts.

Science.gov (United States)

2010-04-01

... Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR PROBATE ESTATES OF INDIANS OF THE FIVE CIVILIZED TRIBES § 16.3 Legal representation in State courts. The statutory duties of the Secretary to... necessary to discharge said duties, with due regard to the complexity of the legal action contemplated, the...

Path integral representation of Lorentzian spinfoam model, asymptotics and simplicial geometries

International Nuclear Information System (INIS)

Han, Muxin; Krajewski, Thomas

2014-01-01

A new path integral representation of Lorentzian Engle–Pereira–Rovelli–Livine spinfoam model is derived by employing the theory of unitary representation of SL(2,C). The path integral representation is taken as a starting point of semiclassical analysis. The relation between the spinfoam model and classical simplicial geometry is studied via the large-spin asymptotic expansion of the spinfoam amplitude with all spins uniformly large. More precisely, in the large-spin regime, there is an equivalence between the spinfoam critical configuration (with certain nondegeneracy assumption) and a classical Lorentzian simplicial geometry. Such an equivalence relation allows us to classify the spinfoam critical configurations by their geometrical interpretations, via two types of solution-generating maps. The equivalence between spinfoam critical configuration and simplical geometry also allows us to define the notion of globally oriented and time-oriented spinfoam critical configuration. It is shown that only at the globally oriented and time-oriented spinfoam critical configuration, the leading-order contribution of spinfoam large-spin asymptotics gives precisely an exponential of Lorentzian Regge action of General Relativity. At all other (unphysical) critical configurations, spinfoam large-spin asymptotics modifies the Regge action at the leading-order approximation. (paper)

A Discussion on Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

Data.gov (United States)

National Aeronautics and Space Administration — This article presented a discussion on uncertainty representation and management for model-based prog- nostics methodologies based on the Bayesian tracking framework...

Mental representation and mental practice: experimental investigation on the functional links between motor memory and motor imagery.

Directory of Open Access Journals (Sweden)

Cornelia Frank

Full Text Available Recent research on mental representation of complex action has revealed distinct differences in the structure of representational frameworks between experts and novices. More recently, research on the development of mental representation structure has elicited functional changes in novices' representations as a result of practice. However, research investigating if and how mental practice adds to this adaptation process is lacking. In the present study, we examined the influence of mental practice (i.e., motor imagery rehearsal on both putting performance and the development of one's representation of the golf putt during early skill acquisition. Novice golfers (N = 52 practiced the task of golf putting under one of four different practice conditions: mental, physical, mental-physical combined, and no practice. Participants were tested prior to and after a practice phase, as well as after a three day retention interval. Mental representation structures of the putt were measured, using the structural dimensional analysis of mental representation. This method provides psychometric data on the distances and groupings of basic action concepts in long-term memory. Additionally, putting accuracy and putting consistency were measured using two-dimensional error scores of each putt. Findings revealed significant performance improvements over the course of practice together with functional adaptations in mental representation structure. Interestingly, after three days of practice, the mental representations of participants who incorporated mental practice into their practice regime displayed representation structures that were more similar to a functional structure than did participants who did not incorporate mental practice. The findings of the present study suggest that mental practice promotes the cognitive adaptation process during motor learning, leading to more elaborate representations than physical practice only.

Committee Representation and Medicare Reimbursements-An Examination of the Resource-Based Relative Value Scale.

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Gao, Y Nina

2018-04-06

The Resource-Based Relative Value Scale Update Committee (RUC) submits recommended reimbursement values for physician work (wRVUs) under Medicare Part B. The RUC includes rotating representatives from medical specialties. To identify changes in physician reimbursements associated with RUC rotating seat representation. Relative Value Scale Update Committee members 1994-2013; Medicare Part B Relative Value Scale 1994-2013; Physician/Supplier Procedure Summary Master File 2007; Part B National Summary Data File 2000-2011. I match service and procedure codes to specialties using 2007 Medicare billing data. Subsequently, I model wRVUs as a function of RUC rotating committee representation and level of code specialization. An annual RUC rotating seat membership is associated with a statistically significant 3-5 percent increase in Medicare expenditures for codes billed to that specialty. For codes that are performed by a small number of physicians, the association between reimbursement and rotating subspecialty representation is positive, 0.177 (SE = 0.024). For codes that are performed by a large number of physicians, the association is negative, -0.183 (SE = 0.026). Rotating representation on the RUC is correlated with overall reimbursement rates. The resulting differential changes may exacerbate existing reimbursement discrepancies between generalist and specialist practitioners. © Health Research and Educational Trust.

Research-Based Worksheets on Using Multiple Representations in Science Classrooms

Science.gov (United States)

Hill, Matthew; Sharma, Manjula

2015-01-01

The ability to represent the world like a scientist is difficult to teach; it is more than simply knowing the representations (e.g., graphs, words, equations and diagrams). For meaningful science learning to take place, consideration needs to be given to explicitly integrating representations into instructional methods, linked to the content, and…

Prediction of Protein-Protein Interaction By Metasample-Based Sparse Representation

Directory of Open Access Journals (Sweden)

Xiuquan Du

2015-01-01

Full Text Available Protein-protein interactions (PPIs play key roles in many cellular processes such as transcription regulation, cell metabolism, and endocrine function. Understanding these interactions takes a great promotion to the pathogenesis and treatment of various diseases. A large amount of data has been generated by experimental techniques; however, most of these data are usually incomplete or noisy, and the current biological experimental techniques are always very time-consuming and expensive. In this paper, we proposed a novel method (metasample-based sparse representation classification, MSRC for PPIs prediction. A group of metasamples are extracted from the original training samples and then use the l1-regularized least square method to express a new testing sample as the linear combination of these metasamples. PPIs prediction is achieved by using a discrimination function defined in the representation coefficients. The MSRC is applied to PPIs dataset; it achieves 84.9% sensitivity, and 94.55% specificity, which is slightly lower than support vector machine (SVM and much higher than naive Bayes (NB, neural networks (NN, and k-nearest neighbor (KNN. The result shows that the MSRC is efficient for PPIs prediction.

Design of multiple representations e-learning resources based on a contextual approach for the basic physics course

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Bakri, F.; Muliyati, D.

2018-05-01

This research aims to design e-learning resources with multiple representations based on a contextual approach for the Basic Physics Course. The research uses the research and development methods accordance Dick & Carey strategy. The development carried out in the digital laboratory of Physics Education Department, Mathematics and Science Faculty, Universitas Negeri Jakarta. The result of the process of product development with Dick & Carey strategy, have produced e-learning design of the Basic Physics Course is presented in multiple representations in contextual learning syntax. The appropriate of representation used in the design of learning basic physics include: concept map, video, figures, data tables of experiment results, charts of data tables, the verbal explanations, mathematical equations, problem and solutions example, and exercise. Multiple representations are presented in the form of contextual learning by stages: relating, experiencing, applying, transferring, and cooperating.

Hologram representation of design data in an expert system knowledge base

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Shiva, S. G.; Klon, Peter F.

1988-01-01

A novel representational scheme for design object descriptions is presented. An abstract notion of modules and signals is developed as a conceptual foundation for the scheme. This abstraction relates the objects to the meaning of system descriptions. Anchored on this abstraction, a representational model which incorporates dynamic semantics for these objects is presented. This representational model is called a hologram scheme since it represents dual level information, namely, structural and semantic. The benefits of this scheme are presented.

Force Concept Inventory-Based Multiple-Choice Test for Investigating Students' Representational Consistency

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Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

2010-01-01

This study investigates students' ability to interpret multiple representations consistently (i.e., representational consistency) in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI), which makes use of nine items from the 1995 version of the Force Concept Inventory…

Visual perception from the perspective of a representational, non-reductionistic, level-dependent account of perception and conscious awareness

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Overgaard, Morten; Mogensen, Jesper

2014-01-01

This article proposes a new model to interpret seemingly conflicting evidence concerning the correlation of consciousness and neural processes. Based on an analysis of research of blindsight and subliminal perception, the reorganization of elementary functions and consciousness framework suggests that mental representations consist of functions at several different levels of analysis, including truly localized perceptual elementary functions and perceptual algorithmic modules, which are interconnections of the elementary functions. We suggest that conscious content relates to the ‘top level’ of analysis in a ‘situational algorithmic strategy’ that reflects the general state of an individual. We argue that conscious experience is intrinsically related to representations that are available to guide behaviour. From this perspective, we find that blindsight and subliminal perception can be explained partly by too coarse-grained methodology, and partly by top-down enhancing of representations that normally would not be relevant to action. PMID:24639581

Ecological Citizenship and Social Representation of Water

Directory of Open Access Journals (Sweden)

Marta Biagi

2011-09-01

Full Text Available This article examines the social representations of water in urban cultures of Argentina, placing the subject as a matter of academic and practical interest. Some questions have guided this investigation—What is water for the urban dweller? What are the actions that a citizen is willing to exercise?—A qualitative research was conducted (according to Yin’s case analysis methodology in Gualeguaychú and Buenos Aires. Following the collected data, the authors reconstructed the dominant paradigm in both cities, which was the ecocentric model. However, the acceptance of ecological values and beliefs is not an indicator of the exercise of proecological behavior concerning water. Empirical findings have guided the authors to inquire the degree of relationship between social representations and attributes of Andrew Dobson’s model of ecological citizenship.

An XML Representation for Crew Procedures

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Simpson, Richard C.

2005-01-01

NASA ensures safe operation of complex systems through the use of formally-documented procedures, which encode the operational knowledge of the system as derived from system experts. Crew members use procedure documentation on the ground for training purposes and on-board space shuttle and space station to guide their activities. Investigators at JSC are developing a new representation for procedures that is content-based (as opposed to display-based). Instead of specifying how a procedure should look on the printed page, the content-based representation will identify the components of a procedure and (more importantly) how the components are related (e.g., how the activities within a procedure are sequenced; what resources need to be available for each activity). This approach will allow different sets of rules to be created for displaying procedures on a computer screen, on a hand-held personal digital assistant (PDA), verbally, or on a printed page, and will also allow intelligent reasoning processes to automatically interpret and use procedure definitions. During his NASA fellowship, Dr. Simpson examined how various industries represent procedures (also called business processes or workflows), in areas such as manufacturing, accounting, shipping, or customer service. A useful method for designing and evaluating workflow representation languages is by determining their ability to encode various workflow patterns, which depict abstract relationships between the components of a procedure removed from the context of a specific procedure or industry. Investigators have used this type of analysis to evaluate how well-suited existing workflow representation languages are for various industries based on the workflow patterns that commonly arise across industry-specific procedures. Based on this type of analysis, it is already clear that existing workflow representations capture discrete flow of control (i.e., when one activity should start and stop based on when other

Force Concept Inventory-based multiple-choice test for investigating students’ representational consistency

Directory of Open Access Journals (Sweden)

Pasi Nieminen

2010-08-01

Full Text Available This study investigates students’ ability to interpret multiple representations consistently (i.e., representational consistency in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI, which makes use of nine items from the 1995 version of the Force Concept Inventory (FCI. These original FCI items were redesigned using various representations (such as motion map, vectorial and graphical, yielding 27 multiple-choice items concerning four central concepts underpinning the force concept: Newton’s first, second, and third laws, and gravitation. We provide some evidence for the validity and reliability of the R-FCI; this analysis is limited to the student population of one Finnish high school. The students took the R-FCI at the beginning and at the end of their first high school physics course. We found that students’ (n=168 representational consistency (whether scientifically correct or not varied considerably depending on the concept. On average, representational consistency and scientifically correct understanding increased during the instruction, although in the post-test only a few students performed consistently both in terms of representations and scientifically correct understanding. We also compared students’ (n=87 results of the R-FCI and the FCI, and found that they correlated quite well.

Skeleton-based human action recognition using multiple sequence alignment

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Ding, Wenwen; Liu, Kai; Cheng, Fei; Zhang, Jin; Li, YunSong

2015-05-01

Human action recognition and analysis is an active research topic in computer vision for many years. This paper presents a method to represent human actions based on trajectories consisting of 3D joint positions. This method first decompose action into a sequence of meaningful atomic actions (actionlets), and then label actionlets with English alphabets according to the Davies-Bouldin index value. Therefore, an action can be represented using a sequence of actionlet symbols, which will preserve the temporal order of occurrence of each of the actionlets. Finally, we employ sequence comparison to classify multiple actions through using string matching algorithms (Needleman-Wunsch). The effectiveness of the proposed method is evaluated on datasets captured by commodity depth cameras. Experiments of the proposed method on three challenging 3D action datasets show promising results.

Efficiency in Rule- vs. Plan-Based Movements Is Modulated by Action-Mode.

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Scheib, Jean P P; Stoll, Sarah; Thürmer, J Lukas; Randerath, Jennifer

2018-01-01

The rule/plan motor cognition (RPMC) paradigm elicits visually indistinguishable motor outputs, resulting from either plan- or rule-based action-selection, using a combination of essentially interchangeable stimuli. Previous implementations of the RPMC paradigm have used pantomimed movements to compare plan- vs. rule-based action-selection. In the present work we attempt to determine the generalizability of previous RPMC findings to real object interaction by use of a grasp-to-rotate task. In the plan task, participants had to use prospective planning to achieve a comfortable post-handle rotation hand posture. The rule task used implementation intentions (if-then rules) leading to the same comfortable end-state. In Experiment A, we compare RPMC performance of 16 healthy participants in pantomime and real object conditions of the experiment, within-subjects. Higher processing efficiency of rule- vs. plan-based action-selection was supported by diffusion model analysis. Results show a significant response-time increase in the pantomime condition compared to the real object condition and a greater response-time advantage of rule-based vs. plan-based actions in the pantomime compared to the real object condition. In Experiment B, 24 healthy participants performed the real object RPMC task in a task switching vs. a blocked condition. Results indicate that plan-based action-selection leads to longer response-times and less efficient information processing than rule-based action-selection in line with previous RPMC findings derived from the pantomime action-mode. Particularly in the task switching mode, responses were faster in the rule compared to the plan task suggesting a modulating influence of cognitive load. Overall, results suggest an advantage of rule-based action-selection over plan-based action-selection; whereby differential mechanisms appear to be involved depending on the action-mode. We propose that cognitive load is a factor that modulates the advantageous

No functional role of attention-based rehearsal in maintenance of spatial working memory representations

NARCIS (Netherlands)

Belopolsky, A.V.; Theeuwes, J.

2009-01-01

The present study systematically examined the role of attention in maintenance of spatial representations in working memory as proposed by the attention-based rehearsal hypothesis [Awh, E., Jonides, J., & Reuter-Lorenz, P. A. (1998). Rehearsal in spatial working memory. Journal of Experimental

Vertex operator representation of the soliton tau functions in the An(1) Toda models by dressing transformations

International Nuclear Information System (INIS)

Belich, H.; Cuba, G.; Paunov, R.

1997-12-01

Affine Toda theories based on simple Lie algebras G are known to posses soliton solutions. Toda solitons has been found by Olive, Turok and Underwood within the group-theoretical approach to the integrable field equations. Single solitons are created by exponentials of special elements of the underlying affine Lie algebra which diagonalize the adjoint action of the principal Heisenberg subalgebra. When G is simply laced and level one representations are considered, the generators of the affine Lie algebra are expressed in terms of the principal Heisenberg oscillators. This representation is known as vertex operator construction. It plays a crucial role in the string theory as well as in the conformal field theory. Alternatively, solitons can be generated from the vacuum by dressing transformations. The problem to relate dressing symmetry to the vertex operator representation of the tau functions for the sine-Gordon model was previously considered by Babelon and Bernard. In the present paper, we extend this relation for arbitrary A (1) n Toda field theory. (author)

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

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Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

Grounded Object and Grasp Representations in a Cognitive Architecture

DEFF Research Database (Denmark)

Kraft, Dirk

developed. This work presents a system that is able to learn autonomously about objects and applicable grasps in an unknown environment through exploratory manipulation and to then use this grounded knowledge in a planning setup to address complex tasks. A set of different subsystems is needed to achieve....... The topics are ordered so that we proceed from the more general integration works towards the works describing the individual components. The first chapter gives an overview over the system that is able to learn a grounded visual object representation and a grounded grasp representation. In the following...... part, we describe how this grounding procedures can be embedded in a three cognitive level architecture. Our initial work to use a tactile sensor to enrichen the object representations as well as allow for more complex actions is presented here as well. Since our system is concerned with learning about...

The Performance and Observation of Action Shape Future Behaviour

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Welsh, Timothy N.; McDougall, Laura M.; Weeks, Daniel J.

2009-01-01

The observation of other people's actions plays an important role in shaping the perceptual, cognitive, and motor processes of the observer. It has been suggested that these social influences occur because the observation of action evokes a representation of that response in the observer and that these codes are subsequently accessed by other…

Function and Form of Action-Based Teaching in Higher Education

DEFF Research Database (Denmark)

Keiding, Tina Bering

The aim of the research is to subject progressive, critical and entrepreneurial pedagogy to a didactic inquiry based on the specific application of action-based teaching in order to answer two fundamental didactic questions: What educational purpose does the use of action-based teaching serve? How...... does the educational purpose affect the specific form of the constituting elements of the method?...

The Quench Action

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Caux, Jean-Sébastien

2016-06-01

We give a pedagogical introduction to the methodology of the Quench Action, which is an effective representation for the calculation of time-dependent expectation values of physical operators following a generic out-of-equilibrium state preparation protocol (for example a quantum quench). The representation, originally introduced in Caux and Essler (2013 Phys. Rev. Lett. 110 257203), is founded on a mixture of exact data for overlaps together with variational reasonings. It is argued to be quite generally valid and thermodynamically exact for arbitrary times after the quench (from short times all the way up to the steady state), and applicable to a wide class of physically relevant observables. Here, we introduce the method and its language, give an overview of some recent results, suggest a roadmap and offer some perspectives on possible future research directions.

Body-specific motor imagery of hand actions: neural evidence from right- and left-handers

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Roel M Willems

2009-11-01

Full Text Available If motor imagery uses neural structures involved in action execution, then the neural correlates of imagining an action should differ between individuals who tend to execute the action differently. Here we report fMRI data showing that motor imagery is influenced by the way people habitually perform motor actions with their particular bodies; that is, motor imagery is ‘body-specific’ (Casasanto, 2009. During mental imagery for complex hand actions, activation of cortical areas involved in motor planning and execution was left-lateralized in right-handers but right-lateralized in left-handers. We conclude that motor imagery involves the generation of an action plan that is grounded in the participant’s motor habits, not just an abstract representation at the level of the action’s goal. People with different patterns of motor experience form correspondingly different neurocognitive representations of imagined actions.

A generalized wavelet extrema representation

Energy Technology Data Exchange (ETDEWEB)

Lu, Jian; Lades, M.

1995-10-01

The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.

Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

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Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

2017-05-01

Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

The application of brain-based learning principles aided by GeoGebra to improve mathematical representation ability

Science.gov (United States)

Priatna, Nanang

2017-08-01

The use of Information and Communication Technology (ICT) in mathematics instruction will help students in building conceptual understanding. One of the software products used in mathematics instruction is GeoGebra. The program enables simple visualization of complex geometric concepts and helps improve students' understanding of geometric concepts. Instruction applying brain-based learning principles is one oriented at the efforts of naturally empowering the brain potentials which enable students to build their own knowledge. One of the goals of mathematics instruction in school is to develop mathematical communication ability. Mathematical representation is regarded as a part of mathematical communication. It is a description, expression, symbolization, or modeling of mathematical ideas/concepts as an attempt of clarifying meanings or seeking for solutions to the problems encountered by students. The research aims to develop a learning model and teaching materials by applying the principles of brain-based learning aided by GeoGebra to improve junior high school students' mathematical representation ability. It adopted a quasi-experimental method with the non-randomized control group pretest-posttest design and the 2x3 factorial model. Based on analysis of the data, it is found that the increase in the mathematical representation ability of students who were treated with mathematics instruction applying the brain-based learning principles aided by GeoGebra was greater than the increase of the students given conventional instruction, both as a whole and based on the categories of students' initial mathematical ability.

Post-apartheid representations of youth in the Zulu novel Kungasa ngifile

Directory of Open Access Journals (Sweden)

N.S. Zulu

2004-07-01

Full Text Available In this article representation of black African youth in the Zulu novel “Kungasa ngifile” is examined. The view is presented that the novel, though seeming to be politically neutral, deals with images of the youth that have ideological concerns in terms of theme, plot action and character portrayal. Such ideological modes of representation seem to be in tune with the present call for moral rejuvenation and the empowerment of the youth who lost opportunities during the liberation struggle. In this respect, the novel backs positive post-apartheid cultural forms.

Model's sparse representation based on reduced mixed GMsFE basis methods

Energy Technology Data Exchange (ETDEWEB)

Jiang, Lijian, E-mail: ljjiang@hnu.edu.cn [Institute of Mathematics, Hunan University, Changsha 410082 (China); Li, Qiuqi, E-mail: qiuqili@hnu.edu.cn [College of Mathematics and Econometrics, Hunan University, Changsha 410082 (China)

2017-06-01

In this paper, we propose a model's sparse representation based on reduced mixed generalized multiscale finite element (GMsFE) basis methods for elliptic PDEs with random inputs. A typical application for the elliptic PDEs is the flow in heterogeneous random porous media. Mixed generalized multiscale finite element method (GMsFEM) is one of the accurate and efficient approaches to solve the flow problem in a coarse grid and obtain the velocity with local mass conservation. When the inputs of the PDEs are parameterized by the random variables, the GMsFE basis functions usually depend on the random parameters. This leads to a large number degree of freedoms for the mixed GMsFEM and substantially impacts on the computation efficiency. In order to overcome the difficulty, we develop reduced mixed GMsFE basis methods such that the multiscale basis functions are independent of the random parameters and span a low-dimensional space. To this end, a greedy algorithm is used to find a set of optimal samples from a training set scattered in the parameter space. Reduced mixed GMsFE basis functions are constructed based on the optimal samples using two optimal sampling strategies: basis-oriented cross-validation and proper orthogonal decomposition. Although the dimension of the space spanned by the reduced mixed GMsFE basis functions is much smaller than the dimension of the original full order model, the online computation still depends on the number of coarse degree of freedoms. To significantly improve the online computation, we integrate the reduced mixed GMsFE basis methods with sparse tensor approximation and obtain a sparse representation for the model's outputs. The sparse representation is very efficient for evaluating the model's outputs for many instances of parameters. To illustrate the efficacy of the proposed methods, we present a few numerical examples for elliptic PDEs with multiscale and random inputs. In particular, a two-phase flow model in

How task goals mediate the interplay between perception and action

Directory of Open Access Journals (Sweden)

Pascal eHaazebroek

2013-05-01

Full Text Available Theories of embodied cognition suppose that perception, action and cognition are tightly intertwined and share common representations and processes. Indeed, numerous empirical studies demonstrate interaction between stimulus perception, response planning and response execution. In this paper, we present an experiment and a connectionist model that show how the Simon effect, a canonical example of perception-action congruency, can be moderated by the (cognitive representation of the task instruction. To date, no representational account of this influence exists. In the experiment, a two-dimensional Simon task was used, with critical stimuli being colored arrows pointing in one of four directions (backward, forward, left or right. Participants stood on a Wii balance board, oriented diagonally towards the screen displaying the stimuli. They were either instructed to imagine standing on a snowboard or on a pair of skis and to respond to the stimulus color by leaning towards either the left or right foot. We expected that participants in the snowboard condition would encode these movements as forward or backward, resulting in a Simon effect on this dimension. This was confirmed by the results. The left–right congruency effect was larger in the ski condition, whereas the forward–backward congruency effect appeared only in the snowboard condition. The results can be readily accounted for by HiTEC, a connectionist model that aims at capturing the interaction between perception and action at the level of representations, and the way this interaction is mediated by cognitive control. Together, the empirical work and the connectionist model contribute to a better understanding of the complex interaction between perception, cognition, and action.

Taking action: A cross-modal investigation of discourse structure

Directory of Open Access Journals (Sweden)

Elsi eKaiser

2012-06-01

Full Text Available Segmenting stimuli into events and understanding the relations between those events is crucial for understanding the world. For example, on the linguistic level, successful language use requires the ability to recognize semantic coherence relations between events (e.g. causality, similarity. However, relatively little is known about the mental representation of discourse structure. We report two experiments that used a cross-modal priming paradigm to investigate how humans represent the relations between events. Participants repeated a motor action modeled by the experimenter (e.g. rolled a ball towards mini bowling pins to knock them over, and then completed an unrelated sentence-continuation task (e.g. provided a continuation for Peter scratched John. …. In two experiments, we tested whether and how the coherence relations represented by the motor actions (e.g., causal events vs. non-causal events influence participants’ performance in the linguistic task. Our analyses focused on the coherence relations between the prompt sentences and participants’ continuations, as well as the referential shifts in the continuations. As a whole, the results suggest that the mental representations activated by motor actions overlap with the mental representations used during linguistic discourse-level processing, but nevertheless contain fine-grained information about sub-types of causality (reaction vs. consequence. In addition, the findings point to parallels between shifting one’s attention from one event to another and shifting one’s attention from one referent to another, and indicate that the event structure of causal sequences is conceptualized more like single events than like two distinct events. As a whole, the results point towards common representations activated by motor sequences and discourse-semantic relations, and further our understanding of the mental representation of discourse structure, an area that is still not yet well-understood.

A continuous-time neural model for sequential action.

Science.gov (United States)

Kachergis, George; Wyatte, Dean; O'Reilly, Randall C; de Kleijn, Roy; Hommel, Bernhard

2014-11-05

Action selection, planning and execution are continuous processes that evolve over time, responding to perceptual feedback as well as evolving top-down constraints. Existing models of routine sequential action (e.g. coffee- or pancake-making) generally fall into one of two classes: hierarchical models that include hand-built task representations, or heterarchical models that must learn to represent hierarchy via temporal context, but thus far lack goal-orientedness. We present a biologically motivated model of the latter class that, because it is situated in the Leabra neural architecture, affords an opportunity to include both unsupervised and goal-directed learning mechanisms. Moreover, we embed this neurocomputational model in the theoretical framework of the theory of event coding (TEC), which posits that actions and perceptions share a common representation with bidirectional associations between the two. Thus, in this view, not only does perception select actions (along with task context), but actions are also used to generate perceptions (i.e. intended effects). We propose a neural model that implements TEC to carry out sequential action control in hierarchically structured tasks such as coffee-making. Unlike traditional feedforward discrete-time neural network models, which use static percepts to generate static outputs, our biological model accepts continuous-time inputs and likewise generates non-stationary outputs, making short-timescale dynamic predictions. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

16 CFR 1025.18 - Class actions.

Science.gov (United States)

2010-01-01

... PROCEEDINGS Pleadings, Form, Execution, Service of Documents § 1025.18 Class actions. (a) Prerequisites to a..., the extent and nature of any proceedings concerning the controversy already commenced against members... that the pleadings be amended to eliminate allegations concerning the representation of absent persons...

Locality-preserving sparse representation-based classification in hyperspectral imagery

Science.gov (United States)

Gao, Lianru; Yu, Haoyang; Zhang, Bing; Li, Qingting

2016-10-01

This paper proposes to combine locality-preserving projections (LPP) and sparse representation (SR) for hyperspectral image classification. The LPP is first used to reduce the dimensionality of all the training and testing data by finding the optimal linear approximations to the eigenfunctions of the Laplace Beltrami operator on the manifold, where the high-dimensional data lies. Then, SR codes the projected testing pixels as sparse linear combinations of all the training samples to classify the testing pixels by evaluating which class leads to the minimum approximation error. The integration of LPP and SR represents an innovative contribution to the literature. The proposed approach, called locality-preserving SR-based classification, addresses the imbalance between high dimensionality of hyperspectral data and the limited number of training samples. Experimental results on three real hyperspectral data sets demonstrate that the proposed approach outperforms the original counterpart, i.e., SR-based classification.

Cross-View Action Recognition via Transferable Dictionary Learning.

Science.gov (United States)

Zheng, Jingjing; Jiang, Zhuolin; Chellappa, Rama

2016-05-01

Discriminative appearance features are effective for recognizing actions in a fixed view, but may not generalize well to a new view. In this paper, we present two effective approaches to learn dictionaries for robust action recognition across views. In the first approach, we learn a set of view-specific dictionaries where each dictionary corresponds to one camera view. These dictionaries are learned simultaneously from the sets of correspondence videos taken at different views with the aim of encouraging each video in the set to have the same sparse representation. In the second approach, we additionally learn a common dictionary shared by different views to model view-shared features. This approach represents the videos in each view using a view-specific dictionary and the common dictionary. More importantly, it encourages the set of videos taken from the different views of the same action to have the similar sparse representations. The learned common dictionary not only has the capability to represent actions from unseen views, but also makes our approach effective in a semi-supervised setting where no correspondence videos exist and only a few labeled videos exist in the target view. The extensive experiments using three public datasets demonstrate that the proposed approach outperforms recently developed approaches for cross-view action recognition.

Alchemical and structural distribution based representation for universal quantum machine learning

Science.gov (United States)

Faber, Felix A.; Christensen, Anders S.; Huang, Bing; von Lilienfeld, O. Anatole

2018-06-01

We introduce a representation of any atom in any chemical environment for the automatized generation of universal kernel ridge regression-based quantum machine learning (QML) models of electronic properties, trained throughout chemical compound space. The representation is based on Gaussian distribution functions, scaled by power laws and explicitly accounting for structural as well as elemental degrees of freedom. The elemental components help us to lower the QML model's learning curve, and, through interpolation across the periodic table, even enable "alchemical extrapolation" to covalent bonding between elements not part of training. This point is demonstrated for the prediction of covalent binding in single, double, and triple bonds among main-group elements as well as for atomization energies in organic molecules. We present numerical evidence that resulting QML energy models, after training on a few thousand random training instances, reach chemical accuracy for out-of-sample compounds. Compound datasets studied include thousands of structurally and compositionally diverse organic molecules, non-covalently bonded protein side-chains, (H2O)40-clusters, and crystalline solids. Learning curves for QML models also indicate competitive predictive power for various other electronic ground state properties of organic molecules, calculated with hybrid density functional theory, including polarizability, heat-capacity, HOMO-LUMO eigenvalues and gap, zero point vibrational energy, dipole moment, and highest vibrational fundamental frequency.

Intelligent robot action planning

Energy Technology Data Exchange (ETDEWEB)

Vamos, T; Siegler, A

1982-01-01

Action planning methods used in intelligent robot control are discussed. Planning is accomplished through environment understanding, environment representation, task understanding and planning, motion analysis and man-machine communication. These fields are analysed in detail. The frames of an intelligent motion planning system are presented. Graphic simulation of the robot's environment and motion is used to support the planning. 14 references.

(Self)-representations on youtube

OpenAIRE

Simonsen, Thomas Mosebo

2011-01-01

This paper examines forms of self-representation on YouTube with specific focus on Vlogs (Video blogs). The analytical scope of the paper is on how User-generated Content on YouTube initiates a certain kind of audiovisual representation and a particular interpretation of reality that can be distinguished within Vlogs. This will be analysed through selected case studies taken from a representative sample of empirically based observations of YouTube videos. The analysis includes a focus on how ...

DEVELOPMENT OF INTERACTIVE E-BOOK BASED ON CHEMICAL REPRESENTATION REFER TO CURRICULUM 2013

Directory of Open Access Journals (Sweden)

L. Tania

2015-11-01

Full Text Available This research aimed to develop an interactive e-book based representations of chemistry; describes the characteristics of the interactive e-book developed; the teachers responses in content suitability with curriculum and graphics aspects; and student responses in readibility aspects. The method used was research and development. The characteristics of interactive e-book: it was developed referring to the core competencies (KI and basic competence (KD in the curriculum 2013, allowed active interaction between students and e-book, completed with pictures, animations or videos in three levels of the chemical representation. Teachers’ responses to the content suitability and graphic aspects were very good with the percentage of each 98.46% and 97.5%. The students’ responses in readibility aspects was very good with percentage of 88.5%.

Permutation representations of the orbits of the automorphism group ...

Indian Academy of Sciences (India)

Abstract. Consider a discrete valuation ring R whose residue field is finite of car- dinality at least 3. For a finite torsion module, we consider transitive subsets O under the action of the automorphism group of the module. We prove that the associated per- mutation representation on the complex vector space C[O] is multiplicity ...

Stereoscopically Observing Manipulative Actions.

Science.gov (United States)

Ferri, S; Pauwels, K; Rizzolatti, G; Orban, G A

2016-08-01

The purpose of this study was to investigate the contribution of stereopsis to the processing of observed manipulative actions. To this end, we first combined the factors "stimulus type" (action, static control, and dynamic control), "stereopsis" (present, absent) and "viewpoint" (frontal, lateral) into a single design. Four sites in premotor, retro-insular (2) and parietal cortex operated specifically when actions were viewed stereoscopically and frontally. A second experiment clarified that the stereo-action-specific regions were driven by actions moving out of the frontoparallel plane, an effect amplified by frontal viewing in premotor cortex. Analysis of single voxels and their discriminatory power showed that the representation of action in the stereo-action-specific areas was more accurate when stereopsis was active. Further analyses showed that the 4 stereo-action-specific sites form a closed network converging onto the premotor node, which connects to parietal and occipitotemporal regions outside the network. Several of the specific sites are known to process vestibular signals, suggesting that the network combines observed actions in peripersonal space with gravitational signals. These findings have wider implications for the function of premotor cortex and the role of stereopsis in human behavior. © The Author 2016. Published by Oxford University Press.

On the Representation of Subgrid Microtopography Effects in Process-based Hydrologic Models

Science.gov (United States)

Jan, A.; Painter, S. L.; Coon, E. T.

2017-12-01

Increased availability of high-resolution digital elevation are enabling process-based hydrologic modeling on finer and finer scales. However, spatial variability in surface elevation (microtopography) exists below the scale of a typical hyper-resolution grid cell and has the potential to play a significant role in water retention, runoff, and surface/subsurface interactions. Though the concept of microtopographic features (depressions, obstructions) and the associated implications on flow and discharge are well established, representing those effects in watershed-scale integrated surface/subsurface hydrology models remains a challenge. Using the complex and coupled hydrologic environment of the Arctic polygonal tundra as an example, we study the effects of submeter topography and present a subgrid model parameterized by small-scale spatial heterogeneities for use in hyper-resolution models with polygons at a scale of 15-20 meters forming the surface cells. The subgrid model alters the flow and storage terms in the diffusion wave equation for surface flow. We compare our results against sub-meter scale simulations (acts as a benchmark for our simulations) and hyper-resolution models without the subgrid representation. The initiation of runoff in the fine-scale simulations is delayed and the recession curve is slowed relative to simulated runoff using the hyper-resolution model with no subgrid representation. Our subgrid modeling approach improves the representation of runoff and water retention relative to models that ignore subgrid topography. We evaluate different strategies for parameterizing subgrid model and present a classification-based method to efficiently move forward to larger landscapes. This work was supported by the Interoperable Design of Extreme-scale Application Software (IDEAS) project and the Next-Generation Ecosystem Experiments-Arctic (NGEE Arctic) project. NGEE-Arctic is supported by the Office of Biological and Environmental Research in the

The homological content of the Jones representations at $q = -1$

DEFF Research Database (Denmark)

Egsgaard, Jens Kristian; Fuglede Jørgensen, Søren

We generalize a discovery of Kasahara and show that the Jones representations of braid groups, when evaluated at $q = -1$, are related to the action on homology of a branched double cover of the underlying punctured disk. As an application, we prove for a large family of pseudo-Anosov mapping...

Knowledge Representation and Inference for Analysis and Design of Database and Tabular Rule-Based Systems

Directory of Open Access Journals (Sweden)

Antoni Ligeza

2001-01-01

Full Text Available Rulebased systems constitute a powerful tool for specification of knowledge in design and implementation of knowledge based systems. They provide also a universal programming paradigm for domains such as intelligent control, decision support, situation classification and operational knowledge encoding. In order to assure safe and reliable performance, such system should satisfy certain formal requirements, including completeness and consistency. This paper addresses the issue of analysis and verification of selected properties of a class of such system in a systematic way. A uniform, tabular scheme of single-level rule-based systems is considered. Such systems can be applied as a generalized form of databases for specification of data pattern (unconditional knowledge, or can be used for defining attributive decision tables (conditional knowledge in form of rules. They can also serve as lower-level components of a hierarchical multi-level control and decision support knowledge-based systems. An algebraic knowledge representation paradigm using extended tabular representation, similar to relational database tables is presented and algebraic bases for system analysis, verification and design support are outlined.

Knowledge Representation Using Multilevel Flow Model in Expert System

International Nuclear Information System (INIS)

Wang, Wenlin; Yang, Ming

2015-01-01

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available

Knowledge Representation Using Multilevel Flow Model in Expert System

Energy Technology Data Exchange (ETDEWEB)

Wang, Wenlin; Yang, Ming [Harbin Engineering University, Harbin (China)

2015-05-15

As for the knowledge representation, of course, there are a great many methods available for knowledge representation. These include frames, causal models, and many others. This paper presents a novel method called Multilevel Flow Model (MFM), which is used for knowledge representation in G2 expert system. Knowledge representation plays a vital role in constructing knowledge bases. Moreover, it also has impact on building of generic fault model as well as knowledge bases. The MFM is particularly useful to describe system knowledge concisely as domain map in expert system when domain experts are not available.

Quota election system as a way of achieving descriptive and substantive representation of women in parliaments

Directory of Open Access Journals (Sweden)

Mršević Zorica

2007-01-01

Full Text Available In ten chapters of the text are analyzed issues of under representation of women in legislative bodies (descriptive representation matched with possibilities of their substantive representation. The substantive representation means contribution of women MPs in development and promotion of "women's politics" and politics of representing specific interest of women's part of population. In chapters under the titles, Underrepresented sex, Quota term, and Myths on quotas, are presented the main characteristics of the issues of women's under representation from political mainstream and decision-making bodies. There is also analyzed quota preferential electoral system as a solution. The gist of the text is comprised in the chapter Why Quotas where are presented the classical arguments for quotas as a specific measure of affirmative action. The way from increasing quantitative presence of women in legislative bodies to increasing the qualitative level of their activities in there is elaborated in the chapters Increasing numbers and achieving quality, Issues of women's political efficiency, Criteria of changes, and Inter parliamentarian activities of women. In the chapter Women's issues and women's perspectives is defined difference between these two aspects of women's MPs activities. Women's issues are those issues influencing directly women on physical or social way (e.g. breast cancer, reproductive rights, gender based discrimination, politics of child's care. The women's perspectives are specific women's interest and views of all other political issues.

Model-based object classification using unification grammars and abstract representations

Science.gov (United States)

Liburdy, Kathleen A.; Schalkoff, Robert J.

1993-04-01

The design and implementation of a high level computer vision system which performs object classification is described. General object labelling and functional analysis require models of classes which display a wide range of geometric variations. A large representational gap exists between abstract criteria such as `graspable' and current geometric image descriptions. The vision system developed and described in this work addresses this problem and implements solutions based on a fusion of semantics, unification, and formal language theory. Object models are represented using unification grammars, which provide a framework for the integration of structure and semantics. A methodology for the derivation of symbolic image descriptions capable of interacting with the grammar-based models is described and implemented. A unification-based parser developed for this system achieves object classification by determining if the symbolic image description can be unified with the abstract criteria of an object model. Future research directions are indicated.

The effect of project-based learning on students' statistical literacy levels for data representation

Science.gov (United States)

Koparan, Timur; Güven, Bülent

2015-07-01

The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35 in the experimental group and 35 in the control group, took this test twice, one before the application and one after the application. All the raw scores were turned into linear points by using the Winsteps 3.72 modelling program that makes the Rasch analysis and t-tests, and an ANCOVA analysis was carried out with the linear points. Depending on the findings, it was concluded that the project-based learning approach increases students' level of statistical literacy for data representation. Students' levels of statistical literacy before and after the application were shown through the obtained person-item maps.

Vision and the representation of the surroundings in spatial memory

Science.gov (United States)

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

Vision and the representation of the surroundings in spatial memory.

Science.gov (United States)

Tatler, Benjamin W; Land, Michael F

2011-02-27

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.

A Review on Human Activity Recognition Using Vision-Based Method.

Science.gov (United States)

Zhang, Shugang; Wei, Zhiqiang; Nie, Jie; Huang, Lei; Wang, Shuang; Li, Zhen

2017-01-01

Human activity recognition (HAR) aims to recognize activities from a series of observations on the actions of subjects and the environmental conditions. The vision-based HAR research is the basis of many applications including video surveillance, health care, and human-computer interaction (HCI). This review highlights the advances of state-of-the-art activity recognition approaches, especially for the activity representation and classification methods. For the representation methods, we sort out a chronological research trajectory from global representations to local representations, and recent depth-based representations. For the classification methods, we conform to the categorization of template-based methods, discriminative models, and generative models and review several prevalent methods. Next, representative and available datasets are introduced. Aiming to provide an overview of those methods and a convenient way of comparing them, we classify existing literatures with a detailed taxonomy including representation and classification methods, as well as the datasets they used. Finally, we investigate the directions for future research.

Right-Linear Languages Generated in Systems of Knowledge Representation based on LSG

Directory of Open Access Journals (Sweden)

Daniela Danciulescu

2017-04-01

Full Text Available In Tudor (Preda (2010 a method for formal languages generation based on labeled stratified graph representations is sketched. The author proves that the considered method can generate regular languages and context-sensitive languages by considering an exemplification of the proposed method for a particular regular language and another one for a particular contextsensitive language. At the end of the study, the author highlights some open problems for future research among which we remind: (1 The study of the language families that can be generated by means of these structures; (2 The study of the infiniteness of the languages that can be represented in stratified graphs. In this paper, we extend the method presented in Tudor (Preda(2010, by considering the stratified graph formalism in a system of knowledge representation and reasoning. More precisely, we propose a method that can be applied for generating any Right Linear Language construction. Our method is proved and exemplified in several cases.

Representation theory a first course

CERN Document Server

Fulton, William

1991-01-01

The primary goal of these lectures is to introduce a beginner to the finite­ dimensional representations of Lie groups and Lie algebras. Since this goal is shared by quite a few other books, we should explain in this Preface how our approach differs, although the potential reader can probably see this better by a quick browse through the book. Representation theory is simple to define: it is the study of the ways in which a given group may act on vector spaces. It is almost certainly unique, however, among such clearly delineated subjects, in the breadth of its interest to mathematicians. This is not surprising: group actions are ubiquitous in 20th century mathematics, and where the object on which a group acts is not a vector space, we have learned to replace it by one that is {e. g. , a cohomology group, tangent space, etc. }. As a consequence, many mathematicians other than specialists in the field {or even those who think they might want to be} come in contact with the subject in various ways. It is for ...

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

Science.gov (United States)

Celaya, Jose R.; Saxen, Abhinav; Goebel, Kai

2012-01-01

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Transient Variable Caching in Java’s Stack-Based Intermediate Representation

Directory of Open Access Journals (Sweden)

Paul Týma

1999-01-01

Full Text Available Java’s stack‐based intermediate representation (IR is typically coerced to execute on register‐based architectures. Unoptimized compiled code dutifully replicates transient variable usage designated by the programmer and common optimization practices tend to introduce further usage (i.e., CSE, Loop‐invariant Code Motion, etc.. On register based machines, often transient variables are cached within registers (when available saving the expense of actually accessing memory. Unfortunately, in stack‐based environments because of the need to push and pop the transient values, further performance improvement is possible. This paper presents Transient Variable Caching (TVC, a technique for eliminating transient variable overhead whenever possible. This optimization would find a likely home in optimizers attached to the back of popular Java compilers. Side effects of the algorithm include significant instruction reordering and introduction of many stack‐manipulation operations. This combination has proven to greatly impede the ability to decompile stack‐based IR code sequences. The code that results from the transform is faster, smaller, and greatly impedes decompilation.

A dynamic texture-based approach to recognition of facial actions and their temporal models.

Science.gov (United States)

Koelstra, Sander; Pantic, Maja; Patras, Ioannis

2010-11-01

In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the dynamics and the appearance in the face region of an input video are compared: an extended version of Motion History Images and a novel method based on Nonrigid Registration using Free-Form Deformations (FFDs). The extracted motion representation is used to derive motion orientation histogram descriptors in both the spatial and temporal domain. Per AU, a combination of discriminative, frame-based GentleBoost ensemble learners and dynamic, generative Hidden Markov Models detects the presence of the AU in question and its temporal segments in an input image sequence. When tested for recognition of all 27 lower and upper face AUs, occurring alone or in combination in 264 sequences from the MMI facial expression database, the proposed method achieved an average event recognition accuracy of 89.2 percent for the MHI method and 94.3 percent for the FFD method. The generalization performance of the FFD method has been tested using the Cohn-Kanade database. Finally, we also explored the performance on spontaneous expressions in the Sensitive Artificial Listener data set.

Ambiguities in the Association Between Symmetries and Conservation Laws in the Presence of Alternative Lagrangian Representations

International Nuclear Information System (INIS)

Amitava Choudhuri; Subrata Ghosh; Talukdar, B.

2011-01-01

We identify two alternative Lagrangian representations for the damped harmonic oscillator characterised by a frictional coefficient γ. The first one is explicitly time independent while the second one involves time parameter explicitly. With separate attention to both Lagrangians we make use of the Noether theorem to compute the variational symmetries and conservation laws in order to study how association between them changes as one goes from one representation to the other. In the case of time independent representation squeezing symmetry leads to conservation of angular momentum for γ = 0, while for the time-dependent Lagrangian the same conserved quantity results from rotational invariance. The Lie algebra (g) of the symmetry vectors that leaves the action corresponding to the time-independent Lagrangian invariant is semi-simple. On the other hand, g is only a simple Lie algebra for the action characterised by the time-dependent Lagrangian. (authors)

Dysregulation in level of goal and action identification across psychological disorders

Science.gov (United States)

Watkins, Edward

2011-01-01

Goals, events, and actions can be mentally represented within a hierarchical framework that ranges from more abstract to more concrete levels of identification. A more abstract level of identification involves general, superordinate, and decontextualized mental representations that convey the meaning of goals, events, and actions, “why” an action is performed, and its purpose, ends, and consequences. A more concrete level of identification involves specific and subordinate mental representations that include contextual details of goals, events, and actions, and the specific “how” details of an action. This review considers three lines of evidence for considering that dysregulation of level of goal/action identification may be a transdiagnostic process. First, there is evidence that different levels of identification have distinct functional consequences and that in non-clinical samples level of goal/action identification appears to be regulated in a flexible and adaptive way to match the level of goal/action identification to circumstances. Second, there is evidence that level of goal/action identification causally influences symptoms and processes involved in psychological disorders, including emotional response, repetitive thought, impulsivity, problem solving and procrastination. Third, there is evidence that the level of goal/action identification is biased and/or dysregulated in certain psychological disorders, with a bias towards more abstract identification for negative events in depression, GAD, PTSD, and social anxiety. PMID:20579789

Preon representations and composite models

International Nuclear Information System (INIS)

Kang, Kyungsik

1982-01-01

This is a brief report on the preon models which are investigated by In-Gyu Koh, A. N. Schellekens and myself and based on complex, anomaly-free and asymptotically free representations of SU(3) to SU(8), SO(4N+2) and E 6 with no more than two different preons. Complete list of the representations that are complex anomaly-free and asymptotically free has been given by E. Eichten, I.-G. Koh and myself. The assumptions made about the ground state composites and the role of Fermi statistics to determine the metaflavor wave functions are discussed in some detail. We explain the method of decompositions of tensor products with definite permutation properties which has been developed for this purpose by I.-G. Koh, A.N. Schellekens and myself. An example based on an anomaly-free representation of the confining metacolor group SU(5) is discussed

An introduction to quiver representations

CERN Document Server

Derksen, Harm

2017-01-01

This book is an introduction to the representation theory of quivers and finite dimensional algebras. It gives a thorough and modern treatment of the algebraic approach based on Auslander-Reiten theory as well as the approach based on geometric invariant theory. The material in the opening chapters is developed starting slowly with topics such as homological algebra, Morita equivalence, and Gabriel's theorem. Next, the book presents Auslander-Reiten theory, including almost split sequences and the Auslander-Reiten transform, and gives a proof of Kac's generalization of Gabriel's theorem. Once this basic material is established, the book goes on with developing the geometric invariant theory of quiver representations. The book features the exposition of the saturation theorem for semi-invariants of quiver representations and its application to Littlewood-Richardson coefficients. In the final chapters, the book exposes tilting modules, exceptional sequences and a connection to cluster categories. The book is su...

Conceptual representations in mind and brain: theoretical developments, current evidence and future directions.

Science.gov (United States)

Kiefer, Markus; Pulvermüller, Friedemann

2012-07-01

Conceptual representations in long-term memory crucially contribute to perception and action, language and thought. However, the precise nature of these conceptual memory traces is discussed controversially. In particular, the grounding of concepts in the sensory and motor brain systems is the focus of a current debate. Here, we review theoretical accounts of the structure and neural basis of conceptual memory and evaluate them in light of recent empirical evidence. Models of conceptual processing can be distinguished along four dimensions: (i) amodal versus modality-specific, (ii) localist versus distributed, (iii) innate versus experience-dependent, and (iv) stable versus flexible. A systematic review of behavioral and neuroimaging studies in healthy participants along with brain-damaged patients will then be used to evaluate the competing theoretical approaches to conceptual representations. These findings indicate that concepts are flexible, distributed representations comprised of modality-specific conceptual features. Conceptual features are stored in distinct sensory and motor brain areas depending on specific sensory and motor experiences during concept acquisition. Three important controversial issues are highlighted, which require further clarification in future research: the existence of an amodal conceptual representation in the anterior temporal lobe, the causal role of sensory and motor activation for conceptual processing and the grounding of abstract concepts in perception and action. We argue that an embodiment view of conceptual representations realized as distributed sensory and motor cell assemblies that are complemented by supramodal integration brain circuits may serve as a theoretical framework to guide future research on concrete and abstract concepts. Copyright © 2011 Elsevier Srl. All rights reserved.

Representations of HIV/AIDS management in South African newspapers.

Science.gov (United States)

Campbell, Catherine; Gibbs, Andy

2008-07-01

In South Africa, numerous strong policy statements emphasise the importance of involving communities in HIV/AIDS management, yet in practice such involvement tends to be tokenistic and minimal. Social representations in the public sphere constitute the symbolic dimension within which responses to HIV and AIDS are conceptualised and transformed into action. Through an analysis of newspaper articles, we explore the dominant representations of HIV/AIDS management circulating in the South African public sphere and examine how community engagement is depicted. We highlight the way media representations reflect narrow understandings of HIV and AIDS as a predominantly medical problem, while depicting HIV/AIDS management as a top-down activity dominated by prominent individuals, such as national leaders, health professionals and philanthropists, thus marginalising the role played by communities, who are often depicted as passive recipients of interventions by active outsiders. These representations fail to reflect the key role played by members of grassroots communities in responding to the HIV epidemic. Such representations provide flawed conceptual tools for shaping responses to the epidemic, given that HIV-related programmes are unlikely to have optimal outcomes unless they resonate with the perceived needs and interests of their target communities, as we contend that effective HIV/AIDS management is best achieved through active participation by communities in HIV/AIDS management strategies. We discuss the implications of a more 'civic-minded journalism.'

Emotions as pragmatic and epistemic actions

Science.gov (United States)

Wilutzky, Wendy

2015-01-01

This paper explores the idea that emotions in social contexts and their intentionality may be conceived of as pragmatic or epistemic actions. That is, emotions are often aimed at achieving certain goals within a social context, so that they resemble pragmatic actions; and in other cases emotions can be plausibly construed as acts of probing the social environment so as to extract or uncover important information, thus complying with the functions of epistemic actions (cf. Kirsh and Maglio, 1994). This view of emotions stands at odds with the wide-held conception that emotions' intentionality can be cashed out in terms of representations of value. On such a position, emotions' intentionality has only a mind-to-world direction of fit while any world-to-mind direction of fit is deemed secondary or is even outrightly denied. However, acknowledging that emotions (qua actions) also have a world-to-mind direction fit has several advantages over the typical rendition of emotions as representations of value, such as accounting for emotions' sensitivity to contextual factors, variations in emotion expression and, importantly, assessing the appropriateness of emotional reactions. To substantiate this claim, several cases of emotions in social contexts are discussed, as the social dimension of emotions highlights that emotions are inherently ways of interacting with one's social environment. In sum, the construal of emotions in social contexts as pragmatic or epistemic actions yields a more fine-grained and accurate understanding of emotions' intentionality and their roles in social contexts than the insistence on a purely mind-to-world direction of fit. PMID:26578999

Mirroring "meaningful" actions: sensorimotor learning modulates imitation of goal-directed actions.

Science.gov (United States)

Catmur, Caroline; Heyes, Cecilia

2017-06-19

Imitation is important in the development of social and technological skills throughout the lifespan. Experiments investigating the acquisition and modulation of imitation (and of its proposed neural substrate, the mirror neuron system) have produced evidence that the capacity for imitation depends on associative learning in which connections are formed between sensory and motor representations of actions. However, evidence that the development of imitation depends on associative learning has been found only for non-goal-directed actions. One reason for the lack of research on goal-directed actions is that imitation of such actions is commonly confounded with the tendency to respond in a spatially compatible manner. However, since the most prominent account of mirror neuron function, and hence of imitation, suggests that these cells encode goal-directed actions, it is important to establish whether sensorimotor learning can also modulate imitation of goal-directed actions. Experiment 1 demonstrated that imitation of goal-directed grasping can be measured while controlling for spatial compatibility, and Experiment 2 showed that this imitation effect can be modulated by sensorimotor training. Together these data support the hypothesis that the capacity for behavioural imitation, and the properties of the mirror neuron system, are constructed in the course of development through associative learning.

Interleaved Practice with Multiple Representations: Analyses with Knowledge Tracing Based Techniques

Science.gov (United States)

Rau, Martina A.; Pardos, Zachary A.

2012-01-01

The goal of this paper is to use Knowledge Tracing to augment the results obtained from an experiment that investigated the effects of practice schedules using an intelligent tutoring system for fractions. Specifically, this experiment compared different practice schedules of multiple representations of fractions: representations were presented to…

Potential role of monkey inferior parietal neurons coding action semantic equivalences as precursors of parts of speech.

Science.gov (United States)

Yamazaki, Yumiko; Yokochi, Hiroko; Tanaka, Michio; Okanoya, Kazuo; Iriki, Atsushi

2010-01-01

The anterior portion of the inferior parietal cortex possesses comprehensive representations of actions embedded in behavioural contexts. Mirror neurons, which respond to both self-executed and observed actions, exist in this brain region in addition to those originally found in the premotor cortex. We found that parietal mirror neurons responded differentially to identical actions embedded in different contexts. Another type of parietal mirror neuron represents an inverse and complementary property of responding equally to dissimilar actions made by itself and others for an identical purpose. Here, we propose a hypothesis that these sets of inferior parietal neurons constitute a neural basis for encoding the semantic equivalence of various actions across different agents and contexts. The neurons have mirror neuron properties, and they encoded generalization of agents, differentiation of outcomes, and categorization of actions that led to common functions. By integrating the activities of these mirror neurons with various codings, we further suggest that in the ancestral primates' brains, these various representations of meaningful action led to the gradual establishment of equivalence relations among the different types of actions, by sharing common action semantics. Such differential codings of the components of actions might represent precursors to the parts of protolanguage, such as gestural communication, which are shared among various members of a society. Finally, we suggest that the inferior parietal cortex serves as an interface between this action semantics system and other higher semantic systems, through common structures of action representation that mimic language syntax.

Spatially variant morphological restoration and skeleton representation.

Science.gov (United States)

Bouaynaya, Nidhal; Charif-Chefchaouni, Mohammed; Schonfeld, Dan

2006-11-01

The theory of spatially variant (SV) mathematical morphology is used to extend and analyze two important image processing applications: morphological image restoration and skeleton representation of binary images. For morphological image restoration, we propose the SV alternating sequential filters and SV median filters. We establish the relation of SV median filters to the basic SV morphological operators (i.e., SV erosions and SV dilations). For skeleton representation, we present a general framework for the SV morphological skeleton representation of binary images. We study the properties of the SV morphological skeleton representation and derive conditions for its invertibility. We also develop an algorithm for the implementation of the SV morphological skeleton representation of binary images. The latter algorithm is based on the optimal construction of the SV structuring element mapping designed to minimize the cardinality of the SV morphological skeleton representation. Experimental results show the dramatic improvement in the performance of the SV morphological restoration and SV morphological skeleton representation algorithms in comparison to their translation-invariant counterparts.

Volume-based Representation of the Magnetic Field

CERN Document Server

Amapane, N; Drollinger, V; Karimäki, V; Klyukhin, V; Todorov, T

2005-01-01

Simulation and reconstruction of events in high-energy experiments require the knowledge of the value of the magnetic field at any point within the detector. The way this information is extracted from the actual map of the magnetic field and served to simulation and reconstruction applications has a large impact on accuracy and performance in terms of speed. As an example, the CMS high level trigger performs on-line tracking of muons within the magnet yoke, where the field is discontinuous and largely inhomogeneous. In this case the high level trigger execution time is dominated by the time needed to access the magnetic field map.For this reason, an optimized approach for the access to the CMS field was developed, based on a dedicated representation of thedetector geometry. The detector is modeled in terms of volumes, constructed in such a way that their boundaries correspond to the fiel d discontinuities due to changes in the magnetic permeability of the materials. The field within each volume is therefore c...

AFFIRMATIVE ACTION DI ERA REFORMASI DAN IMPLIKASINYA TERHADAP PEMBANGUNAN BERWAWASAN GENDER

Directory of Open Access Journals (Sweden)

Silvia Hanani

2012-01-01

Full Text Available The low participation and involvement of women in politics has seen some discrimination and injustice against women, because they do not attention development policies are gender oriented. It is well recognized by women in Indonesia, so the post-New Order government women's advocacy movement that gave birth to affirmative action that essentially encourages and guarantees against women to be involved in politics. Significant impact of affirmative action is the birth of a minimal system of representation of women in parliament 30%. This representation system, reinforced in 2009 with the implementation zipper election system, where from 1-3 candidates proposed must be female. But somehow affirmative action, can not be denied as a form be balanced with minimizing the lack of women and men. Keywords : Affirmative action, politics and participation of womenCopyright © 2012 by Kafa`ah All right reservedDOI : 10.15548/jk.v2i1.45

Representational Thickness

DEFF Research Database (Denmark)

Mullins, Michael

Contemporary communicational and informational processes contribute to the shaping of our physical environment by having a powerful influence on the process of design. Applications of virtual reality (VR) are transforming the way architecture is conceived and produced by introducing dynamic...... elements into the process of design. Through its immersive properties, virtual reality allows access to a spatial experience of a computer model very different to both screen based simulations as well as traditional forms of architectural representation. The dissertation focuses on processes of the current...... representation? How is virtual reality used in public participation and how do virtual environments affect participatory decision making? How does VR thus affect the physical world of built environment? Given the practical collaborative possibilities of immersive technology, how can they best be implemented...

The Paradoxical Impact of Globalisation on Women’s Political Representation: A Review of Situations In Southeast Asia

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Nur Azizah

2015-02-01

Full Text Available The representation of women in a political system is a good test of its claims to democracy. Although there are some progress, the level of women political representation in Southeast Asian countries is still low. Women activists propose the adoption of gender quotas as a fast track to address this issue, but the implementation find many obstacles. This article base of my research which want to examine the impact of globalisation for women’s political representation in Southeast Asian countries. The discussion begin with the overview of women’s political representation issue and some theoretical framewoks for adressing that issue. It identified that globalisation has positive and negative impacts on women’s representation. On the one hand, it encourages the emergence of a global gender equality regime which influences pattern of women’s political representation among Southeast Asian countries. Yet, on the otherhand, itpromotes neo-liberalism ideology which is “inherently oppose to policy interventionism”and it also promotes liberal democratic practices, which oppose affirmative policy for women, included gender quota in parliament.We concludes that the paradoxical impact of globalisation causes progress for increasing women’s representation in Southeast Asian countries move slowly. The efforts for increasing women’s representation in some Southeast Asian countries have not been supported by governments’ “intervention” policies such as gender quota and social welfare policies. Southeast Asian countries are also trapped in a liberal democracy practice which promotes ‘one person one vote’ (equality of opportunity. Thus, the opposition to affirmative action (equality of result is so high. Although some Southeast Asian countries have women quota articles, the implementation has been undermined so far.

Contingent sounds change the mental representation of one's finger length.

Science.gov (United States)

Tajadura-Jiménez, Ana; Vakali, Maria; Fairhurst, Merle T; Mandrigin, Alisa; Bianchi-Berthouze, Nadia; Deroy, Ophelia

2017-07-18

Mental body-representations are highly plastic and can be modified after brief exposure to unexpected sensory feedback. While the role of vision, touch and proprioception in shaping body-representations has been highlighted by many studies, the auditory influences on mental body-representations remain poorly understood. Changes in body-representations by the manipulation of natural sounds produced when one's body impacts on surfaces have recently been evidenced. But will these changes also occur with non-naturalistic sounds, which provide no information about the impact produced by or on the body? Drawing on the well-documented capacity of dynamic changes in pitch to elicit impressions of motion along the vertical plane and of changes in object size, we asked participants to pull on their right index fingertip with their left hand while they were presented with brief sounds of rising, falling or constant pitches, and in the absence of visual information of their hands. Results show an "auditory Pinocchio" effect, with participants feeling and estimating their finger to be longer after the rising pitch condition. These results provide the first evidence that sounds that are not indicative of veridical movement, such as non-naturalistic sounds, can induce a Pinocchio-like change in body-representation when arbitrarily paired with a bodily action.

A measurement perspective on affirmative action in U.S. medical education

Directory of Open Access Journals (Sweden)

Clarence D. Kreiter

2013-04-01

Full Text Available Background: The U.S. Supreme Court has recently heard another affirmative action case, and similar programs to promote equitable representation in higher education are being debated and enacted around the world. Understanding the empirical and quantitative research conducted over the last 50 years is important in designing effective and fair initiatives related to affirmative action in medical education. Unfortunately, the quantitative measurement research relevant to affirmative action is poorly documented in the scholarly journals that serve medical education. Methods: This research organizes and documents the measurement literature relevant to enacting affirmative action within the medical school environment, and should be valuable for informing future actions. It provides summaries of those areas where the research evidence is strong and highlights areas where more research evidence is needed. To structure the presentation, 10 topic areas are identified in the form of research questions. Results: Measurement evidence related to these questions is reviewed and summarized to provide evidence-based answers. Conclusions: These answers should provide a useful foundation for making important decisions regarding the use of racial diversity initiatives in medical education.

Global representations of the Heat and Schrodinger equation with singular potential

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Jose A. Franco

2013-07-01

Full Text Available The n-dimensional Schrodinger equation with a singular potential $V_lambda(x=lambda |x|^{-2}$ is studied. Its solution space is studied as a global representation of $widetilde{SL(2,mathbb{R}}imes O(n$. A special subspace of solutions for which the action globalizes is constructed via nonstandard induction outside the semisimple category. The space of K-finite vectors is calculated, obtaining conditions for $lambda$ so that this space is non-empty. The direct sum of solution spaces over such admissible values of $lambda$ is studied as a representation of the (2n+1-dimensional Heisenberg group.

Robust Face Recognition Via Gabor Feature and Sparse Representation

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Hao Yu-Juan

2016-01-01

Full Text Available Sparse representation based on compressed sensing theory has been widely used in the field of face recognition, and has achieved good recognition results. but the face feature extraction based on sparse representation is too simple, and the sparse coefficient is not sparse. In this paper, we improve the classification algorithm based on the fusion of sparse representation and Gabor feature, and then improved algorithm for Gabor feature which overcomes the problem of large dimension of the vector dimension, reduces the computation and storage cost, and enhances the robustness of the algorithm to the changes of the environment.The classification efficiency of sparse representation is determined by the collaborative representation,we simplify the sparse constraint based on L1 norm to the least square constraint, which makes the sparse coefficients both positive and reduce the complexity of the algorithm. Experimental results show that the proposed method is robust to illumination, facial expression and pose variations of face recognition, and the recognition rate of the algorithm is improved.

Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA.

Science.gov (United States)

Wang, Shunfang; Liu, Shuhui

2015-12-19

An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC), pseudo-amino acid composition (PseAAC) and position specific scoring matrix (PSSM), are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA) is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

Imaging When Acting: Picture but Not Word Cues Induce Action-Related Biases of Visual Attention

Science.gov (United States)

Wykowska, Agnieszka; Hommel, Bernhard; Schubö, Anna

2012-01-01

In line with the Theory of Event Coding (Hommel et al., 2001a), action planning has been shown to affect perceptual processing – an effect that has been attributed to a so-called intentional weighting mechanism (Wykowska et al., 2009; Memelink and Hommel, 2012), whose functional role is to provide information for open parameters of online action adjustment (Hommel, 2010). The aim of this study was to test whether different types of action representations induce intentional weighting to various degrees. To meet this aim, we introduced a paradigm in which participants performed a visual search task while preparing to grasp or to point. The to-be performed movement was signaled either by a picture of a required action or a word cue. We reasoned that picture cues might trigger a more concrete action representation that would be more likely to activate the intentional weighting of perceptual dimensions that provide information for online action control. In contrast, word cues were expected to trigger a more abstract action representation that would be less likely to induce intentional weighting. In two experiments, preparing for an action facilitated the processing of targets in an unrelated search task if they differed from distractors on a dimension that provided information for online action control. As predicted, however, this effect was observed only if action preparation was signaled by picture cues but not if it was signaled by word cues. We conclude that picture cues are more efficient than word cues in activating the intentional weighting of perceptual dimensions, presumably by specifying not only invariant characteristics of the planned action but also the dimensions of action-specific parameters. PMID:23087656

Imaging when acting: picture but not word cues induce action-related biases of visual attention.

Science.gov (United States)

Wykowska, Agnieszka; Hommel, Bernhard; Schubö, Anna

2012-01-01

In line with the Theory of Event Coding (Hommel et al., 2001a), action planning has been shown to affect perceptual processing - an effect that has been attributed to a so-called intentional weighting mechanism (Wykowska et al., 2009; Memelink and Hommel, 2012), whose functional role is to provide information for open parameters of online action adjustment (Hommel, 2010). The aim of this study was to test whether different types of action representations induce intentional weighting to various degrees. To meet this aim, we introduced a paradigm in which participants performed a visual search task while preparing to grasp or to point. The to-be performed movement was signaled either by a picture of a required action or a word cue. We reasoned that picture cues might trigger a more concrete action representation that would be more likely to activate the intentional weighting of perceptual dimensions that provide information for online action control. In contrast, word cues were expected to trigger a more abstract action representation that would be less likely to induce intentional weighting. In two experiments, preparing for an action facilitated the processing of targets in an unrelated search task if they differed from distractors on a dimension that provided information for online action control. As predicted, however, this effect was observed only if action preparation was signaled by picture cues but not if it was signaled by word cues. We conclude that picture cues are more efficient than word cues in activating the intentional weighting of perceptual dimensions, presumably by specifying not only invariant characteristics of the planned action but also the dimensions of action-specific parameters.

Paired structures in knowledge representation

DEFF Research Database (Denmark)

Montero, J.; Bustince, H.; Franco de los Ríos, Camilo

2016-01-01

In this position paper we propose a consistent and unifying view to all those basic knowledge representation models that are based on the existence of two somehow opposite fuzzy concepts. A number of these basic models can be found in fuzzy logic and multi-valued logic literature. Here...... of the relationships between several existing knowledge representation formalisms, providing a basis from which more expressive models can be later developed....

Efficient Online Aggregates in Dense-Region-Based Data Cube Representations

Science.gov (United States)

Haddadin, Kais; Lauer, Tobias

In-memory OLAP systems require a space-efficient representation of sparse data cubes in order to accommodate large data sets. On the other hand, most efficient online aggregation techniques, such as prefix sums, are built on dense array-based representations. These are often not applicable to real-world data due to the size of the arrays which usually cannot be compressed well, as most sparsity is removed during pre-processing. A possible solution is to identify dense regions in a sparse cube and only represent those using arrays, while storing sparse data separately, e.g. in a spatial index structure. Previous dense-region-based approaches have concentrated mainly on the effectiveness of the dense-region detection (i.e. on the space-efficiency of the result). However, especially in higher-dimensional cubes, data is usually more cluttered, resulting in a potentially large number of small dense regions, which negatively affects query performance on such a structure. In this paper, our focus is not only on space-efficiency but also on time-efficiency, both for the initial dense-region extraction and for queries carried out in the resulting hybrid data structure. We describe two methods to trade available memory for increased aggregate query performance. In addition, optimizations in our approach significantly reduce the time to build the initial data structure compared to former systems. Also, we present a straightforward adaptation of our approach to support multi-core or multi-processor architectures, which can further enhance query performance. Experiments with different real-world data sets show how various parameter settings can be used to adjust the efficiency and effectiveness of our algorithms.

Prediction Error During Functional and Non-Functional Action Sequences

DEFF Research Database (Denmark)

Nielbo, Kristoffer Laigaard; Sørensen, Jesper

2013-01-01

recurrent networks were made and the results are presented in this article. The simulations show that non-functional action sequences do indeed increase prediction error, but that context representations, such as abstract goal information, can modulate the error signal considerably. It is also shown...... that the networks are sensitive to boundaries between sequences in both functional and non-functional actions....

Exemplar-based human action pose correction.

Science.gov (United States)

Shen, Wei; Deng, Ke; Bai, Xiang; Leyvand, Tommer; Guo, Baining; Tu, Zhuowen

2014-07-01

The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. In this paper, we propose an exemplar-based method to learn to correct the initially estimated poses. We learn an inhomogeneous systematic bias by leveraging the exemplar information within a specific human action domain. Furthermore, as an extension, we learn a conditional model by incorporation of pose tags to further increase the accuracy of pose correction. In the experiments, significant improvements on both joint-based skeleton correction and tag prediction are observed over the contemporary approaches, including what is delivered by the current Kinect system. Our experiments for the facial landmark correction also illustrate that our algorithm can improve the accuracy of other detection/estimation systems.

Aspect-Aided Dynamic Non-Negative Sparse Representation-Based Microwave Image Classification

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Xinzheng Zhang

2016-09-01

Full Text Available Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ 1 -regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance.

The robust corrective action priority-an improved approach for selecting competing corrective actions in FMEA based on principle of robust design

Science.gov (United States)

Sutrisno, Agung; Gunawan, Indra; Vanany, Iwan

2017-11-01

In spite of being integral part in risk - based quality improvement effort, studies improving quality of selection of corrective action priority using FMEA technique are still limited in literature. If any, none is considering robustness and risk in selecting competing improvement initiatives. This study proposed a theoretical model to select risk - based competing corrective action by considering robustness and risk of competing corrective actions. We incorporated the principle of robust design in counting the preference score among corrective action candidates. Along with considering cost and benefit of competing corrective actions, we also incorporate the risk and robustness of corrective actions. An example is provided to represent the applicability of the proposed model.

A communication-channel-based representation system for software

NARCIS (Netherlands)

Demirezen, Zekai; Tanik, Murat M.; Aksit, Mehmet; Skjellum, Anthony

We observed that before initiating software development the objectives are minimally organized and developers introduce comparatively higher organization throughout the design process. To be able to formally capture this observation, a new communication channel representation system for software is

Tensor-based cortical surface morphometry via weighted spherical harmonic representation.

Science.gov (United States)

Chung, Moo K; Dalton, Kim M; Davidson, Richard J

2008-08-01

We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects.

Inequivalent coherent state representations in group field theory

Science.gov (United States)

Kegeles, Alexander; Oriti, Daniele; Tomlin, Casey

2018-06-01

In this paper we propose an algebraic formulation of group field theory and consider non-Fock representations based on coherent states. We show that we can construct representations with an infinite number of degrees of freedom on compact manifolds. We also show that these representations break translation symmetry. Since such representations can be regarded as quantum gravitational systems with an infinite number of fundamental pre-geometric building blocks, they may be more suitable for the description of effective geometrical phases of the theory.

Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA

Directory of Open Access Journals (Sweden)

Shunfang Wang

2015-12-01

Full Text Available An effective representation of a protein sequence plays a crucial role in protein sub-nuclear localization. The existing representations, such as dipeptide composition (DipC, pseudo-amino acid composition (PseAAC and position specific scoring matrix (PSSM, are insufficient to represent protein sequence due to their single perspectives. Thus, this paper proposes two fusion feature representations of DipPSSM and PseAAPSSM to integrate PSSM with DipC and PseAAC, respectively. When constructing each fusion representation, we introduce the balance factors to value the importance of its components. The optimal values of the balance factors are sought by genetic algorithm. Due to the high dimensionality of the proposed representations, linear discriminant analysis (LDA is used to find its important low dimensional structure, which is essential for classification and location prediction. The numerical experiments on two public datasets with KNN classifier and cross-validation tests showed that in terms of the common indexes of sensitivity, specificity, accuracy and MCC, the proposed fusing representations outperform the traditional representations in protein sub-nuclear localization, and the representation treated by LDA outperforms the untreated one.

Knowledge representation to support reasoning based on multiple models

Science.gov (United States)

Gillam, April; Seidel, Jorge P.; Parker, Alice C.

1990-01-01

Model Based Reasoning is a powerful tool used to design and analyze systems, which are often composed of numerous interactive, interrelated subsystems. Models of the subsystems are written independently and may be used together while they are still under development. Thus the models are not static. They evolve as information becomes obsolete, as improved artifact descriptions are developed, and as system capabilities change. Researchers are using three methods to support knowledge/data base growth, to track the model evolution, and to handle knowledge from diverse domains. First, the representation methodology is based on having pools, or types, of knowledge from which each model is constructed. In addition information is explicit. This includes the interactions between components, the description of the artifact structure, and the constraints and limitations of the models. The third principle we have followed is the separation of the data and knowledge from the inferencing and equation solving mechanisms. This methodology is used in two distinct knowledge-based systems: one for the design of space systems and another for the synthesis of VLSI circuits. It has facilitated the growth and evolution of our models, made accountability of results explicit, and provided credibility for the user community. These capabilities have been implemented and are being used in actual design projects.

Learning to Act: Qualitative Learning of Deterministic Action Models

DEFF Research Database (Denmark)

Bolander, Thomas; Gierasimczuk, Nina

2017-01-01

In this article we study learnability of fully observable, universally applicable action models of dynamic epistemic logic. We introduce a framework for actions seen as sets of transitions between propositional states and we relate them to their dynamic epistemic logic representations as action...... in the limit (inconclusive convergence to the right action model). We show that deterministic actions are finitely identifiable, while arbitrary (non-deterministic) actions require more learning power—they are identifiable in the limit. We then move on to a particular learning method, i.e. learning via update......, which proceeds via restriction of a space of events within a learning-specific action model. We show how this method can be adapted to learn conditional and unconditional deterministic action models. We propose update learning mechanisms for the afore mentioned classes of actions and analyse...

Computational Model of Primary Visual Cortex Combining Visual Attention for Action Recognition.

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Na Shu

Full Text Available Humans can easily understand other people's actions through visual systems, while computers cannot. Therefore, a new bio-inspired computational model is proposed in this paper aiming for automatic action recognition. The model focuses on dynamic properties of neurons and neural networks in the primary visual cortex (V1, and simulates the procedure of information processing in V1, which consists of visual perception, visual attention and representation of human action. In our model, a family of the three-dimensional spatial-temporal correlative Gabor filters is used to model the dynamic properties of the classical receptive field of V1 simple cell tuned to different speeds and orientations in time for detection of spatiotemporal information from video sequences. Based on the inhibitory effect of stimuli outside the classical receptive field caused by lateral connections of spiking neuron networks in V1, we propose surround suppressive operator to further process spatiotemporal information. Visual attention model based on perceptual grouping is integrated into our model to filter and group different regions. Moreover, in order to represent the human action, we consider the characteristic of the neural code: mean motion map based on analysis of spike trains generated by spiking neurons. The experimental evaluation on some publicly available action datasets and comparison with the state-of-the-art approaches demonstrate the superior performance of the proposed model.

Optimal Meter Placement for Distribution Network State Estimation: A Circuit Representation Based MILP Approach

DEFF Research Database (Denmark)

Chen, Xiaoshuang; Lin, Jin; Wan, Can

2016-01-01

State estimation (SE) in distribution networks is not as accurate as that in transmission networks. Traditionally, distribution networks (DNs) are lack of direct measurements due to the limitations of investments and the difficulties of maintenance. Therefore, it is critical to improve the accuracy...... of SE in distribution networks by placing additional physical meters. For state-of-the-art SE models, it is difficult to clearly quantify measurements' influences on SE errors, so the problems of optimal meter placement for reducing SE errors are mostly solved by heuristic or suboptimal algorithms....... Under this background, this paper proposes a circuit representation model to represent SE errors. Based on the matrix formulation of the circuit representation model, the problem of optimal meter placement can be transformed to a mixed integer linear programming problem (MILP) via the disjunctive model...

Exploring the bases for a mixed reality stroke rehabilitation system, Part I: A unified approach for representing action, quantitative evaluation, and interactive feedback

Science.gov (United States)

2011-01-01

Background Although principles based in motor learning, rehabilitation, and human-computer interfaces can guide the design of effective interactive systems for rehabilitation, a unified approach that connects these key principles into an integrated design, and can form a methodology that can be generalized to interactive stroke rehabilitation, is presently unavailable. Results This paper integrates phenomenological approaches to interaction and embodied knowledge with rehabilitation practices and theories to achieve the basis for a methodology that can support effective adaptive, interactive rehabilitation. Our resulting methodology provides guidelines for the development of an action representation, quantification of action, and the design of interactive feedback. As Part I of a two-part series, this paper presents key principles of the unified approach. Part II then describes the application of this approach within the implementation of the Adaptive Mixed Reality Rehabilitation (AMRR) system for stroke rehabilitation. Conclusions The accompanying principles for composing novel mixed reality environments for stroke rehabilitation can advance the design and implementation of effective mixed reality systems for the clinical setting, and ultimately be adapted for home-based application. They furthermore can be applied to other rehabilitation needs beyond stroke. PMID:21875441

Social representations of the health care of the Mbyá-Guarani indigenous population by health workers 1

Science.gov (United States)

Falkenberg, Mirian Benites; Shimizu, Helena Eri; Bermudez, Ximena Pamela Díaz

2017-01-01

ABSTRACT Objective: to analyze the social representations of health care of the Mbyá-Guarani ethnic group by multidisciplinary teams from the Special Indigenous Health District in the south coast of Rio Grande do Sul state (Distrito Sanitário Especial Indígena Litoral Sul do Rio Grande do Sul), Brazil. Method: a qualitative method based on the theory of social representations was used. Data were collected via semi-structured interviews with 20 health workers and by participant observation. The interviews were analyzed with ALCESTE software, which conducts a lexical content analysis using quantitative techniques for the treatment of textual data. Results: there were disagreements in the health care concepts and practices between traditional medicine and biomedicine; however, some progress has been achieved in the area of intermedicality. The ethnic boundaries established between health workers and indigenous peoples based on their representations of culture and family, together with the lack of infrastructure and organization of health actions, are perceived as factors that hinder health care in an intercultural context. Conclusion: a new basis for the process of indigenous health care needs to be established by understanding the needs identified and by agreement among individuals, groups, and health professionals via intercultural exchange. PMID:28177056

A Constrained Algorithm Based NMFα for Image Representation

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Chenxue Yang

2014-01-01

Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.

A neural network model of semantic memory linking feature-based object representation and words.

Science.gov (United States)

Cuppini, C; Magosso, E; Ursino, M

2009-06-01

Recent theories in cognitive neuroscience suggest that semantic memory is a distributed process, which involves many cortical areas and is based on a multimodal representation of objects. The aim of this work is to extend a previous model of object representation to realize a semantic memory, in which sensory-motor representations of objects are linked with words. The model assumes that each object is described as a collection of features, coded in different cortical areas via a topological organization. Features in different objects are segmented via gamma-band synchronization of neural oscillators. The feature areas are further connected with a lexical area, devoted to the representation of words. Synapses among the feature areas, and among the lexical area and the feature areas are trained via a time-dependent Hebbian rule, during a period in which individual objects are presented together with the corresponding words. Simulation results demonstrate that, during the retrieval phase, the network can deal with the simultaneous presence of objects (from sensory-motor inputs) and words (from acoustic inputs), can correctly associate objects with words and segment objects even in the presence of incomplete information. Moreover, the network can realize some semantic links among words representing objects with shared features. These results support the idea that semantic memory can be described as an integrated process, whose content is retrieved by the co-activation of different multimodal regions. In perspective, extended versions of this model may be used to test conceptual theories, and to provide a quantitative assessment of existing data (for instance concerning patients with neural deficits).

Object-Action Complexes: Grounded Abstractions of Sensori-motor Processes

DEFF Research Database (Denmark)

Krüger, Norbert; Geib, Christopher; Piater, Justus

2011-01-01

This paper formalises Object-Action Complexes (OACs) as a basis for symbolic representations of sensorimotor experience and behaviours. OACs are designed to capture the interaction between objects and associated actions in articial cognitive systems. This paper gives a formal denition of OACs, pr......, provides examples of their use for autonomous cognitive robots, and enumerates a number of critical learning problems in terms of OACs....

Mental Representations Formed From Educational Website Formats

Energy Technology Data Exchange (ETDEWEB)

Elizabeth T. Cady; Kimberly R. Raddatz; Tuan Q. Tran; Bernardo de la Garza; Peter D. Elgin

2006-10-01

The increasing popularity of web-based distance education places high demand on distance educators to format web pages to facilitate learning. However, limited guidelines exist regarding appropriate writing styles for web-based distance education. This study investigated the effect of four different writing styles on reader’s mental representation of hypertext. Participants studied hypertext written in one of four web-writing styles (e.g., concise, scannable, objective, and combined) and were then administered a cued association task intended to measure their mental representations of the hypertext. It is hypothesized that the scannable and combined styles will bias readers to scan rather than elaborately read, which may result in less dense mental representations (as identified through Pathfinder analysis) relative to the objective and concise writing styles. Further, the use of more descriptors in the objective writing style will lead to better integration of ideas and more dense mental representations than the concise writing style.

The Political Representation of Women in Public Policy Management Councils

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Lígia Helena Hahn Lüchmann

2010-06-01

Full Text Available This work raises some hypotheses to explain the significant presence of women on public policy management councils, which are spaces for discussion and deliberation of policies that have been implemented in Brazil in recent decades. The data about the profile of representatives on these spaces indicates a situation inversely proportional to the low degree of political inclusion of women in traditional spaces of political representation – executive positions, city councils, and state legislatures. There is thus a need to develop new analytical tools to understand the phenomenon of political representation. The data also question a reductive perspective of action and politics, which concludes that there is a low degree of political inclusion of women.

The Effect of Project-Based Learning on Students' Statistical Literacy Levels for Data Representation

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Koparan, Timur; Güven, Bülent

2015-01-01

The point of this study is to define the effect of project-based learning approach on 8th Grade secondary-school students' statistical literacy levels for data representation. To achieve this goal, a test which consists of 12 open-ended questions in accordance with the views of experts was developed. Seventy 8th grade secondary-school students, 35…

The semantic representation of prejudice and stereotypes.

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Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

Efficient generation of sum-of-products representations of high-dimensional potential energy surfaces based on multimode expansions

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Ziegler, Benjamin; Rauhut, Guntram

2016-03-01

The transformation of multi-dimensional potential energy surfaces (PESs) from a grid-based multimode representation to an analytical one is a standard procedure in quantum chemical programs. Within the framework of linear least squares fitting, a simple and highly efficient algorithm is presented, which relies on a direct product representation of the PES and a repeated use of Kronecker products. It shows the same scalings in computational cost and memory requirements as the potfit approach. In comparison to customary linear least squares fitting algorithms, this corresponds to a speed-up and memory saving by several orders of magnitude. Different fitting bases are tested, namely, polynomials, B-splines, and distributed Gaussians. Benchmark calculations are provided for the PESs of a set of small molecules.

Quantum Computation-Based Image Representation, Processing Operations and Their Applications

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Fei Yan

2014-10-01

Full Text Available A flexible representation of quantum images (FRQI was proposed to facilitate the extension of classical (non-quantum-like image processing applications to the quantum computing domain. The representation encodes a quantum image in the form of a normalized state, which captures information about colors and their corresponding positions in the images. Since its conception, a handful of processing transformations have been formulated, among which are the geometric transformations on quantum images (GTQI and the CTQI that are focused on the color information of the images. In addition, extensions and applications of FRQI representation, such as multi-channel representation for quantum images (MCQI, quantum image data searching, watermarking strategies for quantum images, a framework to produce movies on quantum computers and a blueprint for quantum video encryption and decryption have also been suggested. These proposals extend classical-like image and video processing applications to the quantum computing domain and offer a significant speed-up with low computational resources in comparison to performing the same tasks on traditional computing devices. Each of the algorithms and the mathematical foundations for their execution were simulated using classical computing resources, and their results were analyzed alongside other classical computing equivalents. The work presented in this review is intended to serve as the epitome of advances made in FRQI quantum image processing over the past five years and to simulate further interest geared towards the realization of some secure and efficient image and video processing applications on quantum computers.

A Generalized Pyramid Matching Kernel for Human Action Recognition in Realistic Videos

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Wenjun Zhang

2013-10-01

Full Text Available Human action recognition is an increasingly important research topic in the fields of video sensing, analysis and understanding. Caused by unconstrained sensing conditions, there exist large intra-class variations and inter-class ambiguities in realistic videos, which hinder the improvement of recognition performance for recent vision-based action recognition systems. In this paper, we propose a generalized pyramid matching kernel (GPMK for recognizing human actions in realistic videos, based on a multi-channel “bag of words” representation constructed from local spatial-temporal features of video clips. As an extension to the spatial-temporal pyramid matching (STPM kernel, the GPMK leverages heterogeneous visual cues in multiple feature descriptor types and spatial-temporal grid granularity levels, to build a valid similarity metric between two video clips for kernel-based classification. Instead of the predefined and fixed weights used in STPM, we present a simple, yet effective, method to compute adaptive channel weights of GPMK based on the kernel target alignment from training data. It incorporates prior knowledge and the data-driven information of different channels in a principled way. The experimental results on three challenging video datasets (i.e., Hollywood2, Youtube and HMDB51 validate the superiority of our GPMK w.r.t. the traditional STPM kernel for realistic human action recognition and outperform the state-of-the-art results in the literature.

Abstract Representations of Object-Directed Action in the Left Inferior Parietal Lobule.

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Chen, Quanjing; Garcea, Frank E; Jacobs, Robert A; Mahon, Bradford Z

2018-06-01

Prior neuroimaging and neuropsychological research indicates that the left inferior parietal lobule in the human brain is a critical substrate for representing object manipulation knowledge. In the present functional MRI study we used multivoxel pattern analyses to test whether action similarity among objects can be decoded in the inferior parietal lobule independent of the task applied to objects (identification or pantomime) and stimulus format in which stimuli are presented (pictures or printed words). Participants pantomimed the use of objects, cued by printed words, or identified pictures of objects. Classifiers were trained and tested across task (e.g., training data: pantomime; testing data: identification), stimulus format (e.g., training data: word format; testing format: picture) and specific objects (e.g., training data: scissors vs. corkscrew; testing data: pliers vs. screwdriver). The only brain region in which action relations among objects could be decoded across task, stimulus format and objects was the inferior parietal lobule. By contrast, medial aspects of the ventral surface of the left temporal lobe represented object function, albeit not at the same level of abstractness as actions in the inferior parietal lobule. These results suggest compulsory access to abstract action information in the inferior parietal lobe even when simply identifying objects.

The ERP Effects of Combined Cognitive Training on Intention-based and Stimulus-based Actions in Older Chinese Adults

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Ya-Nan Niu

2016-10-01

Full Text Available Age-related decreases in action are caused by neuromuscular weakness and cognitive decline. Although physical interventions have been reported to have beneficial effects on cognitive function in older adults, whether cognitive training improves action-related function remains unclear. In this study, we investigated the effects of combined cognitive training on intention-based and stimulus-based actions in older adults using event-related potentials (ERPs. A total of 26 healthy older adults (16 in the training group and 10 in the control group participated in the study. The training group received 16 sessions of cognitive training, including 8 sessions of executive function training and 8 sessions of memory strategy training. Before and after training, both groups of participants underwent cognitive assessments and ERP recordings during both the acquisition and test phases with a motor cognitive paradigm. During the acquisition phase, subjects were asked to press one of two keys, either using a self-selected (intention-based method or based on the preceding stimulus (stimulus-based. During the test phase, subjects were asked to respond to the pre-cues with either congruent or incongruent tasks. Using ERP indices—including readiness potential, P3 and contingent negative variation to identify motor preparation, stimulus processing and interference effect, respectively—we revealed the effects of training on both intention-based and stimulus-based actions. The correlations were also computed between the improved cognitive performance and the ERP amplitudes. It was shown that the improved executive function might extend substantial benefits to both actions, whereas associative memory may be specifically related to the bidirectional action-effect association of intention-based action, although the training effect of memory was absent during the insufficient training hours. In sum, the present study provided empirical evidence demonstrating that

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

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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).

When action is not enough: tool-use reveals tactile-dependent access to Body Schema.

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Cardinali, L; Brozzoli, C; Urquizar, C; Salemme, R; Roy, A C; Farnè, A

2011-11-01

Proper motor control of our own body implies a reliable representation of body parts. This information is supposed to be stored in the Body Schema (BS), a body representation that appears separate from a more perceptual body representation, the Body Image (BI). The dissociation between BS for action and BI for perception, originally based on neuropsychological evidence, has recently become the focus of behavioural studies in physiological conditions. By inducing the rubber hand illusion in healthy participants, Kammers et al. (2009) showed perceptual changes attributable to the BI to which the BS, as indexed via motor tasks, was immune. To more definitively support the existence of dissociable body representations in physiological conditions, here we tested for the opposite dissociation, namely, whether a tool-use paradigm would induce a functional update of the BS (via a motor localization task) without affecting the BI (via a perceptual localization task). Healthy subjects were required to localize three anatomical landmarks on their right arm, before and after using the same arm to control a tool. In addition to this classical task-dependency approach, we assessed whether preferential access to the BS could also depend upon the way positional information about forearm targets is provided, to subsequently execute the same task. To this aim, participants performed either verbally or tactually driven versions of the motor and perceptual localization tasks. Results showed that both the motor and perceptual tasks were sensitive to the update of the forearm representation, but only when the localization task (perceptual or motor) was driven by a tactile input. This pattern reveals that the motor output is not sufficient per se, but has to be coupled with tactually mediated information to guarantee access to the BS. These findings shade a new light on the action-perception models of body representations and underlie how functional plasticity may be a useful tool to

Representations and processes of human spatial competence.

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Gunzelmann, Glenn; Lyon, Don R

2011-10-01

This article presents an approach to understanding human spatial competence that focuses on the representations and processes of spatial cognition and how they are integrated with cognition more generally. The foundational theoretical argument for this research is that spatial information processing is central to cognition more generally, in the sense that it is brought to bear ubiquitously to improve the adaptivity and effectiveness of perception, cognitive processing, and motor action. We describe research spanning multiple levels of complexity to understand both the detailed mechanisms of spatial cognition, and how they are utilized in complex, naturalistic tasks. In the process, we discuss the critical role of cognitive architectures in developing a consistent account that spans this breadth, and we note some areas in which the current version of a popular architecture, ACT-R, may need to be augmented. Finally, we suggest a framework for understanding the representations and processes of spatial competence and their role in human cognition generally. Copyright © 2011 Cognitive Science Society, Inc.

How initial representations shape coupled learning processes

DEFF Research Database (Denmark)

Puranam, Phanish; Swamy, M.

2016-01-01

Coupled learning processes, in which specialists from different domains learn how to make interdependent choices among alternatives, are common in organizations. We explore the role played by initial representations held by the learners in coupled learning processes using a formal agent-based model....... We find that initial representations have important consequences for the success of the coupled learning process, particularly when communication is constrained and individual rates of learning are high. Under these conditions, initial representations that generate incorrect beliefs can outperform...... one that does not discriminate among alternatives, or even a mix of correct and incorrect representations among the learners. We draw implications for the design of coupled learning processes in organizations. © 2016 INFORMS....

The foundation of Piaget's theories: mental and physical action.

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Beilin, H; Fireman, G

1999-01-01

Piaget's late theory of action and action implication was the realization of a long history of development. A review of that history shows the central place of action in all of his theoretical assertions, despite the waxing and waning of other important features of his theories. Action was said to be the primary source of knowledge with perception and language in secondary roles. Action is for the most part not only organized but there is logic in action. Action, which is at first physical, becomes internalized and transformed into mental action and mental representation, largely in the development of the symbolic or semiotic function in the sensorimotor period. A number of alternative theories of cognitive development place primary emphasis on mental representation. Piaget provided it with an important place as well, but subordinated it to mental action in the form of operations. In this, as Russell claims, he paralleled Schopenhauer's distinction between representation and will. Piaget's theory of action was intimately related to the gradual development of intentionality in childhood. Intentions were tied to actions by way of the conscious awareness of goals and the means to achieve them. Mental action, following the sensorimotor period, was limited in its logical form to semilogical or one-way functions. These forms were said by Piaget to lack logical reversibility, which was achieved only in the sixth or seventh year, in concrete operations. Mental action was not to be fully realized until the development of formal operations, with hypothetical reasoning, in adolescence, according to the classical Piagetian formulation. This view of the child's logical development, which relied heavily on truth-table (extensional) logic, underwent a number of changes. First from the addition of other logics: category theory and the theory of functions among them. In his last theory, however, an even more radical change occurred. With the collaboration of R. Garcia, he proposed

Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

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YANG Zhaoxia

2015-07-01

Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

Just do it: action-dependent learning allows sensory prediction.

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Itai Novick

Full Text Available Sensory-motor learning is commonly considered as a mapping process, whereby sensory information is transformed into the motor commands that drive actions. However, this directional mapping, from inputs to outputs, is part of a loop; sensory stimuli cause actions and vice versa. Here, we explore whether actions affect the understanding of the sensory input that they cause. Using a visuo-motor task in humans, we demonstrate two types of learning-related behavioral effects. Stimulus-dependent effects reflect stimulus-response learning, while action-dependent effects reflect a distinct learning component, allowing the brain to predict the forthcoming sensory outcome of actions. Together, the stimulus-dependent and the action-dependent learning components allow the brain to construct a complete internal representation of the sensory-motor loop.

Decision Making under Uncertainty: A Neural Model based on Partially Observable Markov Decision Processes

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Rajesh P N Rao

2010-11-01

Full Text Available A fundamental problem faced by animals is learning to select actions based on noisy sensory information and incomplete knowledge of the world. It has been suggested that the brain engages in Bayesian inference during perception but how such probabilistic representations are used to select actions has remained unclear. Here we propose a neural model of action selection and decision making based on the theory of partially observable Markov decision processes (POMDPs. Actions are selected based not on a single optimal estimate of state but on the posterior distribution over states (the belief state. We show how such a model provides a unified framework for explaining experimental results in decision making that involve both information gathering and overt actions. The model utilizes temporal difference (TD learning for maximizing expected reward. The resulting neural architecture posits an active role for the neocortex in belief computation while ascribing a role to the basal ganglia in belief representation, value computation, and action selection. When applied to the random dots motion discrimination task, model neurons representing belief exhibit responses similar to those of LIP neurons in primate neocortex. The appropriate threshold for switching from information gathering to overt actions emerges naturally during reward maximization. Additionally, the time course of reward prediction error in the model shares similarities with dopaminergic responses in the basal ganglia during the random dots task. For tasks with a deadline, the model learns a decision making strategy that changes with elapsed time, predicting a collapsing decision threshold consistent with some experimental studies. The model provides a new framework for understanding neural decision making and suggests an important role for interactions between the neocortex and the basal ganglia in learning the mapping between probabilistic sensory representations and actions that maximize

Interacting Brain Modules for Memory: An Adaptive Representations Architecture

Science.gov (United States)

2008-06-01

and sensory preconditioning, which depend on compressing together the representations of conditioned stimulus and context and/or co-occurring cues...learning and rewarded behavior, partly because of clear evidence of their key role in drugs of addiction (DiChiara, 1999), and because they are among the...Approach of this sort is a Pavlovian response---it is like a pre-wired action inspired by novelty (and also reward prediction). Theoretical

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

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Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

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Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

The influence of action-effect anticipation on bistable perception: Differences between onset rivalry and ambiguous motion

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Dogge, M.; Gayet, S.; Custers, R.; Aarts, H.A.G.

2018-01-01

Perception is strongly shaped by the actions we perform. According to the theory of event coding, and forward models of motor control, goal-directed action preparation activates representations of desired effects. These expectations about the precise stimulus identity of one's action-outcomes (i.e.

General regression and representation model for classification.

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Jianjun Qian

Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

Dissociating action-effect activation and effect-based response selection.

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Schwarz, Katharina A; Pfister, Roland; Wirth, Robert; Kunde, Wilfried

2018-05-25

Anticipated action effects have been shown to govern action selection and initiation, as described in ideomotor theory, and they have also been demonstrated to determine crosstalk between different tasks in multitasking studies. Such effect-based crosstalk was observed not only in a forward manner (with a first task influencing performance in a following second task) but also in a backward manner (the second task influencing the preceding first task), suggesting that action effect codes can become activated prior to a capacity-limited processing stage often denoted as response selection. The process of effect-based response production, by contrast, has been proposed to be capacity-limited. These observations jointly suggest that effect code activation can occur independently of effect-based response production, though this theoretical implication has not been tested directly at present. We tested this hypothesis by employing a dual-task set-up in which we manipulated the ease of effect-based response production (via response-effect compatibility) in an experimental design that allows for observing forward and backward crosstalk. We observed robust crosstalk effects and response-effect compatibility effects alike, but no interaction between both effects. These results indicate that effect activation can occur in parallel for several tasks, independently of effect-based response production, which is confined to one task at a time. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of technical alternative technologies for the development of context-driven composable environmental representations for JSB

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Hummel, John R.; Bergenthal, Jeff J.; Seng, William F.; Moulton, Joseph R., Jr.; Prager, S. D.

2004-08-01

The Joint Synthetic Battlespace for the Air Force (JSB-AF) is being developed to provide realistic representations of friendly and threat capabilities and the natural environmental conditions to support a variety of Department of Defense missions including training, mission rehearsal, decision support, acquisition, deployment, employment, operations, and the development of Courses of Action. This paper addresses three critical JSB issues associated with providing environ-mental representations to Modeling and Simulation (M&S) applications. First, how should the requirements for envi-ronmental functionality in a JSB-AF application be collected, analyzed, and used to define an Authoritative Environ-mental Representation (AER)? Second, how can JSB-AF AERs be generated? Third, once an AER has been generated, how should it be "served up" to the JSB-AF components? Our analyses of these issues will be presented from a general M&S perspective, with examples given from a JSB-AF centered view. In the context of this effort, the term "representa-tions" is meant to incorporate both basic environmental "data" (e.g., temperature, pressure, slope, elevation, etc.) and "effects", properties that can be derived from these data using physics-based models or empirical relationship from the fundamental data (e.g., extinction coefficients, radiance, soil moisture strength, etc.) We present a state-of-the-art review of the existing processes and technologies that address these questions.

Spatio-temporal dynamics of action-effect associations in oculomotor control.

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Riechelmann, Eva; Pieczykolan, Aleksandra; Horstmann, Gernot; Herwig, Arvid; Huestegge, Lynn

2017-10-01

While there is ample evidence that actions are guided by anticipating their effects (ideomotor control) in the manual domain, much less is known about the underlying characteristics and dynamics of effect-based oculomotor control. Here, we address three open issues. 1) Is action-effect anticipation in oculomotor control reflected in corresponding spatial saccade characteristics in inanimate environments? 2) Does the previously reported dependency of action latency on the temporal effect delay (action-effect interval) also occur in the oculomotor domain? 3) Which temporal effect delay is optimally suited to develop strong action-effect associations over time in the oculomotor domain? Participants executed left or right free-choice saccades to peripheral traffic lights, causing an (immediate or delayed) action-contingent light switch in the upper vs. lower part of the traffic light. Results indicated that saccades were spatially shifted toward the location of the upcoming change, indicating anticipation of the effect (location). Saccade latency was affected by effect delay, suggesting that corresponding time information is integrated into event representations. Finally, delayed (vs. immediate) effects were more effective in strengthening action-effect associations over the course of the experiment, likely due to greater saliency of perceptual changes occurring during target fixation as opposed to changes during saccades (saccadic suppression). Overall, basic principles underlying ideomotor control appear to generalize to the oculomotor domain. Copyright © 2017 Elsevier B.V. All rights reserved.

Theory of discretely decomposable restrictions of unitary representations of semisimple lie groups and some applications

CERN Document Server

Kobayashi, T

2002-01-01

Based on an embedding formula of the CAR algebra into the Cuntz algebra ${\\mathcal O}_{2^p}$, properties of the CAR algebra are studied in detail by restricting those of the Cuntz algebra. Various $\\ast$-endomorphisms of the Cuntz algebra are explicitly constructed, and transcribed into those of the CAR algebra. In particular, a set of $\\ast$-endomorphisms of the CAR algebra into its even subalgebra are constructed. According to branching formulae, which are obtained by composing representations and $\\ast$-endomorphisms, it is shown that a KMS state of the CAR algebra is obtained through the above even-CAR endomorphisms from the Fock representation. A $U(2^p)$ action on ${\\mathcal O}_{2^p}$ induces $\\ast$-automorphisms of the CAR algebra, which are given by nonlinear transformations expressed in terms of polynomials in generators. It is shown that, among such $\\ast$-automorphisms of the CAR algebra, there exists a family of one-parameter groups of $\\ast$-automorphisms describing time evolutions of fermions, i...

Simple adaptive sparse representation based classification schemes for EEG based brain-computer interface applications.

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Shin, Younghak; Lee, Seungchan; Ahn, Minkyu; Cho, Hohyun; Jun, Sung Chan; Lee, Heung-No

2015-11-01

One of the main problems related to electroencephalogram (EEG) based brain-computer interface (BCI) systems is the non-stationarity of the underlying EEG signals. This results in the deterioration of the classification performance during experimental sessions. Therefore, adaptive classification techniques are required for EEG based BCI applications. In this paper, we propose simple adaptive sparse representation based classification (SRC) schemes. Supervised and unsupervised dictionary update techniques for new test data and a dictionary modification method by using the incoherence measure of the training data are investigated. The proposed methods are very simple and additional computation for the re-training of the classifier is not needed. The proposed adaptive SRC schemes are evaluated using two BCI experimental datasets. The proposed methods are assessed by comparing classification results with the conventional SRC and other adaptive classification methods. On the basis of the results, we find that the proposed adaptive schemes show relatively improved classification accuracy as compared to conventional methods without requiring additional computation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mental Representations in Art Discourse

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Katja Sudec

2014-03-01

Full Text Available The paper starts by examining the content included in the museum environment, where I write about the type of relations that emerge in a museum or artistic setting. This is followed by an observation of a social act (socialising and a chapter on the use of food in an artistic venue. At the end, I address art education via the format that I developed at the 6th Berlin Biennale. This is followed by an overview of the cognitive model of the fort-da game based on Freud’s theory via two discourse models. Here, I address discourse on art works in the form of a lecture or reading, where the art space is fictitiously present, and then move on to discuss discourse on art works in real, “present” art space. This is followed by a section on actions (Handlungen in German and methods supporting the fort-da model. The last part of the article examines the issue of “mental representations”, defining and explaining the function of mental representations with regard to the target audience of the blind and visually impaired.

Neural and Computational Mechanisms of Action Processing: Interaction between Visual and Motor Representations.

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Giese, Martin A; Rizzolatti, Giacomo

2015-10-07

Action recognition has received enormous interest in the field of neuroscience over the last two decades. In spite of this interest, the knowledge in terms of fundamental neural mechanisms that provide constraints for underlying computations remains rather limited. This fact stands in contrast with a wide variety of speculative theories about how action recognition might work. This review focuses on new fundamental electrophysiological results in monkeys, which provide constraints for the detailed underlying computations. In addition, we review models for action recognition and processing that have concrete mathematical implementations, as opposed to conceptual models. We think that only such implemented models can be meaningfully linked quantitatively to physiological data and have a potential to narrow down the many possible computational explanations for action recognition. In addition, only concrete implementations allow judging whether postulated computational concepts have a feasible implementation in terms of realistic neural circuits. Copyright © 2015 Elsevier Inc. All rights reserved.

Action identity: evidence from self-recognition, prediction, and coordination.

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Knoblich, Günther; Flach, Rüdiger

2003-12-01

Prior research suggests that the action system is responsible for creating an immediate sense of self by determining whether certain sensations and perceptions are the result of one's own actions. In addition, it is assumed that declarative, episodic, or autobiographical memories create a temporally extended sense of self or some form of identity. In the present article, we review recent evidence suggesting that action (procedural) knowledge also forms part of a person's identity, an action identity, so to speak. Experiments that addressed self-recognition of past actions, prediction, and coordination provide ample evidence for this assumption. The phenomena observed in these experiments can be explained by the assumption that observing an action results in the activation of action representations, the more so, when the action observed corresponds to the way in which the observer would produce it.

The WLC principle for action-oriented perception

Science.gov (United States)

Arena, Paolo; Fortuna, Luigi; Lombardo, Davide; Patané, Luca; Velarde, Manuel G.

2007-05-01

In this paper a new methodology for action-oriented perception will be introduced. It is based on a previous method that used Turing Patterns in CNNs for the arousal of "perceptual states" as representation of the environmental condition. The emerging patterns were associated to codes which gave rise to learnable actions on a moving robot. Recently the new paradigm of Winnerless Competition (WLC) was taken into consideration to represent a suitable, bioinspired and efficient method to generate sequences of neural activations, strictly related to the spatial-temporal activity of input sensors. This fascinating property was recently peculiarly measured in the olfactory system, in particular in groups of neurons belonging to the insects' Antennal Lobe and to the mammalians' Olfactory Bulb. Taking inspiration from these experimental results and from the analytical model of the WLC, a cellular nonlinear model generating sequences of cell activation, representing the input pattern at the sensory level, will be used in an action-oriented perception framework. In fact simulation results showed the potentiality of the WLC approach to design dynamic networks for discrimination and classification, with a potentially huge memory capacity. In the present manuscript the WLC principle, implemented in a network of FitzHugh Nagumo neurons will be used within the whole framework for action-oriented perception, and the results will be applied to a roving robot.

Content-adaptive pyramid representation for 3D object classification

DEFF Research Database (Denmark)

Kounalakis, Tsampikos; Boulgouris, Nikolaos; Triantafyllidis, Georgios

2016-01-01

In this paper we introduce a novel representation for the classification of 3D images. Unlike most current approaches, our representation is not based on a fixed pyramid but adapts to image content and uses image regions instead of rectangular pyramid scales. Image characteristics, such as depth...... and color, are used for defining regions within images. Multiple region scales are formed in order to construct the proposed pyramid image representation. The proposed method achieves excellent results in comparison to conventional representations....

Geometric modular action and transformation groups

International Nuclear Information System (INIS)

Summers, S.J.

1996-01-01

We study a weak form of geometric modular action, which is naturally associated with transformation groups of partially ordered sets and which provides these groups with projective representations. Under suitable conditions it is shown that these groups are implemented by point transformations of topological spaces serving as models for space-times, leading to groups which may be interpreted as symmetry groups of the space-times. As concrete examples, it is shown that the Poincare group and the de Sitter group can be derived from this condition of geometric modular action. Further consequences and examples are discussed. (orig.)

The symplectic fermion ribbon quasi-Hopf algebra and the SL(2,Z)-action on its centre

Energy Technology Data Exchange (ETDEWEB)

Farsad, Vanda

2017-06-14

This thesis is concerned with ''N pairs of symplectic fermions'' which are examples of logarithmic conformal field theories in two dimensions. The mathematical language of two-dimensional conformal field theories (on Riemannian surfaces of genus zero) are vertex operator algebras. The representation category of the even part of the symplectic fermion vertex operator super-algebra Rep V{sub ev} is conjecturally a factorisable finite ribbon tensor category. This determines an isomorphism of projective representations between two SL(2,Z)-actions associated to V{sub ev}. The first action is obtained by modular transformations on the space of so-called pseudo-trace functions of a vertex operator algebra. For V{sub ev} this was developed by A.M.Gaberdiel and I. Runkel. For the action one uses that Rep V{sub ev} is conjecturally a factorisable finite ribbon tensor category and thus carries a projective SL(2,Z)-action on a certain Hom-space [Ly1,Ly2,KL]. To do so we calculate the SL(2,Z)-action on the representation category of a general factorisable quasi-Hopf algebras. Then we show that Rep V{sub ev} is conjecturally ribbon equivalent to Rep Q, for Q a factorisable quasi-Hopf algebra, and calculate the SL(2,Z)-action explicitly on Rep Q. The result is that the two SL(2,Z)-action indeed agree. This poses the first example of such comparison for logarithmic conformal field theories.

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed; Zhang, Xiangliang

2017-01-01

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

KAUST Repository

Alharbi, Basma Mohammed

2017-02-07

Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

Analysis of graphic representations of activity theory in international journals

Directory of Open Access Journals (Sweden)

Marco André Mazzarotto

2016-05-01

Full Text Available Activity theory is a relevant framework for the Design field, and their graphic representations are cognitive artifacts that aid the understanding, use and communication of this theory. However, there is a lack of consistency around the graphics and labels used in these representations. Based on this, the aim of this study was to identify, analyze and evaluate these differences and propose a representation that aims to be more suitable for the theory. For this, uses as method a literature review based on Engeström (2001 and its three generations of visual models, combined with graphical analysis of representations collected in a hundred papers from international journals.

Representations of quantum algebras and combinatorics of Young tableaux

CERN Document Server

Ariki, Susumu

2002-01-01

Among several tools used in studying representations of quantum groups (or quantum algebras) are the notions of Kashiwara's crystal bases and Lusztig's canonical bases. Mixing both approaches allows us to use a combinatorial approach to representations of quantum groups and to apply the theory to representations of Hecke algebras. The primary goal of this book is to introduce the representation theory of quantum groups using quantum groups of type A_{r-1}^{(1)} as a main example. The corresponding combinatorics, developed by Misra and Miwa, turns out to be the combinatorics of Young tableaux. The second goal of this book is to explain the proof of the (generalized) Leclerc-Lascoux-Thibon conjecture. This conjecture, which is now a theorem, is an important breakthrough in the modular representation theory of the Hecke algebras of classical type. The book contains most of the nonstandard material necessary to get acquainted with this new rapidly developing area. It can be used as a good entry point into the stu...

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

Science.gov (United States)

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

Integrating robotic action with biologic perception: A brain-machine symbiosis theory

Science.gov (United States)

Mahmoudi, Babak

In patients with motor disability the natural cyclic flow of information between the brain and external environment is disrupted by their limb impairment. Brain-Machine Interfaces (BMIs) aim to provide new communication channels between the brain and environment by direct translation of brain's internal states into actions. For enabling the user in a wide range of daily life activities, the challenge is designing neural decoders that autonomously adapt to different tasks, environments, and to changes in the pattern of neural activity. In this dissertation, a novel decoding framework for BMIs is developed in which a computational agent autonomously learns how to translate neural states into action based on maximization of a measure of shared goal between user and the agent. Since the agent and brain share the same goal, a symbiotic relationship between them will evolve therefore this decoding paradigm is called a Brain-Machine Symbiosis (BMS) framework. A decoding agent was implemented within the BMS framework based on the Actor-Critic method of Reinforcement Learning. The rule of the Actor as a neural decoder was to find mapping between the neural representation of motor states in the primary motor cortex (MI) and robot actions in order to solve reaching tasks. The Actor learned the optimal control policy using an evaluative feedback that was estimated by the Critic directly from the user's neural activity of the Nucleus Accumbens (NAcc). Through a series of computational neuroscience studies in a cohort of rats it was demonstrated that NAcc could provide a useful evaluative feedback by predicting the increase or decrease in the probability of earning reward based on the environmental conditions. Using a closed-loop BMI simulator it was demonstrated the Actor-Critic decoding architecture was able to adapt to different tasks as well as changes in the pattern of neural activity. The custom design of a dual micro-wire array enabled simultaneous implantation of MI and

An Eye-tracking Study of Notational, Informational, and Emotional Aspects of Learning Analytics Representations

DEFF Research Database (Denmark)

Vatrapu, Ravi; Reimann, Peter; Bull, Susan

2013-01-01

This paper presents an eye-tracking study of notational, informational, and emotional aspects of nine different notational systems (Skill Meters, Smilies, Traffic Lights, Topic Boxes, Collective Histograms, Word Clouds, Textual Descriptors, Table, and Matrix) and three different information states...... (Weak, Average, & Strong) used to represent student's learning. Findings from the eye-tracking study show that higher emotional activation was observed for the metaphorical notations of traffic lights and smilies and collective representations. Mean view time was higher for representations...... of the "average" informational learning state. Qualitative data analysis of the think-aloud comments and post-study interview show that student participants reflected on the meaning-making opportunities and action-taking possibilities afforded by the representations. Implications for the design and evaluation...

Factorizations and physical representations

International Nuclear Information System (INIS)

Revzen, M; Khanna, F C; Mann, A; Zak, J

2006-01-01

A Hilbert space in M dimensions is shown explicitly to accommodate representations that reflect the decomposition of M into prime numbers. Representations that exhibit the factorization of M into two relatively prime numbers: the kq representation (Zak J 1970 Phys. Today 23 51), and related representations termed q 1 q 2 representations (together with their conjugates) are analysed, as well as a representation that exhibits the complete factorization of M. In this latter representation each quantum number varies in a subspace that is associated with one of the prime numbers that make up M

Representations of braid group obtained from quantum sl(3) enveloping algebra

International Nuclear Information System (INIS)

Ma Zhongqi.

1989-07-01

The quantum Clebsch-Gordan coefficients for the coproduct 6x6 of the quantum sl(3) enveloping algebra are computed. Based on the representation 6, the representation of the braid group and the corresponding link polynomial are obtained. The link polynomials based on the representations of the quantum sl(3) enveloping algebra with one row Young tableau are discussed. (author). 11 refs, 3 tabs

Effective 1.0: An Analytic Effective Action Analysis Library

OpenAIRE

Hetherington, James P. J.; Stephens, Philip

2006-01-01

Effective is a C++ library which provides the user a toolbox to study the effective action of an arbitrary field theory. From the field content, gauge groups and representations an appropriate action is generated symbolically. The effective potential, mass spectrum, field couplings and vacuum expectation values are then obtained automatically; tree level results are obtained analytically while many tools, both numeric and analytic, provide a variety of approaches to deal with the one-loop cor...

Representations of G+++ and the role of space-time

International Nuclear Information System (INIS)

Kleinschmidt, A.; West, P.

2004-01-01

We consider the decomposition of the adjoint and fundamental representations of very extended Kac-Moody algebras G+++ with respect to their regular A type subalgebra which, in the corresponding non-linear realisation, is associated with gravity. We find that for many very extended algebras almost all the A type representations that occur in the decomposition of the fundamental representations also occur in the adjoint representation of G+++ . In particular, for E 8 +++ , this applies to all its fundamental representations. However, there are some important examples, such as A N-3 +++ , where this is not true and indeed the adjoint representation contains no generator that can be identified with a space-time translation. We comment on the significance of these results for how space-time can occur in the non-linear realisation based on G+++ . Finally we show that there is a correspondence between the A representations that occur in the fundamental representation associated with the very extended node and the adjoint representation of G+++ which is consistent with the interpretation of the former as charges associated with brane solutions. (author)

Advances in visual representation of molecular potentials.

Science.gov (United States)

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

A generative representation for the evolution of jazz solos

DEFF Research Database (Denmark)

Bäckman, Kjell; Dahlstedt, Palle

2008-01-01

This paper describes a system developed to create computer based jazz improvisation solos. The generation of the improvisation material uses interactive evolution, based on a dual genetic representation: a basic melody line representation, with energy constraints ("rubber band") and a hierarchic...... developed for this specific type of music. This is the first published part of an ongoing research project in generative jazz, based on probabilistic and evolutionary strategies....

Simple Ontology of Manipulation Actions based on Hand-Object Relations

DEFF Research Database (Denmark)

Wörgötter, Florentin; Aksoy, E. E.; Krüger, Norbert

2013-01-01

and time. For this we use as temporal anchor points those moments where two objects (or hand and object) touch or un-touch each other during a manipulation. We show that by this one can define a relatively small tree-like manipulation ontology. We find less than 30 fundamental manipulations. The temporal...... and encoded. Examples of manipulations recognition and execution by a robot based on this representation are given at the end of this study....