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Sample records for based action representation

  1. Primitive Based Action Representation and Recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker

    2009-01-01

    a sequential and statistical     learning algorithm for   automatic detection of the action primitives and the action grammar   based on these primitives.  We model a set of actions using a   single HMM whose structure is learned incrementally as we observe   new types.   Actions are modeled with sufficient...

  2. Primitive Based Action Representation and recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan

    The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human......-machine interface, entertainment, biomechanics etc. Recent developments in neuroscience suggest that all actions are a compositions of smaller units called primitives. Current works based on primitives for action recognition uses a supervised framework for specifying the primitives. We propose a method to extract...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

  3. Human action recognition using trajectory-based representation

    Directory of Open Access Journals (Sweden)

    Haiam A. Abdul-Azim

    2015-07-01

    Full Text Available Recognizing human actions in video sequences has been a challenging problem in the last few years due to its real-world applications. A lot of action representation approaches have been proposed to improve the action recognition performance. Despite the popularity of local features-based approaches together with “Bag-of-Words” model for action representation, it fails to capture adequate spatial or temporal relationships. In an attempt to overcome this problem, a trajectory-based local representation approaches have been proposed to capture the temporal information. This paper introduces an improvement of trajectory-based human action recognition approaches to capture discriminative temporal relationships. In our approach, we extract trajectories by tracking the detected spatio-temporal interest points named “cuboid features” with matching its SIFT descriptors over the consecutive frames. We, also, propose a linking and exploring method to obtain efficient trajectories for motion representation in realistic conditions. Then the volumes around the trajectories’ points are described to represent human actions based on the Bag-of-Words (BOW model. Finally, a support vector machine is used to classify human actions. The effectiveness of the proposed approach was evaluated on three popular datasets (KTH, Weizmann and UCF sports. Experimental results showed that the proposed approach yields considerable performance improvement over the state-of-the-art approaches.

  4. Multi-stream CNN: Learning representations based on human-related regions for action recognition

    NARCIS (Netherlands)

    Tu, Zhigang; Xie, Wei; Qin, Qianqing; Poppe, R.W.; Veltkamp, R.C.; Li, Baoxin; Yuan, Junsong

    2018-01-01

    The most successful video-based human action recognition methods rely on feature representations extracted using Convolutional Neural Networks (CNNs). Inspired by the two-stream network (TS-Net), we propose a multi-stream Convolutional Neural Network (CNN) architecture to recognize human actions. We

  5. Improved Collaborative Representation Classifier Based on l2-Regularized for Human Action Recognition

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    Shirui Huo

    2017-01-01

    Full Text Available Human action recognition is an important recent challenging task. Projecting depth images onto three depth motion maps (DMMs and extracting deep convolutional neural network (DCNN features are discriminant descriptor features to characterize the spatiotemporal information of a specific action from a sequence of depth images. In this paper, a unified improved collaborative representation framework is proposed in which the probability that a test sample belongs to the collaborative subspace of all classes can be well defined and calculated. The improved collaborative representation classifier (ICRC based on l2-regularized for human action recognition is presented to maximize the likelihood that a test sample belongs to each class, then theoretical investigation into ICRC shows that it obtains a final classification by computing the likelihood for each class. Coupled with the DMMs and DCNN features, experiments on depth image-based action recognition, including MSRAction3D and MSRGesture3D datasets, demonstrate that the proposed approach successfully using a distance-based representation classifier achieves superior performance over the state-of-the-art methods, including SRC, CRC, and SVM.

  6. A Comprehensive Review on Handcrafted and Learning-Based Action Representation Approaches for Human Activity Recognition

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    Allah Bux Sargano

    2017-01-01

    Full Text Available Human activity recognition (HAR is an important research area in the fields of human perception and computer vision due to its wide range of applications. These applications include: intelligent video surveillance, ambient assisted living, human computer interaction, human-robot interaction, entertainment, and intelligent driving. Recently, with the emergence and successful deployment of deep learning techniques for image classification, researchers have migrated from traditional handcrafting to deep learning techniques for HAR. However, handcrafted representation-based approaches are still widely used due to some bottlenecks such as computational complexity of deep learning techniques for activity recognition. However, approaches based on handcrafted representation are not able to handle complex scenarios due to their limitations and incapability; therefore, resorting to deep learning-based techniques is a natural option. This review paper presents a comprehensive survey of both handcrafted and learning-based action representations, offering comparison, analysis, and discussions on these approaches. In addition to this, the well-known public datasets available for experimentations and important applications of HAR are also presented to provide further insight into the field. This is the first review paper of its kind which presents all these aspects of HAR in a single review article with comprehensive coverage of each part. Finally, the paper is concluded with important discussions and research directions in the domain of HAR.

  7. Action simulation: time course and representational mechanisms

    Science.gov (United States)

    Springer, Anne; Parkinson, Jim; Prinz, Wolfgang

    2013-01-01

    The notion of action simulation refers to the ability to re-enact foreign actions (i.e., actions observed in other individuals). Simulating others' actions implies a mirroring of their activities, based on one's own sensorimotor competencies. Here, we discuss theoretical and experimental approaches to action simulation and the study of its representational underpinnings. One focus of our discussion is on the timing of internal simulation and its relation to the timing of external action, and a paradigm that requires participants to predict the future course of actions that are temporarily occluded from view. We address transitions between perceptual mechanisms (referring to action representation before and after occlusion) and simulation mechanisms (referring to action representation during occlusion). Findings suggest that action simulation runs in real-time; acting on newly created action representations rather than relying on continuous visual extrapolations. A further focus of our discussion pertains to the functional characteristics of the mechanisms involved in predicting other people's actions. We propose that two processes are engaged, dynamic updating and static matching, which may draw on both semantic and motor information. In a concluding section, we discuss these findings in the context of broader theoretical issues related to action and event representation, arguing that a detailed functional analysis of action simulation in cognitive, neural, and computational terms may help to further advance our understanding of action cognition and motor control. PMID:23847563

  8. Action representation: crosstalk between semantics and pragmatics.

    Science.gov (United States)

    Prinz, Wolfgang

    2014-03-01

    Marc Jeannerod pioneered a representational approach to movement and action. In his approach, motor representations provide both, declarative knowledge about action and procedural knowledge for action (action semantics and action pragmatics, respectively). Recent evidence from language comprehension and action simulation supports the claim that action pragmatics and action semantics draw on common representational resources, thus challenging the traditional divide between declarative and procedural action knowledge. To account for these observations, three kinds of theoretical frameworks are discussed: (i) semantics is grounded in pragmatics, (ii) pragmatics is anchored in semantics, and (iii) pragmatics is part and parcel of semantics. © 2013 Elsevier Ltd. All rights reserved.

  9. Efficient Interaction Recognition through Positive Action Representation

    Directory of Open Access Journals (Sweden)

    Tao Hu

    2013-01-01

    Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.

  10. Culture-specific familiarity equally mediates action representations across cultures.

    Science.gov (United States)

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

    2014-01-01

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

  11. Learning a Mid-Level Representation for Multiview Action Recognition

    Directory of Open Access Journals (Sweden)

    Cuiwei Liu

    2018-01-01

    Full Text Available Recognizing human actions in videos is an active topic with broad commercial potentials. Most of the existing action recognition methods are supposed to have the same camera view during both training and testing. And thus performances of these single-view approaches may be severely influenced by the camera movement and variation of viewpoints. In this paper, we address the above problem by utilizing videos simultaneously recorded from multiple views. To this end, we propose a learning framework based on multitask random forest to exploit a discriminative mid-level representation for videos from multiple cameras. In the first step, subvolumes of continuous human-centered figures are extracted from original videos. In the next step, spatiotemporal cuboids sampled from these subvolumes are characterized by multiple low-level descriptors. Then a set of multitask random forests are built upon multiview cuboids sampled at adjacent positions and construct an integrated mid-level representation for multiview subvolumes of one action. Finally, a random forest classifier is employed to predict the action category in terms of the learned representation. Experiments conducted on the multiview IXMAS action dataset illustrate that the proposed method can effectively recognize human actions depicted in multiview videos.

  12. Studying Action Representation in Children via Motor Imagery

    Science.gov (United States)

    Gabbard, Carl

    2009-01-01

    The use of motor imagery is a widely used experimental paradigm for the study of cognitive aspects of action planning and control in adults. Furthermore, there are indications that motor imagery provides a window into the process of action representation. These notions complement internal model theory suggesting that such representations allow…

  13. [Children with developmental coordination disorder have difficulty with action representation].

    Science.gov (United States)

    Gabbard, Carl; Cacola, Priscila

    The study of children with developmental coordination disorder (DCD) has emerged as a vibrant line of inquiry over the last two decades. The literature indicates quite clearly that children with DCD display deficits with an array of perceptual-motor and daily living skills. The movements of children with DCD are often described as clumsy and uncoordinated and lead to difficulties with performing many of the activities of daily living and sports that typically developing children perform easily. It has been hypothesized, based on limited research, that an underlying problem is a deficit in generating and/or monitoring an action representation termed the internal modeling deficit 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. Included are research methods and possible brain structures involved. An addition, a paradigm unique with this population-estimation of reachability (distance) via motor imagery, will be described.

  14. Motor memory is encoded as a gain-field combination of intrinsic and extrinsic action representations.

    Science.gov (United States)

    Brayanov, Jordan B; Press, Daniel Z; Smith, Maurice A

    2012-10-24

    Actions can be planned in either an intrinsic (body-based) reference frame or an extrinsic (world-based) frame, and understanding how the internal representations associated with these frames contribute to the learning of motor actions is a key issue in motor control. We studied the internal representation of this learning in human subjects by analyzing generalization patterns across an array of different movement directions and workspaces after training a visuomotor rotation in a single movement direction in one workspace. This provided a dense sampling of the generalization function across intrinsic and extrinsic reference frames, which allowed us to dissociate intrinsic and extrinsic representations and determine the manner in which they contributed to the motor memory for a trained action. A first experiment showed that the generalization pattern reflected a memory that was intermediate between intrinsic and extrinsic representations. A second experiment showed that this intermediate representation could not arise from separate intrinsic and extrinsic learning. Instead, we find that the representation of learning is based on a gain-field combination of local representations in intrinsic and extrinsic coordinates. This gain-field representation generalizes between actions by effectively computing similarity based on the (Mahalanobis) distance across intrinsic and extrinsic coordinates and is in line with neural recordings showing mixed intrinsic-extrinsic representations in motor and parietal cortices.

  15. Invariant recognition drives neural representations of action sequences.

    Directory of Open Access Journals (Sweden)

    Andrea Tacchetti

    2017-12-01

    Full Text Available Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs, that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences.

  16. 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.

  17. 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.

  18. 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....

  19. Learning Visual Representations for Perception-Action Systems

    DEFF Research Database (Denmark)

    Piater, Justus; Jodogne, Sebastien; Detry, Renaud

    2011-01-01

    and RLJC, our second method learns structural object models for robust object detection and pose estimation by probabilistic inference. To these models, the method associates grasp experiences autonomously learned by trial and error. These experiences form a nonparametric representation of grasp success......We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily complex, we argue that in many cases it is advantageous to link them rather directly to action via learned mappings....... These arguments are illustrated by two examples of our own work. First, our RLVC algorithm performs reinforcement learning directly on the visual input space. To make this very large space manageable, RLVC interleaves the reinforcement learner with a supervised classification algorithm that seeks to split...

  20. Action Intentions: Action Influences Both On-Line Perception and Off-Line Representation

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    C Kirtley

    2014-08-01

    Full Text Available Given that one role of vision is to gather information for upcoming tasks, previous studies have investigated whether the preparation for action affects visual behaviour. The current studies aimed to determine if such influences on visual selection would also influence the formation of subsequent memory representations. Two experiments were conducted- in the first, participants' action intentions towards a scene were manipulated by the performance of different grasping postures as they observed the scene. This was followed by a memory test for the objects presented. Participants' eye movements were affected by their action intention, so that performing a power grip led to significantly longer fixation durations on power grip compatible objects. In contrast, memory for the objects and their properties was not affected by the action. Our second study required participants to make the action posture during the recall phase. No effect on eye movements was found, but recall was affected, with a particular advantage for recall of the position of grip-compatible objects. Previous studies have shown that action intentions can affect the on-line perception of objects. The current study suggests this may not extend to off-line representations if they are accessed after the action has been completed or abandoned. However, the recall of information may be affected if gestures are formed during retrieval. Memory representations may not be tailored specifically to an action, but actions can still affect the recall of information.

  1. Simulating my own or others action plans?--Motor representations, not visual representations are recalled in motor memory.

    Directory of Open Access Journals (Sweden)

    Christian Seegelke

    Full Text Available Action plans are not generated from scratch for each movement, but features of recently generated plans are recalled for subsequent movements. This study investigated whether the observation of an action is sufficient to trigger plan recall processes. Participant dyads performed an object manipulation task in which one participant transported a plunger from an outer platform to a center platform of different heights (first move. Subsequently, either the same (intra-individual task condition or the other participant (inter-individual task condition returned the plunger to the outer platform (return moves. Grasp heights were inversely related to center target height and similar irrespective of direction (first vs. return move and task condition (intra- vs. inter-individual. Moreover, participants' return move grasp heights were highly correlated with their own, but not with their partners' first move grasp heights. Our findings provide evidence that a simulated action plan resembles a plan of how the observer would execute that action (based on a motor representation rather than a plan of the actually observed action (based on a visual representation.

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

    Science.gov (United States)

    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.

  3. Dynamic evocation of hand action representations during sentence comprehension.

    Science.gov (United States)

    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.

  4. 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

  5. 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.

  6. 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

  7. 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.

  8. 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.

  9. 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…

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

    Science.gov (United States)

    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.

  11. 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

  12. 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

  13. The Representation of Action Plans in Long Term Memory

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    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.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  16. 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...

  17. 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...

  18. 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.)

  19. LPS: a rule-based, schema-oriented knowledge representation system

    Energy Technology Data Exchange (ETDEWEB)

    Anzai, Y; Mitsuya, Y; Nakajima, S; Ura, S

    1981-01-01

    A new knowledge representation system called LPS is presented. The global control structure of LPS is rule-based, but the local representational structure is schema-oriented. The present version of LPS was designed to increase the understandability of representation while keeping time efficiency reasonable. Pattern matching through slot-networks and meta-actions from among the implemented facilities of LPS, are especially described in detail. 7 references.

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

    Science.gov (United States)

    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.

  1. 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

  2. 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...

  3. 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.

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

    Science.gov (United States)

    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%).

  5. Neural representation of the sensorimotor speech-action-repository

    Directory of Open Access Journals (Sweden)

    Cornelia eEckers

    2013-04-01

    Full Text Available A speech-action-repository (SAR or mental syllabary has been proposed as a central module for sensorimotor processing of syllables. In this approach, syllables occurring frequently within language are assumed to be stored as holistic sensorimotor patterns, while non-frequent syllables need to be assembled from sub-syllabic units. Thus, frequent syllables are processed efficiently and quickly during production or perception by a direct activation of their sensorimotor patterns. Whereas several behavioral psycholinguistic studies provided evidence in support of the existence of a syllabary, fMRI studies have failed to demonstrate its neural reality. In the present fMRI study a reaction paradigm using homogeneous vs. heterogeneous syllable blocks are used during overt vs. covert speech production and auditory vs. visual presentation modes. Two complementary data analyses were performed: (1 in a logical conjunction, activation for syllable processing independent of input modality and response mode was assessed, in order to support the assumption of existence of a supramodal hub within a SAR. (2 In addition priming effects in the BOLD response in homogeneous vs. heterogeneous blocks were measured in order to identify brain regions, which indicate reduced activity during multiple production/perception repetitions of a specific syllable in order to determine state maps. Auditory-visual conjunction analysis revealed an activation network comprising bilateral precentral gyrus and left inferior frontal gyrus (area 44. These results are compatible with the notion of a supramodal hub within the SAR. The main effect of homogeneity priming revealed an activation pattern of areas within frontal, temporal, and parietal lobe. These findings are taken to represent sensorimotor state maps of the SAR. In conclusion, the present study provided preliminary evidence for a SAR.

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

    Science.gov (United States)

    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…

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

    Science.gov (United States)

    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…

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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)

  10. A word in the hand: action, gesture and mental representation in humans and non-human primates

    Science.gov (United States)

    Cartmill, Erica A.; Beilock, Sian; Goldin-Meadow, Susan

    2012-01-01

    The movements we make with our hands both reflect our mental processes and help to shape them. Our actions and gestures can affect our mental representations of actions and objects. In this paper, we explore the relationship between action, gesture and thought in both humans and non-human primates and discuss its role in the evolution of language. Human gesture (specifically representational gesture) may provide a unique link between action and mental representation. It is kinaesthetically close to action and is, at the same time, symbolic. Non-human primates use gesture frequently to communicate, and do so flexibly. However, their gestures mainly resemble incomplete actions and lack the representational elements that characterize much of human gesture. Differences in the mirror neuron system provide a potential explanation for non-human primates' lack of representational gestures; the monkey mirror system does not respond to representational gestures, while the human system does. In humans, gesture grounds mental representation in action, but there is no evidence for this link in other primates. We argue that gesture played an important role in the transition to symbolic thought and language in human evolution, following a cognitive leap that allowed gesture to incorporate representational elements. PMID:22106432

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

    Directory of Open Access Journals (Sweden)

    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.

  12. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation

    Directory of Open Access Journals (Sweden)

    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.

  13. 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.

    Science.gov (United States)

    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.

  14. 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...

  15. Representation

    National Research Council Canada - National Science Library

    Little, Daniel

    2006-01-01

    ...). The reason this is so is due to hierarchies that we take for granted. By hierarchies I mean that there is a layer of representation of us as individuals, as military professional, as members of a military unit and as citizens of an entire nation...

  16. Representation

    Science.gov (United States)

    2006-09-01

    two weeks to arrive. Source: http://beergame.mit.edu/ Permission Granted – MIT Supply Chain Forum 2005 Professor Sterman –Sloan School of...Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html Rules of Engagement The MIT Beer Game Simulation 04-04 Slide Number 10 Professor...Sterman –Sloan School of Management - MITSource: http://web.mit.edu/jsterman/www/ SDG /beergame.html What is the Significance of Representation

  17. 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.

  18. Neural Representation. A Survey-Based Analysis of the Notion

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  20. 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....

  1. 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.

  2. 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.

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

    Science.gov (United States)

    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.

  4. 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.

  5. 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...

  6. 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...

  7. 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.

  8. Supervised Filter Learning for Representation Based Face Recognition.

    Directory of Open Access Journals (Sweden)

    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.

  9. 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

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  12. Conformal-Based Surface Morphing and Multi-Scale Representation

    Directory of Open Access Journals (Sweden)

    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.

  13. 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...

  14. Smooth Particle Hydrodynamics-based Wind Representation

    Energy Technology Data Exchange (ETDEWEB)

    Prescott, Steven [Idaho National Lab. (INL), Idaho Falls, ID (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States); Hess, Stephen [Idaho National Lab. (INL), Idaho Falls, ID (United States); Lin, Linyu [Idaho National Lab. (INL), Idaho Falls, ID (United States); Sampath, Ram [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-12-01

    As a result of the 2011 accident at the Fukushima Dai-ichi NPP and other operational NPP experience, there is an identified need to better characterize and evaluate the potential impacts of externally generated hazards on NPP safety. Due to the ubiquitous occurrence of high winds around the world and the possible extreme magnitude of the hazard that has been observed, the assessment of the impact of the high-winds hazard has been identified as an important activity by both NPP owner-operators and regulatory authorities. However, recent experience obtained from the conduct of high-winds risk assessments indicates that such activities have been both labor-intensive and expensive to perform. Additionally, the existing suite of methods and tools to conduct such assessments (which were developed decades ago) do not make use of modern computational architectures (e.g., parallel processing, object-oriented programming techniques, or simple user interfaces) or methods (e.g., efficient and robust numerical-solution schemes). As a result, the current suite of methods and tools will rapidly become obsolete. Physics-based 3D simulation methods can provide information to assist in the RISMC PRA methodology. This research is intended to determine what benefits SPH methods could bring to high-winds simulations for the purposes of assessing their potential impact on NPP safety. The initial investigation has determined that SPH can simulate key areas of high-wind events with reasonable accuracy, compared to other methods. Some problems, such as simulation voids, need to be addressed, but possible solutions have been identified and will be tested with continued work. This work also demonstrated that SPH simulations can provide a means for simulating debris movement; however, further investigations into the capability to determine the impact of high winds and the impacts of wind-driven debris that lead to SSC failures need to be done. SPH simulations alone would be limited in size

  15. 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.

  16. 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...

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. 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

  2. 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.

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

    Science.gov (United States)

    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

  4. Order-based representation in random networks of cortical neurons.

    Directory of Open Access Journals (Sweden)

    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.

  5. 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.

  6. 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.

  7. 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

  8. Human action recognition based on estimated weak poses

    Science.gov (United States)

    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.

  9. 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).

  10. 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.

  11. 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.

  12. 3D ear identification based on sparse representation.

    Directory of Open Access Journals (Sweden)

    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.

  13. Ubiquitous log odds: a common representation of probability and frequency distortion in perception, action and cognition

    Directory of Open Access Journals (Sweden)

    Hang eZhang

    2012-01-01

    Full Text Available In decision from experience, the source of probability information affects how probability is distorted in the decision task. Understanding how and why probability is distorted is a key issue in understanding the peculiar character of experience-based decision. We consider how probability information is used not just in decision making but also in a wide variety of cognitive, perceptual and motor tasks. Very similar patterns of distortion of probability/frequency information have been found in visual frequency estimation, frequency estimation based on memory, signal detection theory, and in the use of probability information in decision-making under risk and uncertainty. We show that distortion of probability in all cases is well captured as linear transformations of the log odds of frequency and/or probability, a model with a slope parameter and an intercept parameter. We then consider how task and experience influence these two parameters and the resulting distortion of probability. We review how the probability distortions change in systematic ways with task and report three experiments on frequency distortion where the distortions change systematically in the same task. We found that the slope of frequency distortions decreases with the sample size, which is echoed by findings in decision from experience. We review previous models of the representation of uncertainty and find that none can account for the empirical findings.

  14. 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.

  15. 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

  16. Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. 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

    2017-09-01

    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.

  19. 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…

  20. 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.

  1. A robust probabilistic collaborative representation based classification for multimodal biometrics

    Science.gov (United States)

    Zhang, Jing; Liu, Huanxi; Ding, Derui; Xiao, Jianli

    2018-04-01

    Most of the traditional biometric recognition systems perform recognition with a single biometric indicator. These systems have suffered noisy data, interclass variations, unacceptable error rates, forged identity, and so on. Due to these inherent problems, it is not valid that many researchers attempt to enhance the performance of unimodal biometric systems with single features. Thus, multimodal biometrics is investigated to reduce some of these defects. This paper proposes a new multimodal biometric recognition approach by fused faces and fingerprints. For more recognizable features, the proposed method extracts block local binary pattern features for all modalities, and then combines them into a single framework. For better classification, it employs the robust probabilistic collaborative representation based classifier to recognize individuals. Experimental results indicate that the proposed method has improved the recognition accuracy compared to the unimodal biometrics.

  2. Object-Based Benefits without Object-Based Representations

    OpenAIRE

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

    2012-01-01

    The organization of visual information into objects strongly influences visual memory: Displays with objects defined by two features (e.g. color, orientation) are easier to remember than displays with twice as many objects defined by one feature (Olson & Jiang, 2002). Existing theories suggest that this ‘object-benefit’ is based on object-based limitations in working memory: because a limited number of objects can be stored, packaging features together so that fewer objects have to be remembe...

  3. Twisted Diff S sup 1 -action on loop groups and representations of the Virasoro algebra

    Energy Technology Data Exchange (ETDEWEB)

    Harnad, J [Montreal Univ., Quebec (Canada). Centre de Recherches Mathematiques (CRM); Kupershmidt, B A [Tennessee Univ., Tullahoma (USA). Space Inst.

    1990-05-01

    A modified Hamiltonian action of Diff S{sup 1} on the phase space LG{sup C}/G{sup C}, where LG is a loop group, is defined by twisting the usual action by a left translation in LG. This twisted action is shown to be generated by a nonequivariant moment map, thereby defining a classical Poisson bracket realization of a central extension of the Lie algebra diff{sub C} S{sup 1}. The resulting formula expresses the Diff S{sup 1} generators in terms of the left LG translation generators, giving a shifted modification of both the classical and quantum versions of the Sugawara formula. (orig.).

  4. 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.

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  7. 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…

  8. Pedestrian detection from thermal images: A sparse representation based approach

    Science.gov (United States)

    Qi, Bin; John, Vijay; Liu, Zheng; Mita, Seiichi

    2016-05-01

    Pedestrian detection, a key technology in computer vision, plays a paramount role in the applications of advanced driver assistant systems (ADASs) and autonomous vehicles. The objective of pedestrian detection is to identify and locate people in a dynamic environment so that accidents can be avoided. With significant variations introduced by illumination, occlusion, articulated pose, and complex background, pedestrian detection is a challenging task for visual perception. Different from visible images, thermal images are captured and presented with intensity maps based objects' emissivity, and thus have an enhanced spectral range to make human beings perceptible from the cool background. In this study, a sparse representation based approach is proposed for pedestrian detection from thermal images. We first adopted the histogram of sparse code to represent image features and then detect pedestrian with the extracted features in an unimodal and a multimodal framework respectively. In the unimodal framework, two types of dictionaries, i.e. joint dictionary and individual dictionary, are built by learning from prepared training samples. In the multimodal framework, a weighted fusion scheme is proposed to further highlight the contributions from features with higher separability. To validate the proposed approach, experiments were conducted to compare with three widely used features: Haar wavelets (HWs), histogram of oriented gradients (HOG), and histogram of phase congruency (HPC) as well as two classification methods, i.e. AdaBoost and support vector machine (SVM). Experimental results on a publicly available data set demonstrate the superiority of the proposed approach.

  9. Face antispoofing based on frame difference and multilevel representation

    Science.gov (United States)

    Benlamoudi, Azeddine; Aiadi, Kamal Eddine; Ouafi, Abdelkrim; Samai, Djamel; Oussalah, Mourad

    2017-07-01

    Due to advances in technology, today's biometric systems become vulnerable to spoof attacks made by fake faces. These attacks occur when an intruder attempts to fool an established face-based recognition system by presenting a fake face (e.g., print photo or replay attacks) in front of the camera instead of the intruder's genuine face. For this purpose, face antispoofing has become a hot topic in face analysis literature, where several applications with antispoofing task have emerged recently. We propose a solution for distinguishing between real faces and fake ones. Our approach is based on extracting features from the difference between successive frames instead of individual frames. We also used a multilevel representation that divides the frame difference into multiple multiblocks. Different texture descriptors (local binary patterns, local phase quantization, and binarized statistical image features) have then been applied to each block. After the feature extraction step, a Fisher score is applied to sort the features in ascending order according to the associated weights. Finally, a support vector machine is used to differentiate between real and fake faces. We tested our approach on three publicly available databases: CASIA Face Antispoofing database, Replay-Attack database, and MSU Mobile Face Spoofing database. The proposed approach outperforms the other state-of-the-art methods in different media and quality metrics.

  10. 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.

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

    Science.gov (United States)

    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.

  12. Supramodal and modality-sensitive representations of perceived action categories in the human brain

    NARCIS (Netherlands)

    Ramsey, R.; Cross, E.S.; Hamilton, A.F.D.C.

    2013-01-01

    Seeing Suzie bite an apple or reading the sentence ‘Suzie munched the apple’ both convey a similar idea. But is there a common neural basis for action comprehension when generated through video or text? The current study used functional magnetic resonance imaging to address this question.

  13. 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...

  14. 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

  15. Frontal and parietal cortical interactions with distributed visual representations during selective attention and action selection.

    Science.gov (United States)

    Nelissen, Natalie; Stokes, Mark; Nobre, Anna C; Rushworth, Matthew F S

    2013-10-16

    Using multivoxel pattern analysis (MVPA), we studied how distributed visual representations in human occipitotemporal cortex are modulated by attention and link their modulation to concurrent activity in frontal and parietal cortex. We detected similar occipitotemporal patterns during a simple visuoperceptual task and an attention-to-working-memory task in which one or two stimuli were cued before being presented among other pictures. Pattern strength varied from highest to lowest when the stimulus was the exclusive focus of attention, a conjoint focus, and when it was potentially distracting. Although qualitatively similar effects were seen inside regions relatively specialized for the stimulus category and outside, the former were quantitatively stronger. By regressing occipitotemporal pattern strength against activity elsewhere in the brain, we identified frontal and parietal areas exerting top-down control over, or reading information out from, distributed patterns in occipitotemporal cortex. Their interactions with patterns inside regions relatively specialized for that stimulus category were higher than those with patterns outside those regions and varied in strength as a function of the attentional condition. One area, the frontal operculum, was distinguished by selectively interacting with occipitotemporal patterns only when they were the focus of attention. There was no evidence that any frontal or parietal area actively inhibited occipitotemporal representations even when they should be ignored and were suppressed. Using MVPA to decode information within these frontal and parietal areas showed that they contained information about attentional context and/or readout information from occipitotemporal cortex to guide behavior but that frontal regions lacked information about category identity.

  16. Frontal and Parietal Cortical Interactions with Distributed Visual Representations during Selective Attention and Action Selection

    Science.gov (United States)

    Stokes, Mark; Nobre, Anna C.; Rushworth, Matthew F. S.

    2013-01-01

    Using multivoxel pattern analysis (MVPA), we studied how distributed visual representations in human occipitotemporal cortex are modulated by attention and link their modulation to concurrent activity in frontal and parietal cortex. We detected similar occipitotemporal patterns during a simple visuoperceptual task and an attention-to-working-memory task in which one or two stimuli were cued before being presented among other pictures. Pattern strength varied from highest to lowest when the stimulus was the exclusive focus of attention, a conjoint focus, and when it was potentially distracting. Although qualitatively similar effects were seen inside regions relatively specialized for the stimulus category and outside, the former were quantitatively stronger. By regressing occipitotemporal pattern strength against activity elsewhere in the brain, we identified frontal and parietal areas exerting top-down control over, or reading information out from, distributed patterns in occipitotemporal cortex. Their interactions with patterns inside regions relatively specialized for that stimulus category were higher than those with patterns outside those regions and varied in strength as a function of the attentional condition. One area, the frontal operculum, was distinguished by selectively interacting with occipitotemporal patterns only when they were the focus of attention. There was no evidence that any frontal or parietal area actively inhibited occipitotemporal representations even when they should be ignored and were suppressed. Using MVPA to decode information within these frontal and parietal areas showed that they contained information about attentional context and/or readout information from occipitotemporal cortex to guide behavior but that frontal regions lacked information about category identity. PMID:24133250

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. 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

  7. 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...

  8. Towards a Script-Based Representation Language for Educational Films.

    Science.gov (United States)

    Parkes, Alan P.

    1987-01-01

    Discusses aspects of the syntax and semantics of film, and presents a scenario for the use of film by intelligent computer assisted instruction (ICAI) systems. An outline of a representation language for educational films on videodisc is presented, and an appendix provides conceptual graphs that explain notations used in examples. (Author/LRW)

  9. 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.

  10. The Neural Representation of Goal-Directed Actions and Outcomes in the Ventral Striatum's Olfactory Tubercle

    Science.gov (United States)

    Gadziola, Marie A.

    2016-01-01

    The ventral striatum is critical for evaluating reward information and the initiation of goal-directed behaviors. The many cellular, afferent, and efferent similarities between the ventral striatum's nucleus accumbens and olfactory tubercle (OT) suggests the distributed involvement of neurons within the ventral striatopallidal complex in motivated behaviors. Although the nucleus accumbens has an established role in representing goal-directed actions and their outcomes, it is not known whether this function is localized within the nucleus accumbens or distributed also within the OT. Answering such a fundamental question will expand our understanding of the neural mechanisms underlying motivated behaviors. Here we address whether the OT encodes natural reinforcers and serves as a substrate for motivational information processing. In recordings from mice engaged in a novel water-motivated instrumental task, we report that OT neurons modulate their firing rate during initiation and progression of the instrumental licking behavior, with some activity being internally generated and preceding the first lick. We further found that as motivational drive decreases throughout a session, the activity of OT neurons is enhanced earlier relative to the behavioral action. Additionally, OT neurons discriminate the types and magnitudes of fluid reinforcers. Together, these data suggest that the processing of reward information and the orchestration of goal-directed behaviors is a global principle of the ventral striatum and have important implications for understanding the neural systems subserving addiction and mood disorders. SIGNIFICANCE STATEMENT Goal-directed behaviors are widespread among animals and underlie complex behaviors ranging from food intake, social behavior, and even pathological conditions, such as gambling and drug addiction. The ventral striatum is a neural system critical for evaluating reward information and the initiation of goal-directed behaviors. Here we

  11. A Constrained Algorithm Based NMFα for Image Representation

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. Action-based mechanisms of attention.

    OpenAIRE

    Tipper, S P; Howard, L A; Houghton, G

    1998-01-01

    Actions, which have effects in the external world, must be spatiotopically represented in the brain. The brain is capable of representing space in many different forms (e.g. retinotopic-, environment-, head- or shoulder-centred), but we maintain that actions are represented in action-centred space, meaning that, at the cellular level, the direction of movement is defined by the activity of cells. In reaching, for example, object location is defined as the direction and distance between the or...

  14. Project transition to risk based corrective action

    International Nuclear Information System (INIS)

    Judge, J.M.; Cormier, S.L.

    1996-01-01

    Many states have adopted or are considering the adoption of the America Society for Testing and Materials (ASTM) Standard E 1739, Standard for Risk Based Corrective Action (RBCA) Applied to Petroleum Release Sites. This standard is being adopted to regulate leaking underground storage tank (LUST) sites. The case studies of two LUST sites in Michigan will be presented to demonstrate the decision making process and limiting factors involved in transitioning sites to the RBCA program. Both of these case studies had been previously investigated and one was actively remediated. The first case study involves a private petroleum facility where soil and ground water have been impacted. Remediation involved a ground water pump and treat system. Subsequent monitoring during system operation indicated that analytical data were still above the Tier 1 RBSLs but below the Tier 2 SSTLs. The closure strategy that was developed was based on the compounds of concern that were below the SSTLs. A deed restriction was also developed for the site as an institutional control. The second LUST site exhibited BTEX concentrations in soil and ground water above the Tier 1 RBSLs. Due to the exceedence of the Tier 1 RBSLs, the second site required a Tier 2 assessment to develop SSTLs as remedial objectives and remove hot spots in the soil and treat the ground water to achieve closure. Again, a deed restriction was instituted along with a performance monitoring plan

  15. 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.

  16. Visual Vehicle Tracking Based on Deep Representation and Semisupervised Learning

    Directory of Open Access Journals (Sweden)

    Yingfeng Cai

    2017-01-01

    Full Text Available Discriminative tracking methods use binary classification to discriminate between the foreground and background and have achieved some useful results. However, the use of labeled training samples is insufficient for them to achieve accurate tracking. Hence, discriminative classifiers must use their own classification results to update themselves, which may lead to feedback-induced tracking drift. To overcome these problems, we propose a semisupervised tracking algorithm that uses deep representation and transfer learning. Firstly, a 2D multilayer deep belief network is trained with a large amount of unlabeled samples. The nonlinear mapping point at the top of this network is subtracted as the feature dictionary. Then, this feature dictionary is utilized to transfer train and update a deep tracker. The positive samples for training are the tracked vehicles, and the negative samples are the background images. Finally, a particle filter is used to estimate vehicle position. We demonstrate experimentally that our proposed vehicle tracking algorithm can effectively restrain drift while also maintaining the adaption of vehicle appearance. Compared with similar algorithms, our method achieves a better tracking success rate and fewer average central-pixel errors.

  17. 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...

  18. 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…

  19. Developing Action Plans Based on Strategy

    DEFF Research Database (Denmark)

    Carstensen, Peter H.; Vinter, Otto

    2018-01-01

    The authors have performed a thorough study of the change strategy literature that is the foundation for the 10 overall change strategies defined in ISO/IEC 33014. Then the authors identified eight aspects that should be considered when developing the concrete actions for executing the strategy....

  20. 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.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  4. PCANet-Based Structural Representation for Nonrigid Multimodal Medical Image Registration

    Directory of Open Access Journals (Sweden)

    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.

  5. 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...

  6. Skeleton-based human action recognition using multiple sequence alignment

    Science.gov (United States)

    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.

  7. AGAMA: Action-based galaxy modeling framework

    Science.gov (United States)

    Vasiliev, Eugene

    2018-05-01

    The AGAMA library models galaxies. It computes gravitational potential and forces, performs orbit integration and analysis, and can convert between position/velocity and action/angle coordinates. It offers a framework for finding best-fit parameters of a model from data and self-consistent multi-component galaxy models, and contains useful auxiliary utilities such as various mathematical routines. The core of the library is written in C++, and there are Python and Fortran interfaces. AGAMA may be used as a plugin for the stellar-dynamical software packages galpy (ascl:1411.008), AMUSE (ascl:1107.007), and NEMO (ascl:1010.051).

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

    Directory of Open Access Journals (Sweden)

    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.

  9. 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.

  10. Generating concept representations from examples, using set-based notation

    DEFF Research Database (Denmark)

    Galle, Per

    2000-01-01

    A database or knowledge-based system must draw on a conceptual schema that defines the domain concepts with which its user works. In the case of a system for architectural design support, for example, this might be concepts of walls, windows etc. However, making concepts explicit and expressing t...

  11. Representability in DL-Lite_R knowledge base exchange

    NARCIS (Netherlands)

    Arenas, M.; Botoeva, E.; Calvanese, D.; Ryzhikov, V.; Sherkhonov, E.

    2012-01-01

    Knowledge base exchange can be considered as a generalization of data exchange in which the aim is to exchange between a source and a target connected through mappings, not only explicit knowledge, i.e., data, but also implicit knowledge in the form of axioms. Such problem has been investigated

  12. 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.

  13. TARGET-ORIENTED GENERIC FINGERPRINT-BASED MOLECULAR REPRESENTATION

    OpenAIRE

    Petr Skoda; David Hoksza

    2014-01-01

    The screening of chemical libraries is an important step in the drug discovery process. The existing chemical libraries contain up to millions of compounds. As the screening at such scale is expensive, the virtual screening is often utilized. There exist several variants of virtual screening and ligand-based virtual screening is one of them. It utilizes the similarity of screened chemical compounds to known compounds. Besides the employed similarity measure, another aspect grea...

  14. 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

  15. Ontology and modeling patterns for state-based behavior representation

    Science.gov (United States)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; hide

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  16. 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.

  17. 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...

  18. 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

  19. 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

  20. 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

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

    Science.gov (United States)

    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…

  2. Ontology-Based Vaccine Adverse Event Representation and Analysis.

    Science.gov (United States)

    Xie, Jiangan; He, Yongqun

    2017-01-01

    Vaccine is the one of the greatest inventions of modern medicine that has contributed most to the relief of human misery and the exciting increase in life expectancy. In 1796, an English country physician, Edward Jenner, discovered that inoculating mankind with cowpox can protect them from smallpox (Riedel S, Edward Jenner and the history of smallpox and vaccination. Proceedings (Baylor University. Medical Center) 18(1):21, 2005). Based on the vaccination worldwide, we finally succeeded in the eradication of smallpox in 1977 (Henderson, Vaccine 29:D7-D9, 2011). Other disabling and lethal diseases, like poliomyelitis and measles, are targeted for eradication (Bonanni, Vaccine 17:S120-S125, 1999).Although vaccine development and administration are tremendously successful and cost-effective practices to human health, no vaccine is 100% safe for everyone because each person reacts to vaccinations differently given different genetic background and health conditions. Although all licensed vaccines are generally safe for the majority of people, vaccinees may still suffer adverse events (AEs) in reaction to various vaccines, some of which can be serious or even fatal (Haber et al., Drug Saf 32(4):309-323, 2009). Hence, the double-edged sword of vaccination remains a concern.To support integrative AE data collection and analysis, it is critical to adopt an AE normalization strategy. In the past decades, different controlled terminologies, including the Medical Dictionary for Regulatory Activities (MedDRA) (Brown EG, Wood L, Wood S, et al., Drug Saf 20(2):109-117, 1999), the Common Terminology Criteria for Adverse Events (CTCAE) (NCI, The Common Terminology Criteria for Adverse Events (CTCAE). Available from: http://evs.nci.nih.gov/ftp1/CTCAE/About.html . Access on 7 Oct 2015), and the World Health Organization (WHO) Adverse Reactions Terminology (WHO-ART) (WHO, The WHO Adverse Reaction Terminology - WHO-ART. Available from: https://www.umc-products.com/graphics/28010.pdf

  3. 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

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

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

    Science.gov (United States)

    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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. 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.…

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

    Directory of Open Access Journals (Sweden)

    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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    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.

  4. Mental Representation and Motor Imagery Training

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  6. Individual differences in action co-representation : not personal distress or subclinical psychotic experiences but sex composition modulates joint action performance

    NARCIS (Netherlands)

    van der Weiden, Anouk; Aarts, Henk; Prikken, Merel; van Haren, Neeltje E M

    2015-01-01

    Successful social interaction requires the ability to integrate as well as distinguish own and others' actions. Normally, the integration and distinction of self and other are a well-balanced process, occurring without much effort or conscious attention. However, not everyone is blessed with the

  7. 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.

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    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.

  15. 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%.

  16. 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...

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  19. Predicate Structures, Gesture, and Simultaneity in the Representation of Action in British Sign Language: Evidence From Deaf Children and Adults

    Science.gov (United States)

    Cormier, Kearsy

    2013-01-01

    British Sign Language (BSL) signers use a variety of structures, such as constructed action (CA), depicting constructions (DCs), or lexical verbs, to represent action and other verbal meanings. This study examines the use of these verbal predicate structures and their gestural counterparts, both separately and simultaneously, in narratives by deaf children with various levels of exposure to BSL (ages 5;1 to 7;5) and deaf adult native BSL signers. Results reveal that all groups used the same types of predicative structures, including children with minimal BSL exposure. However, adults used CA, DCs, and/or lexical signs simultaneously more frequently than children. These results suggest that simultaneous use of CA with lexical and depicting predicates is more complex than the use of these predicate structures alone and thus may take deaf children more time to master. PMID:23670881

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

    Science.gov (United States)

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

    2009-04-21

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

  1. Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

    Science.gov (United States)

    An, Gary

    2009-01-01

    The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

  2. 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.

  3. 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.

  4. 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.

  5. 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).

  6. 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...

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

    Science.gov (United States)

    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.

  8. Rule-based emergency action level monitor prototype

    International Nuclear Information System (INIS)

    Touchton, R.A.; Gunter, A.D.; Cain, D.

    1985-01-01

    In late 1983, the Electric Power Research Institute (EPRI) began a program to encourage and stimulate the development of artificial intelligence (AI) applications for the nuclear industry. Development of a rule-based emergency action level classification system prototype is discussed. The paper describes both the full prototype currently under development and the completed, simplified prototype

  9. Robot soccer action selection based on Q learning

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

  10. Gain Scheduling of Observer-Based Controllers with Integral Action

    DEFF Research Database (Denmark)

    Trangbæk, Klaus; Stoustrup, Jakob; Bendtsen, Jan Dimon

    2006-01-01

     This paper presents a method for continuous gain scheduling of  observer-based controllers with integral action. Given two stabilising controllers for a given system, explicit state space formulae are presented, allowing to change gradually from one  controller to the other while preserving...

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. A searching and reporting system for relational databases using a graph-based metadata representation.

    Science.gov (United States)

    Hewitt, Robin; Gobbi, Alberto; Lee, Man-Ling

    2005-01-01

    Relational databases are the current standard for storing and retrieving data in the pharmaceutical and biotech industries. However, retrieving data from a relational database requires specialized knowledge of the database schema and of the SQL query language. At Anadys, we have developed an easy-to-use system for searching and reporting data in a relational database to support our drug discovery project teams. This system is fast and flexible and allows users to access all data without having to write SQL queries. This paper presents the hierarchical, graph-based metadata representation and SQL-construction methods that, together, are the basis of this system's capabilities.

  18. Improving Feature Representation Based on a Neural Network for Author Profiling in Social Media Texts.

    Science.gov (United States)

    Gómez-Adorno, Helena; Markov, Ilia; Sidorov, Grigori; Posadas-Durán, Juan-Pablo; Sanchez-Perez, Miguel A; Chanona-Hernandez, Liliana

    2016-01-01

    We introduce a lexical resource for preprocessing social media data. We show that a neural network-based feature representation is enhanced by using this resource. We conducted experiments on the PAN 2015 and PAN 2016 author profiling corpora and obtained better results when performing the data preprocessing using the developed lexical resource. The resource includes dictionaries of slang words, contractions, abbreviations, and emoticons commonly used in social media. Each of the dictionaries was built for the English, Spanish, Dutch, and Italian languages. The resource is freely available.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. A fast image encryption system based on chaotic maps with finite precision representation

    International Nuclear Information System (INIS)

    Kwok, H.S.; Tang, Wallace K.S.

    2007-01-01

    In this paper, a fast chaos-based image encryption system with stream cipher structure is proposed. In order to achieve a fast throughput and facilitate hardware realization, 32-bit precision representation with fixed point arithmetic is assumed. The major core of the encryption system is a pseudo-random keystream generator based on a cascade of chaotic maps, serving the purpose of sequence generation and random mixing. Unlike the other existing chaos-based pseudo-random number generators, the proposed keystream generator not only achieves a very fast throughput, but also passes the statistical tests of up-to-date test suite even under quantization. The overall design of the image encryption system is to be explained while detail cryptanalysis is given and compared with some existing schemes

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

    Science.gov (United States)

    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…

  8. Rigid Body Attitude Control Based on a Manifold Representation of Direction Cosine Matrices

    International Nuclear Information System (INIS)

    Nakath, David; Clemens, Joachim; Rachuy, Carsten

    2017-01-01

    Autonomous systems typically actively observe certain aspects of their surroundings, which makes them dependent on a suitable controller. However, building an attitude controller for three degrees of freedom is a challenging task, mainly due to singularities in the different parametrizations of the three dimensional rotation group SO (3). Thus, we propose an attitude controller based on a manifold representation of direction cosine matrices: In state space, the attitude is globally and uniquely represented as a direction cosine matrix R ∈ SO (3). However, differences in the state space, i.e., the attitude errors, are exposed to the controller in the vector space ℝ 3 . This is achieved by an operator, which integrates the matrix logarithm mapping from SO (3) to so(3) and the map from so(3) to ℝ 3 . Based on this representation, we derive a proportional and derivative feedback controller, whose output has an upper bound to prevent actuator saturation. Additionally, the feedback is preprocessed by a particle filter to account for measurement and state transition noise. We evaluate our approach in a simulator in three different spacecraft maneuver scenarios: (i) stabilizing, (ii) rest-to-rest, and (iii) nadir-pointing. The controller exhibits stable behavior from initial attitudes near and far from the setpoint. Furthermore, it is able to stabilize a spacecraft and can be used for nadir-pointing maneuvers. (paper)

  9. 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.

  10. Improving Mobility Performance in Low Vision With a Distance-Based Representation of the Visual Scene.

    Science.gov (United States)

    van Rheede, Joram J; Wilson, Iain R; Qian, Rose I; Downes, Susan M; Kennard, Christopher; Hicks, Stephen L

    2015-07-01

    Severe visual impairment can have a profound impact on personal independence through its effect on mobility. We investigated whether the mobility of people with vision low enough to be registered as blind could be improved by presenting the visual environment in a distance-based manner for easier detection of obstacles. We accomplished this by developing a pair of "residual vision glasses" (RVGs) that use a head-mounted depth camera and displays to present information about the distance of obstacles to the wearer as brightness, such that obstacles closer to the wearer are represented more brightly. We assessed the impact of the RVGs on the mobility performance of visually impaired participants during the completion of a set of obstacle courses. Participant position was monitored continuously, which enabled us to capture the temporal dynamics of mobility performance. This allowed us to find correlates of obstacle detection and hesitations in walking behavior, in addition to the more commonly used measures of trial completion time and number of collisions. All participants were able to use the smart glasses to navigate the course, and mobility performance improved for those visually impaired participants with the worst prior mobility performance. However, walking speed was slower and hesitations increased with the altered visual representation. A depth-based representation of the visual environment may offer low vision patients improvements in independent mobility. It is important for further work to explore whether practice can overcome the reductions in speed and increased hesitation that were observed in our trial.

  11. 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.

  12. 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.

  13. Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

    Science.gov (United States)

    Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

    2017-08-01

    Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

  14. 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.

  15. Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 (United States); Chen, Ken Chung [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Stomatology, National Cheng Kung University Medical College and Hospital, Tainan, Taiwan 70403 (China); Shen, Steve G. F.; Yan, Jin [Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Lee, Philip K. M.; Chow, Ben [Hong Kong Dental Implant and Maxillofacial Centre, Hong Kong, China 999077 (China); Liu, Nancy X. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 and Department of Oral and Maxillofacial Surgery, Peking University School and Hospital of Stomatology, Beijing, China 100050 (China); Xia, James J. [Department of Oral and Maxillofacial Surgery, Houston Methodist Hospital Research Institute, Houston, Texas 77030 (United States); Department of Surgery (Oral and Maxillofacial Surgery), Weill Medical College, Cornell University, New York, New York 10065 (United States); Department of Oral and Craniomaxillofacial Surgery and Science, Shanghai Ninth People' s Hospital, Shanghai Jiao Tong University College of Medicine, Shanghai, China 200011 (China); Shen, Dinggang, E-mail: dgshen@med.unc.edu [Department of Radiology and BRIC, University of North Carolina at Chapel Hill, North Carolina 27599 and Department of Brain and Cognitive Engineering, Korea University, Seoul, 136701 (Korea, Republic of)

    2014-04-15

    Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

  16. Automated bone segmentation from dental CBCT images using patch-based sparse representation and convex optimization

    International Nuclear Information System (INIS)

    Wang, Li; Gao, Yaozong; Shi, Feng; Liao, Shu; Li, Gang; Chen, Ken Chung; Shen, Steve G. F.; Yan, Jin; Lee, Philip K. M.; Chow, Ben; Liu, Nancy X.; Xia, James J.; Shen, Dinggang

    2014-01-01

    Purpose: Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate three-dimensional (3D) models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the poor image quality, including very low signal-to-noise ratio and the widespread image artifacts such as noise, beam hardening, and inhomogeneity, it is challenging to segment the CBCT images. In this paper, the authors present a new automatic segmentation method to address these problems. Methods: To segment CBCT images, the authors propose a new method for fully automated CBCT segmentation by using patch-based sparse representation to (1) segment bony structures from the soft tissues and (2) further separate the mandible from the maxilla. Specifically, a region-specific registration strategy is first proposed to warp all the atlases to the current testing subject and then a sparse-based label propagation strategy is employed to estimate a patient-specific atlas from all aligned atlases. Finally, the patient-specific atlas is integrated into amaximum a posteriori probability-based convex segmentation framework for accurate segmentation. Results: The proposed method has been evaluated on a dataset with 15 CBCT images. The effectiveness of the proposed region-specific registration strategy and patient-specific atlas has been validated by comparing with the traditional registration strategy and population-based atlas. The experimental results show that the proposed method achieves the best segmentation accuracy by comparison with other state-of-the-art segmentation methods. Conclusions: The authors have proposed a new CBCT segmentation method by using patch-based sparse representation and convex optimization, which can achieve considerably accurate segmentation results in CBCT

  17. 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...

  18. 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.

  19. 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.

  20. Radiation exposure map based on fuzzy logic for the representation of areas with high natural background

    International Nuclear Information System (INIS)

    Vasconcelos, Wagner Eustaquio de; Lira, Carlos Alberto Brayner de Oliveira

    2009-01-01

    The identification of areas with high concentrations of natural radionuclides is an important task in classifying these areas in relation to the health risk for residents in the region. The aim of this work is to identify areas of high exposure to nuclear radiation using a geographic representation based on the theory of fuzzy sets. Radiometric data obtained from previous works developed in a region of high concentrations in natural uranium were used to create a fuzzy map of the local radiation levels. During the image processing, a nonlinear filter was applied to eliminate noise i.e. to reduce isolated pixels that would eventually cause major uncertainties in the results. A resulting image was geographically positioned (WGS40) and obtained in gray scale. This image was fuzzified for membership functions that represent linguistic variables as low exposure, medium exposure and high exposure. After representing the membership grade in a RGB (red, green and blue) image it was possible to visualize the radiation level in the area of exposure. When compared to data from the region, results demonstrated the good efficiency of the technique here employed for the representation of areas with high radioactivity levels. The image obtained also provided important information about those areas where exposure to radiation is more pronounced. Hence, the fuzzy map can be applied in decision-making of experts when a risk situation is identified. (author)

  1. 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.

  2. Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach.

    Science.gov (United States)

    Li, Qing; Liang, Steven Y

    2018-04-20

    Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method.

  3. 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.

  4. 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.

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

    Science.gov (United States)

    Belopolsky, Artem V; Theeuwes, Jan

    2009-10-01

    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 Psychology--Human Perception and Performance, 24(3), 780-790]. Three main issues were examined. First, Experiments 1-3 demonstrated that inhibition and not facilitation of visual processing is often observed at the memorized location during the retention interval. This inhibition was caused by keeping a location in memory and not by the exogenous nature of the memory cue. Second, Experiment 4 showed that inhibition of the memorized location does not lead to any significant impairment in memory accuracy. Finally, Experiment 5 connected current results to the previous findings and demonstrated facilitation of processing at the memorized location. Importantly, facilitation of processing did not lead to more accurate memory performance. The present results challenge the functional role of attention in maintenance of spatial working memory representations.

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

    Directory of Open Access Journals (Sweden)

    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.

  7. Gender in facial representations: a contrast-based study of adaptation within and between the sexes.

    Science.gov (United States)

    Oruç, Ipek; Guo, Xiaoyue M; Barton, Jason J S

    2011-01-18

    Face aftereffects are proving to be an effective means of examining the properties of face-specific processes in the human visual system. We examined the role of gender in the neural representation of faces using a contrast-based adaptation method. If faces of different genders share the same representational face space, then adaptation to a face of one gender should affect both same- and different-gender faces. Further, if these aftereffects differ in magnitude, this may indicate distinct gender-related factors in the organization of this face space. To control for a potential confound between physical similarity and gender, we used a Bayesian ideal observer and human discrimination data to construct a stimulus set in which pairs of different-gender faces were equally dissimilar as same-gender pairs. We found that the recognition of both same-gender and different-gender faces was suppressed following a brief exposure of 100 ms. Moreover, recognition was more suppressed for test faces of a different-gender than those of the same-gender as the adaptor, despite the equivalence in physical and psychophysical similarity. Our results suggest that male and female faces likely occupy the same face space, allowing transfer of aftereffects between the genders, but that there are special properties that emerge along gender-defining dimensions of this space.

  8. Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

    Science.gov (United States)

    Xie, Qi; Zhao, Qian; Meng, Deyu; Xu, Zongben

    2017-08-02

    It is well known that the sparsity/low-rank of a vector/matrix can be rationally measured by nonzero-entries-number ($l_0$ norm)/nonzero- singular-values-number (rank), respectively. However, data from real applications are often generated by the interaction of multiple factors, which obviously cannot be sufficiently represented by a vector/matrix, while a high order tensor is expected to provide more faithful representation to deliver the intrinsic structure underlying such data ensembles. Unlike the vector/matrix case, constructing a rational high order sparsity measure for tensor is a relatively harder task. To this aim, in this paper we propose a measure for tensor sparsity, called Kronecker-basis-representation based tensor sparsity measure (KBR briefly), which encodes both sparsity insights delivered by Tucker and CANDECOMP/PARAFAC (CP) low-rank decompositions for a general tensor. Then we study the KBR regularization minimization (KBRM) problem, and design an effective ADMM algorithm for solving it, where each involved parameter can be updated with closed-form equations. Such an efficient solver makes it possible to extend KBR to various tasks like tensor completion and tensor robust principal component analysis. A series of experiments, including multispectral image (MSI) denoising, MSI completion and background subtraction, substantiate the superiority of the proposed methods beyond state-of-the-arts.

  9. 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.

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

    Science.gov (United States)

    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.

  11. Vision-based Human Action Classification Using Adaptive Boosting Algorithm

    KAUST Repository

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

    2018-01-01

    Precise recognition of human action is a key enabler for the development of many applications including autonomous robots for medical diagnosis and surveillance of elderly people in home environment. This paper addresses the human action recognition based on variation in body shape. Specifically, we divide the human body into five partitions that correspond to five partial occupancy areas. For each frame, we calculated area ratios and used them as input data for recognition stage. Here, we consider six classes of activities namely: walking, standing, bending, lying, squatting, and sitting. In this paper, we proposed an efficient human action recognition scheme, which takes advantages of superior discrimination capacity of AdaBoost algorithm. We validated the effectiveness of this approach by using experimental data from two publicly available databases fall detection databases from the University of Rzeszow’s and the Universidad de Málaga fall detection datasets. We provided comparisons of the proposed approach with state-of-the-art classifiers based on the neural network, K-nearest neighbor, support vector machine and naïve Bayes and showed that we achieve better results in discriminating human gestures.

  12. Vision-based Human Action Classification Using Adaptive Boosting Algorithm

    KAUST Repository

    Zerrouki, Nabil

    2018-05-07

    Precise recognition of human action is a key enabler for the development of many applications including autonomous robots for medical diagnosis and surveillance of elderly people in home environment. This paper addresses the human action recognition based on variation in body shape. Specifically, we divide the human body into five partitions that correspond to five partial occupancy areas. For each frame, we calculated area ratios and used them as input data for recognition stage. Here, we consider six classes of activities namely: walking, standing, bending, lying, squatting, and sitting. In this paper, we proposed an efficient human action recognition scheme, which takes advantages of superior discrimination capacity of AdaBoost algorithm. We validated the effectiveness of this approach by using experimental data from two publicly available databases fall detection databases from the University of Rzeszow’s and the Universidad de Málaga fall detection datasets. We provided comparisons of the proposed approach with state-of-the-art classifiers based on the neural network, K-nearest neighbor, support vector machine and naïve Bayes and showed that we achieve better results in discriminating human gestures.

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

    Directory of Open Access Journals (Sweden)

    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

  14. Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

    Directory of Open Access Journals (Sweden)

    Bo Kong

    2017-01-01

    Full Text Available In an integrated radar-communication network, multiuser access techniques with minimal performance degradation and without range-Doppler ambiguities are required, especially in a dense user environment. In this paper, a multiuser access scheme with random subcarrier allocation mechanism is proposed for orthogonal frequency division multiplexing (OFDM based integrated radar-communication networks. The expression of modulation Symbol-Domain method combined with sparse representation (SR for range-Doppler estimation is introduced and a parallel reconstruction algorithm is employed. The radar target detection performance is improved with less spectrum occupation. Additionally, a Doppler frequency detector is exploited to decrease the computational complexity. Numerical simulations show that the proposed method outperforms the traditional modulation Symbol-Domain method under ideal and realistic nonideal scenarios.

  15. Hologram representation of design data in an expert system knowledge base

    Science.gov (United States)

    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.

  16. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Directory of Open Access Journals (Sweden)

    Su Yang

    Full Text Available Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1 Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2 The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3 The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  17. Spatiotemporal Context Awareness for Urban Traffic Modeling and Prediction: Sparse Representation Based Variable Selection.

    Science.gov (United States)

    Yang, Su; Shi, Shixiong; Hu, Xiaobing; Wang, Minjie

    2015-01-01

    Spatial-temporal correlations among the data play an important role in traffic flow prediction. Correspondingly, traffic modeling and prediction based on big data analytics emerges due to the city-scale interactions among traffic flows. A new methodology based on sparse representation is proposed to reveal the spatial-temporal dependencies among traffic flows so as to simplify the correlations among traffic data for the prediction task at a given sensor. Three important findings are observed in the experiments: (1) Only traffic flows immediately prior to the present time affect the formation of current traffic flows, which implies the possibility to reduce the traditional high-order predictors into an 1-order model. (2) The spatial context relevant to a given prediction task is more complex than what is assumed to exist locally and can spread out to the whole city. (3) The spatial context varies with the target sensor undergoing prediction and enlarges with the increment of time lag for prediction. Because the scope of human mobility is subject to travel time, identifying the varying spatial context against time lag is crucial for prediction. Since sparse representation can capture the varying spatial context to adapt to the prediction task, it outperforms the traditional methods the inputs of which are confined as the data from a fixed number of nearby sensors. As the spatial-temporal context for any prediction task is fully detected from the traffic data in an automated manner, where no additional information regarding network topology is needed, it has good scalability to be applicable to large-scale networks.

  18. 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.

  19. 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...

  20. 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.

  1. Epileptic Seizure Detection with Log-Euclidean Gaussian Kernel-Based Sparse Representation.

    Science.gov (United States)

    Yuan, Shasha; Zhou, Weidong; Wu, Qi; Zhang, Yanli

    2016-05-01

    Epileptic seizure detection plays an important role in the diagnosis of epilepsy and reducing the massive workload of reviewing electroencephalography (EEG) recordings. In this work, a novel algorithm is developed to detect seizures employing log-Euclidean Gaussian kernel-based sparse representation (SR) in long-term EEG recordings. Unlike the traditional SR for vector data in Euclidean space, the log-Euclidean Gaussian kernel-based SR framework is proposed for seizure detection in the space of the symmetric positive definite (SPD) matrices, which form a Riemannian manifold. Since the Riemannian manifold is nonlinear, the log-Euclidean Gaussian kernel function is applied to embed it into a reproducing kernel Hilbert space (RKHS) for performing SR. The EEG signals of all channels are divided into epochs and the SPD matrices representing EEG epochs are generated by covariance descriptors. Then, the testing samples are sparsely coded over the dictionary composed by training samples utilizing log-Euclidean Gaussian kernel-based SR. The classification of testing samples is achieved by computing the minimal reconstructed residuals. The proposed method is evaluated on the Freiburg EEG dataset of 21 patients and shows its notable performance on both epoch-based and event-based assessments. Moreover, this method handles multiple channels of EEG recordings synchronously which is more speedy and efficient than traditional seizure detection methods.

  2. Commitment-based action: Rational choice theory and contrapreferential choice

    Directory of Open Access Journals (Sweden)

    Radovanović Bojana

    2014-01-01

    Full Text Available This paper focuses on Sen’s concept of contrapreferential choice. Sen has developed this concept in order to overcome weaknesses of the rational choice theory. According to rational choice theory a decision-maker can be always seen as someone who maximises utility, and each choice he makes as the one that brings to him the highest level of personal wellbeing. Sen argues that in some situations we chose alternatives that bring us lower level of wellbeing than we could achieve if we had chosen some other alternative available to us. This happens when we base our decisions on moral principles, when we act out of duty. Sen calls such action a commitment-based action. When we act out of commitment we actually neglect our preferences and thus we make a contrapreferential choice, as Sen argues. This paper shows that, contrary to Sen, a commitment-based action can be explained within the framework of rational choice theory. However, when each choice we make can be explained within the framework of rational choice theory, when in everything we do maximisation principle can be loaded, then the variety of our motives and traits is lost, and the explanatory power of the rational choice theory is questionable. [Projekat Ministarstva nauke Republike Srbije, br. 47009: Evropske integracije i društveno-ekonomske promene privrede Srbije na putu ka EU i br. 179015: Izazovi i perspektive strukturnih promena u Srbiji: Strateški pravci ekonomskog razvoja i usklađivanje sa zahtevima EU

  3. Building the knowledge base for environmental action and sustainability

    DEFF Research Database (Denmark)

    2015-01-01

    was “Building the knowledge base for environmental action and sustainability”. The joint conference was designed to facilitate ‘within‐the‐domain’, as well as to create a space for developing synergies between the two communities. Altogether 125 research and applied papers (including extended abstracts) from 42......“Knowledge is power” (Sir Francis Bacon (1561 – 1626), Religious Meditations, Of Heresis, 1597) “Science is organised knowledge. Wisdom is organised life” (Immanuel Kant (1724 – 1804)) The 29th International Conference on Informatics for Environmental Protection and the third International...

  4. Deep learning based beat event detection in action movie franchises

    Science.gov (United States)

    Ejaz, N.; Khan, U. A.; Martínez-del-Amor, M. A.; Sparenberg, H.

    2018-04-01

    Automatic understanding and interpretation of movies can be used in a variety of ways to semantically manage the massive volumes of movies data. "Action Movie Franchises" dataset is a collection of twenty Hollywood action movies from five famous franchises with ground truth annotations at shot and beat level of each movie. In this dataset, the annotations are provided for eleven semantic beat categories. In this work, we propose a deep learning based method to classify shots and beat-events on this dataset. The training dataset for each of the eleven beat categories is developed and then a Convolution Neural Network is trained. After finding the shot boundaries, key frames are extracted for each shot and then three classification labels are assigned to each key frame. The classification labels for each of the key frames in a particular shot are then used to assign a unique label to each shot. A simple sliding window based method is then used to group adjacent shots having the same label in order to find a particular beat event. The results of beat event classification are presented based on criteria of precision, recall, and F-measure. The results are compared with the existing technique and significant improvements are recorded.

  5. 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...

  6. GrandBase: generating actionable knowledge from Big Data

    Directory of Open Access Journals (Sweden)

    Xiu Susie Fang

    2017-08-01

    Full Text Available Purpose – This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB, called GrandBase. Design/methodology/approach – In particular, this study extracts new predicates from four types of data sources, namely, Web texts, Document Object Model (DOM trees, existing KBs and query stream to augment the ontology of the existing KB (i.e. Freebase. In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed. Findings – Empirical studies demonstrate the effectiveness of the approaches presented in this study and the potential of GrandBase. The future research directions regarding GrandBase construction and extension has also been discussed. Originality/value – To revolutionize our modern society by using the wisdom of Big Data, considerable KBs have been constructed to feed the massive knowledge-driven applications with Resource Description Framework triples. The important challenges for KB construction include extracting information from large-scale, possibly conflicting and different-structured data sources (i.e. the knowledge extraction problem and reconciling the conflicts that reside in the sources (i.e. the truth discovery problem. Tremendous research efforts have been contributed on both problems. However, the existing KBs are far from being comprehensive and accurate: first, existing knowledge extraction systems retrieve data from limited types of Web sources; second, existing truth discovery approaches commonly assume each predicate has only one true value. In this paper, the focus is on the problem of generating actionable knowledge from Big Data. A system is proposed, which consists of two phases, namely, knowledge extraction and truth discovery, to construct a broader KB, called GrandBase.

  7. 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.

  8. Patent Keyword Extraction Algorithm Based on Distributed Representation for Patent Classification

    Directory of Open Access Journals (Sweden)

    Jie Hu

    2018-02-01

    Full Text Available Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM classification, which are valuable when human-annotated keywords are not available. We used a standard benchmark dataset and a homemade patent dataset to evaluate the performance of PKEA. Our patent dataset includes 2500 patents from five distinct technological fields related to autonomous cars (GPS systems, lidar systems, object recognition systems, radar systems, and vehicle control systems. We compared our method with Frequency, Term Frequency-Inverse Document Frequency (TF-IDF, TextRank and Rapid Automatic Keyword Extraction (RAKE. The experimental results show that our proposed algorithm provides a promising way to extract keywords from patent texts for patent classification.

  9. 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.

  10. 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.

  11. 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…

  12. 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…

  13. 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.

  14. 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.

  15. An application to pulmonary emphysema classification based on model of texton learning by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2012-03-01

    We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

  16. Investigating shape representation using sensitivity to part- and axis-based transformations.

    Science.gov (United States)

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

    2016-09-01

    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, orientation and location were applied to a small part attached to a larger base of a two-part shape. Increment thresholds were estimated for each transformation using a 2IFC procedure. Thresholds were converted into common units of shape difference to enable comparisons across transformations. Higher sensitivity was consistently found for transformations involving a parameter of a single part (length, width, curvature) than those involving spatial relations between two parts (relative orientation and location), suggesting a single-part superiority effect. Moreover, sensitivity to shifts in part location - a biomechanically implausible shape transformation - was consistently poorest. The influence of region-based geometry was investigated via stereoscopic manipulation of figure and ground. Sensitivity was compared across positive parts (protrusions) and negative parts (indentations) for transformations involving a change in orientation or location. For changes in part orientation (biomechanically plausible), sensitivity was better for positive than negative parts; whereas for changes in part location (biomechanically implausible), no systematic difference was observed. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Speckle Reduction on Ultrasound Liver Images Based on a Sparse Representation over a Learned Dictionary

    Directory of Open Access Journals (Sweden)

    Mohamed Yaseen Jabarulla

    2018-05-01

    Full Text Available Ultrasound images are corrupted with multiplicative noise known as speckle, which reduces the effectiveness of image processing and hampers interpretation. This paper proposes a multiplicative speckle suppression technique for ultrasound liver images, based on a new signal reconstruction model known as sparse representation (SR over dictionary learning. In the proposed technique, the non-uniform multiplicative signal is first converted into additive noise using an enhanced homomorphic filter. This is followed by pixel-based total variation (TV regularization and patch-based SR over a dictionary trained using K-singular value decomposition (KSVD. Finally, the split Bregman algorithm is used to solve the optimization problem and estimate the de-speckled image. The simulations performed on both synthetic and clinical ultrasound images for speckle reduction, the proposed technique achieved peak signal-to-noise ratios of 35.537 dB for the dictionary trained on noisy image patches and 35.033 dB for the dictionary trained using a set of reference ultrasound image patches. Further, the evaluation results show that the proposed method performs better than other state-of-the-art denoising algorithms in terms of both peak signal-to-noise ratio and subjective visual quality assessment.

  18. Map-based model of the cardiac action potential

    International Nuclear Information System (INIS)

    Pavlov, Evgeny A.; Osipov, Grigory V.; Chan, C.K.; Suykens, Johan A.K.

    2011-01-01

    A simple computationally efficient model which is capable of replicating the basic features of cardiac cell action potential is proposed. The model is a four-dimensional map and demonstrates good correspondence with real cardiac cells. Various regimes of cardiac activity, which can be reproduced by the proposed model, are shown. Bifurcation mechanisms of these regimes transitions are explained using phase space analysis. The dynamics of 1D and 2D lattices of coupled maps which model the behavior of electrically connected cells is discussed in the context of synchronization theory. -- Highlights: → Recent experimental-data based models are complicated for analysis and simulation. → The simplified map-based model of the cardiac cell is constructed. → The model is capable for replication of different types of cardiac activity. → The spatio-temporal dynamics of ensembles of coupled maps are investigated. → Received data are analyzed in context of biophysical processes in the myocardium.

  19. Map-based model of the cardiac action potential

    Energy Technology Data Exchange (ETDEWEB)

    Pavlov, Evgeny A., E-mail: genie.pavlov@gmail.com [Department of Computational Mathematics and Cybernetics, Nizhny Novgorod State University, 23, Gagarin Avenue, 603950 Nizhny Novgorod (Russian Federation); Osipov, Grigory V. [Department of Computational Mathematics and Cybernetics, Nizhny Novgorod State University, 23, Gagarin Avenue, 603950 Nizhny Novgorod (Russian Federation); Chan, C.K. [Institute of Physics, Academia Sinica, 128 Sec. 2, Academia Road, Nankang, Taipei 115, Taiwan (China); Suykens, Johan A.K. [K.U. Leuven, ESAT-SCD/SISTA, Kasteelpark Arenberg 10, B-3001 Leuven (Heverlee) (Belgium)

    2011-07-25

    A simple computationally efficient model which is capable of replicating the basic features of cardiac cell action potential is proposed. The model is a four-dimensional map and demonstrates good correspondence with real cardiac cells. Various regimes of cardiac activity, which can be reproduced by the proposed model, are shown. Bifurcation mechanisms of these regimes transitions are explained using phase space analysis. The dynamics of 1D and 2D lattices of coupled maps which model the behavior of electrically connected cells is discussed in the context of synchronization theory. -- Highlights: → Recent experimental-data based models are complicated for analysis and simulation. → The simplified map-based model of the cardiac cell is constructed. → The model is capable for replication of different types of cardiac activity. → The spatio-temporal dynamics of ensembles of coupled maps are investigated. → Received data are analyzed in context of biophysical processes in the myocardium.

  20. 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.

  1. 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.

  2. Infants Prospectively Control Reaching Based on the Difficulty of Future Actions: To What Extent Can Infants' Multiple-Step Actions Be Explained by Fitts' Law?

    Science.gov (United States)

    Gottwald, Janna M.; De Bortoli Vizioli, Aurora; Lindskog, Marcus; Nyström, Pär; L. Ekberg, Therese; von Hofsten, Claes; Gredebäck, Gustaf

    2017-01-01

    Prospective motor control, a key element of action planning, is the ability to adjust one's actions with respect to task demands and action goals in an anticipatory manner. The current study investigates whether 14-month-olds can prospectively control their reaching actions based on the difficulty of the subsequent action. We used a reach-to-place…

  3. Students Mental Representation of Biology Diagrams/Pictures Conventions Based on Formation of Causal Network

    Science.gov (United States)

    Sampurno, A. W.; Rahmat, A.; Diana, S.

    2017-09-01

    Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.

  4. Media Representations of Breech Birth: A Prospective Analysis of Web-Based News Reports.

    Science.gov (United States)

    Petrovska, Karolina; Sheehan, Athena; Homer, Caroline S E

    2017-07-01

    Recent research has demonstrated that the media presentation of childbirth is highly medicalized, often portraying birth as risky and dramatic. Media representation of breech presentation and birth is unexplored in this context. This study aimed to explore the content and tone of news media reports relating to breech presentation and breech birth. Google alerts were created using the terms breech and breech birth in online English-language news sites over a 3-year period from January 1, 2013, to December 31, 2015. Alerts were received daily and filed for analysis, and data were analyzed to generate themes. A total of 138 web-based news reports were gathered from 9 countries. Five themes that arose from the data included the problem of breech presentation, the high drama of vaginal breech birth, the safe option of cesarean birth versus dangers of vaginal breech birth, the defiant mother versus the saintly mother, and vaginal breech birth and medical misadventure. Media reports in this study predominantly demonstrated negative views toward breech presentation and vaginal breech birth. Cesarean birth was portrayed as the safe option for breech birth, while vaginal breech birth was associated with poor outcomes. Media presentations may impact decision making about mode of birth for pregnant women with a breech fetus. Health care providers can play an important role in balancing the media depiction of planned vaginal breech birth by providing nonjudgmental, evidence-based information to such women to facilitate informed decision making for birth. © 2017 by the American College of Nurse-Midwives.

  5. An Address Event Representation-Based Processing System for a Biped Robot

    Directory of Open Access Journals (Sweden)

    Uziel Jaramillo-Avila

    2016-02-01

    Full Text Available In recent years, several important advances have been made in the fields of both biologically inspired sensorial processing and locomotion systems, such as Address Event Representation-based cameras (or Dynamic Vision Sensors and in human-like robot locomotion, e.g., the walking of a biped robot. However, making these fields merge properly is not an easy task. In this regard, Neuromorphic Engineering is a fast-growing research field, the main goal of which is the biologically inspired design of hybrid hardware systems in order to mimic neural architectures and to process information in the manner of the brain. However, few robotic applications exist to illustrate them. The main goal of this work is to demonstrate, by creating a closed-loop system using only bio-inspired techniques, how such applications can work properly. We present an algorithm using Spiking Neural Networks (SNN for a biped robot equipped with a Dynamic Vision Sensor, which is designed to follow a line drawn on the floor. This is a commonly used method for demonstrating control techniques. Most of them are fairly simple to implement without very sophisticated components; however, it can still serve as a good test in more elaborate circumstances. In addition, the locomotion system proposed is able to coordinately control the six DOFs of a biped robot in switching between basic forms of movement. The latter has been implemented as a FPGA-based neuromorphic system. Numerical tests and hardware validation are presented.

  6. Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism.

    Science.gov (United States)

    Liu, Qingping; Wang, Jiahao; Zhu, Yan; He, Yongqun

    2017-12-21

    Rheumatism represents any disease condition marked with inflammation and pain in the joints, muscles, or connective tissues. Many traditional Chinese drugs have been used for a long time to treat rheumatism. However, a comprehensive information source for these drugs is still missing, and their anti-rheumatism mechanisms remain unclear. An ontology for anti-rheumatism traditional Chinese drugs would strongly support the representation, analysis, and understanding of these drugs. In this study, we first systematically collected reported information about 26 traditional Chinese decoction pieces drugs, including their chemical ingredients and adverse events (AEs). By mostly reusing terms from existing ontologies (e.g., TCMDPO for traditional Chinese medicines, NCBITaxon for taxonomy, ChEBI for chemical elements, and OAE for adverse events) and making semantic axioms linking different entities, we developed the Ontology of Chinese Medicine for Rheumatism (OCMR) that includes over 3000 class terms. Our OCMR analysis found that these 26 traditional Chinese decoction pieces are made from anatomic entities (e.g., root and stem) from 3 Bilateria animals and 23 Mesangiospermae plants. Anti-inflammatory and antineoplastic roles are important for anti-rheumatism drugs. Using the total of 555 unique ChEBI chemical entities identified from these drugs, our ChEBI-based classification analysis identified 18 anti-inflammatory, 33 antineoplastic chemicals, and 9 chemicals (including 3 diterpenoids and 3 triterpenoids) having both anti-inflammatory and antineoplastic roles. Furthermore, our study detected 22 diterpenoids and 23 triterpenoids, including 16 pentacyclic triterpenoids that are likely bioactive against rheumatism. Six drugs were found to be associated with 184 unique AEs, including three AEs (i.e., dizziness, nausea and vomiting, and anorexia) each associated with 5 drugs. Several chemical entities are classified as neurotoxins (e.g., diethyl phthalate) and allergens (e

  7. Comprehensive evaluation of SNP identification with the Restriction Enzyme-based Reduced Representation Library (RRL method

    Directory of Open Access Journals (Sweden)

    Du Ye

    2012-02-01

    Full Text Available Abstract Background Restriction Enzyme-based Reduced Representation Library (RRL method represents a relatively feasible and flexible strategy used for Single Nucleotide Polymorphism (SNP identification in different species. It has remarkable advantage of reducing the complexity of the genome by orders of magnitude. However, comprehensive evaluation for actual efficacy of SNP identification by this method is still unavailable. Results In order to evaluate the efficacy of Restriction Enzyme-based RRL method, we selected Tsp 45I enzyme which covers 266 Mb flanking region of the enzyme recognition site according to in silico simulation on human reference genome, then we sequenced YH RRL after Tsp 45I treatment and obtained reads of which 80.8% were mapped to target region with an 20-fold average coverage, about 96.8% of target region was covered by at least one read and 257 K SNPs were identified in the region using SOAPsnp software. Compared with whole genome resequencing data, we observed false discovery rate (FDR of 13.95% and false negative rate (FNR of 25.90%. The concordance rate of homozygote loci was over 99.8%, but that of heterozygote were only 92.56%. Repeat sequences and bases quality were proved to have a great effect on the accuracy of SNP calling, SNPs in recognition sites contributed evidently to the high FNR and the low concordance rate of heterozygote. Our results indicated that repeat masking and high stringent filter criteria could significantly decrease both FDR and FNR. Conclusions This study demonstrates that Restriction Enzyme-based RRL method was effective for SNP identification. The results highlight the important role of bias and the method-derived defects represented in this method and emphasize the special attentions noteworthy.

  8. Applying representational state transfer (REST) architecture to archetype-based electronic health record systems

    Science.gov (United States)

    2013-01-01

    Background The openEHR project and the closely related ISO 13606 standard have defined structures supporting the content of Electronic Health Records (EHRs). However, there is not yet any finalized openEHR specification of a service interface to aid application developers in creating, accessing, and storing the EHR content. The aim of this paper is to explore how the Representational State Transfer (REST) architectural style can be used as a basis for a platform-independent, HTTP-based openEHR service interface. Associated benefits and tradeoffs of such a design are also explored. Results The main contribution is the formalization of the openEHR storage, retrieval, and version-handling semantics and related services into an implementable HTTP-based service interface. The modular design makes it possible to prototype, test, replicate, distribute, cache, and load-balance the system using ordinary web technology. Other contributions are approaches to query and retrieval of the EHR content that takes caching, logging, and distribution into account. Triggering on EHR change events is also explored. A final contribution is an open source openEHR implementation using the above-mentioned approaches to create LiU EEE, an educational EHR environment intended to help newcomers and developers experiment with and learn about the archetype-based EHR approach and enable rapid prototyping. Conclusions Using REST addressed many architectural concerns in a successful way, but an additional messaging component was needed to address some architectural aspects. Many of our approaches are likely of value to other archetype-based EHR implementations and may contribute to associated service model specifications. PMID:23656624

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

    Science.gov (United States)

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

    2015-07-01

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

  10. Ontology-based data integration from heterogeneous urban systems : A knowledge representation framework for smart cities

    NARCIS (Netherlands)

    Psyllidis, A.

    2015-01-01

    This paper presents a novel knowledge representation framework for smart city planning and management that enables the semantic integration of heterogeneous urban data from diverse sources. Currently, the combination of information across city agencies is cumbersome, as the increasingly available

  11. Ontology-based representation and analysis of host-Brucella interactions.

    Science.gov (United States)

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

  12. Pulmonary emphysema classification based on an improved texton learning model by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2013-03-01

    In this paper, we present a texture classification method based on texton learned via sparse representation (SR) with new feature histogram maps in the classification of emphysema. First, an overcomplete dictionary of textons is learned via KSVD learning on every class image patches in the training dataset. In this stage, high-pass filter is introduced to exclude patches in smooth area to speed up the dictionary learning process. Second, 3D joint-SR coefficients and intensity histograms of the test images are used for characterizing regions of interest (ROIs) instead of conventional feature histograms constructed from SR coefficients of the test images over the dictionary. Classification is then performed using a classifier with distance as a histogram dissimilarity measure. Four hundreds and seventy annotated ROIs extracted from 14 test subjects, including 6 paraseptal emphysema (PSE) subjects, 5 centrilobular emphysema (CLE) subjects and 3 panlobular emphysema (PLE) subjects, are used to evaluate the effectiveness and robustness of the proposed method. The proposed method is tested on 167 PSE, 240 CLE and 63 PLE ROIs consisting of mild, moderate and severe pulmonary emphysema. The accuracy of the proposed system is around 74%, 88% and 89% for PSE, CLE and PLE, respectively.

  13. Information dimension analysis of bacterial essential and nonessential genes based on chaos game representation

    International Nuclear Information System (INIS)

    Zhou, Qian; Yu, Yong-ming

    2014-01-01

    Essential genes are indispensable for the survival of an organism. Investigating features associated with gene essentiality is fundamental to the prediction and identification of the essential genes. Selecting features associated with gene essentiality is fundamental to predict essential genes with computational techniques. We use fractal theory to make comparative analysis of essential and nonessential genes in bacteria. The information dimensions of essential genes and nonessential genes available in the DEG database for 27 bacteria are calculated based on their gene chaos game representations (CGRs). It is found that weak positive linear correlation exists between information dimension and gene length. Moreover, for genes of similar length, the average information dimension of essential genes is larger than that of nonessential genes. This indicates that essential genes show less regularity and higher complexity than nonessential genes. Our results show that for bacterium with a similar number of essential genes and nonessential genes, the CGR information dimension is helpful for the classification of essential genes and nonessential genes. Therefore, the gene CGR information dimension is very probably a useful gene feature for a genetic algorithm predicting essential genes. (paper)

  14. Foundations for Reasoning in Cognition-Based Computational Representations of Human Decision Making; TOPICAL

    International Nuclear Information System (INIS)

    SENGLAUB, MICHAEL E.; HARRIS, DAVID L.; RAYBOURN, ELAINE M.

    2001-01-01

    In exploring the question of how humans reason in ambiguous situations or in the absence of complete information, we stumbled onto a body of knowledge that addresses issues beyond the original scope of our effort. We have begun to understand the importance that philosophy, in particular the work of C. S. Peirce, plays in developing models of human cognition and of information theory in general. We have a foundation that can serve as a basis for further studies in cognition and decision making. Peircean philosophy provides a foundation for understanding human reasoning and capturing behavioral characteristics of decision makers due to cultural, physiological, and psychological effects. The present paper describes this philosophical approach to understanding the underpinnings of human reasoning. We present the work of C. S. Peirce, and define sets of fundamental reasoning behavior that would be captured in the mathematical constructs of these newer technologies and would be able to interact in an agent type framework. Further, we propose the adoption of a hybrid reasoning model based on his work for future computational representations or emulations of human cognition

  15. 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

  16. Local curvature entropy-based 3D terrain representation using a comprehensive Quadtree

    Science.gov (United States)

    Chen, Qiyu; Liu, Gang; Ma, Xiaogang; Mariethoz, Gregoire; He, Zhenwen; Tian, Yiping; Weng, Zhengping

    2018-05-01

    Large scale 3D digital terrain modeling is a crucial part of many real-time applications in geoinformatics. In recent years, the improved speed and precision in spatial data collection make the original terrain data more complex and bigger, which poses challenges for data management, visualization and analysis. In this work, we presented an effective and comprehensive 3D terrain representation based on local curvature entropy and a dynamic Quadtree. The Level-of-detail (LOD) models of significant terrain features were employed to generate hierarchical terrain surfaces. In order to reduce the radical changes of grid density between adjacent LODs, local entropy of terrain curvature was regarded as a measure of subdividing terrain grid cells. Then, an efficient approach was presented to eliminate the cracks among the different LODs by directly updating the Quadtree due to an edge-based structure proposed in this work. Furthermore, we utilized a threshold of local entropy stored in each parent node of this Quadtree to flexibly control the depth of the Quadtree and dynamically schedule large-scale LOD terrain. Several experiments were implemented to test the performance of the proposed method. The results demonstrate that our method can be applied to construct LOD 3D terrain models with good performance in terms of computational cost and the maintenance of terrain features. Our method has already been deployed in a geographic information system (GIS) for practical uses, and it is able to support the real-time dynamic scheduling of large scale terrain models more easily and efficiently.

  17. Ability-Based View in Action: A Software Corporation Study

    Directory of Open Access Journals (Sweden)

    Farley Simon Nobre

    2014-04-01

    Full Text Available This research investigates antecedents, developments and consequences of dynamic capabilities in an organization. It contributes by searching theoretical and empirical answers to the questions: (a What are the antecedents which can provide an organization with dynamic and ordinary capabilities?; (b How do these antecedents contribute to create capabilities in an organization?; (c How do they affect an organization’s competitive advantage?; (d Can we assess and measure the antecedents and consequences to an organization? From a first (theoretical perspective, this paper searches answers to the first, second and third questions by reviewing concepts of an ability-based view of organizations that involves the abilities of cognition, intelligence, autonomy, learning and knowledge management, and which contributes to explain the dynamic behavior of the firm in the pursuit of competitive advantage. From a second (empirical perspective, this paper reinforces and delivers findings to the second, third and fourth questions by presenting a case study that evidences the ability-based view in action in a software corporation, where it contributes by investigating: (a the development of organizational capabilities; (b the effects of the new capabilities on the organization; and (c the assessment and measurement of the abilities and consequences.

  18. Action First--Understanding Follows: An Expansion of Skills-Based Training Using Action Method.

    Science.gov (United States)

    Martin, Colin

    1988-01-01

    This paper discusses the concept of training trainers in the skills they need to perform competently as trainers and how they follow their skills mastery with discussion on their new theoretical insight. Moreno's action method (psychodrama, sociodrama, sociometry, and role training) is the model used. (JOW)

  19. 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

  20. Visual tracking based on the sparse representation of the PCA subspace

    Science.gov (United States)

    Chen, Dian-bing; Zhu, Ming; Wang, Hui-li

    2017-09-01

    We construct a collaborative model of the sparse representation and the subspace representation. First, we represent the tracking target in the principle component analysis (PCA) subspace, and then we employ an L 1 regularization to restrict the sparsity of the residual term, an L 2 regularization term to restrict the sparsity of the representation coefficients, and an L 2 norm to restrict the distance between the reconstruction and the target. Then we implement the algorithm in the particle filter framework. Furthermore, an iterative method is presented to get the global minimum of the residual and the coefficients. Finally, an alternative template update scheme is adopted to avoid the tracking drift which is caused by the inaccurate update. In the experiment, we test the algorithm on 9 sequences, and compare the results with 5 state-of-art methods. According to the results, we can conclude that our algorithm is more robust than the other methods.

  1. The construction of semantic memory: grammar based representations learned from relational episodic information

    Directory of Open Access Journals (Sweden)

    Francesco P Battaglia

    2011-08-01

    Full Text Available After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation, collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside-outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of ``sleep replay'' of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata.

  2. Multi-scale Gaussian representation and outline-learning based cell image segmentation

    Science.gov (United States)

    2013-01-01

    Background High-throughput genome-wide screening to study gene-specific functions, e.g. for drug discovery, demands fast automated image analysis methods to assist in unraveling the full potential of such studies. Image segmentation is typically at the forefront of such analysis as the performance of the subsequent steps, for example, cell classification, cell tracking etc., often relies on the results of segmentation. Methods We present a cell cytoplasm segmentation framework which first separates cell cytoplasm from image background using novel approach of image enhancement and coefficient of variation of multi-scale Gaussian scale-space representation. A novel outline-learning based classification method is developed using regularized logistic regression with embedded feature selection which classifies image pixels as outline/non-outline to give cytoplasm outlines. Refinement of the detected outlines to separate cells from each other is performed in a post-processing step where the nuclei segmentation is used as contextual information. Results and conclusions We evaluate the proposed segmentation methodology using two challenging test cases, presenting images with completely different characteristics, with cells of varying size, shape, texture and degrees of overlap. The feature selection and classification framework for outline detection produces very simple sparse models which use only a small subset of the large, generic feature set, that is, only 7 and 5 features for the two cases. Quantitative comparison of the results for the two test cases against state-of-the-art methods show that our methodology outperforms them with an increase of 4-9% in segmentation accuracy with maximum accuracy of 93%. Finally, the results obtained for diverse datasets demonstrate that our framework not only produces accurate segmentation but also generalizes well to different segmentation tasks. PMID:24267488

  3. The Construction of Semantic Memory: Grammar-Based Representations Learned from Relational Episodic Information

    Science.gov (United States)

    Battaglia, Francesco P.; Pennartz, Cyriel M. A.

    2011-01-01

    After acquisition, memories underlie a process of consolidation, making them more resistant to interference and brain injury. Memory consolidation involves systems-level interactions, most importantly between the hippocampus and associated structures, which takes part in the initial encoding of memory, and the neocortex, which supports long-term storage. This dichotomy parallels the contrast between episodic memory (tied to the hippocampal formation), collecting an autobiographical stream of experiences, and semantic memory, a repertoire of facts and statistical regularities about the world, involving the neocortex at large. Experimental evidence points to a gradual transformation of memories, following encoding, from an episodic to a semantic character. This may require an exchange of information between different memory modules during inactive periods. We propose a theory for such interactions and for the formation of semantic memory, in which episodic memory is encoded as relational data. Semantic memory is modeled as a modified stochastic grammar, which learns to parse episodic configurations expressed as an association matrix. The grammar produces tree-like representations of episodes, describing the relationships between its main constituents at multiple levels of categorization, based on its current knowledge of world regularities. These regularities are learned by the grammar from episodic memory information, through an expectation-maximization procedure, analogous to the inside–outside algorithm for stochastic context-free grammars. We propose that a Monte-Carlo sampling version of this algorithm can be mapped on the dynamics of “sleep replay” of previously acquired information in the hippocampus and neocortex. We propose that the model can reproduce several properties of semantic memory such as decontextualization, top-down processing, and creation of schemata. PMID:21887143

  4. Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

    Science.gov (United States)

    Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

    2018-05-01

    Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

  5. 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.

  6. Dialectical thinking and fairness-based perspectives of affirmative action.

    Science.gov (United States)

    Hideg, Ivona; Ferris, D Lance

    2017-05-01

    Affirmative action (AA) policies are among the most effective means for enhancing diversity and equality in the workplace, yet are also often viewed with scorn by the wider public. Fairness-based explanations for this scorn suggest AA policies provide preferential treatment to minorities, violating procedural fairness principles of consistent treatment. In other words, to promote equality in the workplace, effective AA policies promote inequality when selecting employees, and the broader public perceives this to be procedurally unfair. Given this inconsistency underlies negative reactions to AA policies, we argue that better preparing individuals to deal with inconsistencies can mitigate negative reactions to AA policies. Integrating theories from the fairness and cognitive styles literature, we demonstrate across 4 studies how dialectical thinking-a cognitive style associated with accepting inconsistencies in one's environment-increases support for AA policies via procedural fairness perceptions. Specifically, we found support for our propositions across a variety of AA policy types (i.e., strong and weak preference policies) and when conceptualizing dialectical thinking either as an individual difference or as a state that can be primed-including being primed by the framing of the AA policy itself. We discuss theoretical contributions and insights for policy-making at government and organizational levels. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  7. 3D base: a geometrical data base system for the analysis and visualisation of 3D-shapes obtained from parallel serial sections including three different geometrical representations

    NARCIS (Netherlands)

    Verbeek, F. J.; de Groot, M. M.; Huijsmans, D. P.; Lamers, W. H.; Young, I. T.

    1993-01-01

    In this paper we discuss a geometrical data base that includes three different geometrical representations of one and the same reconstructed 3D shape: the contour-pile, the voxel enumeration, and the triangulation of a surface. The data base is tailored for 3D shapes obtained from plan-parallel

  8. 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.

  9. 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...

  10. MAP-Motivated Carrier Synchronization of GMSK Based on the Laurent AMP Representation

    Science.gov (United States)

    Simon, M. K.

    1998-01-01

    Using the MAP estimation approach to carrier synchronization of digital modulations containing ISI together with a two pulse stream AMP representation of GMSK, it is possible to obtain an optimum closed loop configuration in the same manner as has been previously proposed for other conventional modulations with ISI.

  11. Embodied Numerosity: Implicit Hand-Based Representations Influence Symbolic Number Processing across Cultures

    Science.gov (United States)

    Domahs, Frank; Moeller, Korbinian; Huber, Stefan; Willmes, Klaus; Nuerk, Hans-Christoph

    2010-01-01

    In recent years, a strong functional relationship between finger counting and number processing has been suggested. Developmental studies have shown specific effects of the structure of the individual finger counting system on arithmetic abilities. Moreover, the orientation of the mental quantity representation ("number line") seems to be…

  12. Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations

    NARCIS (Netherlands)

    van Noord, Rik; Bos, Johannes

    2017-01-01

    We evaluate the character-level translation method for neural semantic parsing on a large corpus of sentences annotated with Abstract Meaning Representations (AMRs). Using a sequence-to-sequence model, and some trivial preprocessing and postprocessing of AMRs, we obtain a baseline accuracy of 53.1

  13. Mis/Representations in School-Based Digital Media Production: An Ethnographic Exploration with Muslim Girls

    Science.gov (United States)

    Dahya, Negin; Jenson, Jennifer

    2015-01-01

    In this article, the authors discuss findings from a digital media production club with racialized girls in a low-income school in Toronto, Ontario. Specifically, the authors consider how student-produced media is impacted by ongoing postcolonial structures relating to power and representation in the school and in the media production work of…

  14. Getting the picture: The role of external representations in simulation-based inquiry learning.

    NARCIS (Netherlands)

    Kolloffel, Bas Jan

    2008-01-01

    Three studies were performed to examine the effects of formats of ‘pre-fabricated’ and learner-generated representations on learning outcomes of pupils learning combinatorics and probability theory. In Study I, the effects of different formats on learning outcomes were examined. Learners in five

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

    Directory of Open Access Journals (Sweden)

    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.

  16. Developing Young Adults' Representational Competence through Infographic-Based Science News Reporting

    Science.gov (United States)

    Gebre, Engida H.; Polman, Joseph L.

    2016-01-01

    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…

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

    Science.gov (United States)

    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.

  18. Formal TCA cycle description based on elementary actions

    Indian Academy of Sciences (India)

    Prakash

    2006-12-20

    Dec 20, 2006 ... Applied to the description of the tricarboxylic acid cycle (TCA), we show that. BioΨ allows ... BAs, biological activities; BEAs, basic elements of action; BFs, biological ..... the mitochondria, such as respiratory chain and fatty acid.

  19. Episodic Reasoning for Vision-Based Human Action Recognition

    Directory of Open Access Journals (Sweden)

    Maria J. Santofimia

    2014-01-01

    Full Text Available Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning.

  20. Heart rate variability analysis based on time–frequency representation and entropies in hypertrophic cardiomyopathy patients

    International Nuclear Information System (INIS)

    Clariá, F; Vallverdú, M; Caminal, P; Baranowski, R; Chojnowska, L

    2008-01-01

    In hypertrophic cardiomyopathy (HCM) patients there is an increased risk of premature death, which can occur with little or no warning. Furthermore, classification for sudden cardiac death on patients with HCM is very difficult. The aim of our study was to improve the prognostic value of heart rate variability (HRV) in HCM patients, giving insight into changes of the autonomic nervous system. In this way, the suitability of linear and nonlinear measures was studied to assess the HRV. These measures were based on time–frequency representation (TFR) and on Shannon and Rényi entropies, and compared with traditional HRV measures. Holter recordings of 64 patients with HCM and 55 healthy subjects were analyzed. The HCM patients consisted of two groups: 13 high risk patients, after aborted sudden cardiac death (SCD); 51 low risk patients, without SCD. Five-hour RR signals, corresponding to the sleep period of the subjects, were considered for the analysis as a comparable standard situation. These RR signals were filtered in the three frequency bands: very low frequency band (VLF, 0–0.04 Hz), low frequency band (LF, 0.04–0.15 Hz) and high frequency band (HF, 0.15–0.45 Hz). TFR variables based on instantaneous frequency and energy functions were able to classify HCM patients and healthy subjects (control group). Results revealed that measures obtained from TFR analysis of the HRV better classified the groups of subjects than traditional HRV parameters. However, results showed that nonlinear measures improved group classification. It was observed that entropies calculated in the HF band showed the highest statistically significant levels comparing the HCM group and the control group, p-value < 0.0005. The values of entropy measures calculated in the HCM group presented lower values, indicating a decreasing of complexity, than those calculated from the control group. Moreover, similar behavior was observed comparing high and low risk of premature death, the values of

  1. 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.

  2. Concise and Accessible Representations for Multidimensional Datasets: Introducing a Framework Based on the nD-EVM and Kohonen Networks

    Directory of Open Access Journals (Sweden)

    Ricardo Pérez-Aguila

    2015-01-01

    Full Text Available A new framework intended for representing and segmenting multidimensional datasets resulting in low spatial complexity requirements and with appropriate access to their contained information is described. Two steps are going to be taken in account. The first step is to specify (n-1D hypervoxelizations, n≥2, as Orthogonal Polytopes whose nth dimension corresponds to color intensity. Then, the nD representation is concisely expressed via the Extreme Vertices Model in the n-Dimensional Space (nD-EVM. Some examples are presented, which, under our methodology, have storing requirements minor than those demanded by their original hypervoxelizations. In the second step, 1-Dimensional Kohonen Networks (1D-KNs are applied in order to segment datasets taking in account their geometrical and topological properties providing a non-supervised way to compact even more the proposed n-Dimensional representations. The application of our framework shares compression ratios, for our set of study cases, in the range 5.6496 to 32.4311. Summarizing, the contribution combines the power of the nD-EVM and 1D-KNs by producing very concise datasets’ representations. We argue that the new representations also provide appropriate segmentations by introducing some error functions such that our 1D-KNs classifications are compared against classifications based only in color intensities. Along the work, main properties and algorithms behind the nD-EVM are introduced for the purpose of interrogating the final representations in such a way that it efficiently obtains useful geometrical and topological information.

  3. Neural bases of selective attention in action video game players

    OpenAIRE

    Bavelier, D; Achtman, RL; Mani, M; Föcker, J

    2011-01-01

    Over the past few years, the very act of playing action video games has been shown to enhance several different aspects of visual selective attention. Yet little is known about the neural mechanisms that mediate such attentional benefits. A review of the aspects of attention enhanced in action game players suggests there are changes in the mechanisms that control attention allocation and its efficiency (Hubert-Wallander et al., 2010). The present study used brain imaging to test this hypothes...

  4. Regional Densification of a Global VTEC Model Based on B-Spline Representations

    Science.gov (United States)

    Erdogan, Eren; Schmidt, Michael; Dettmering, Denise; Goss, Andreas; Seitz, Florian; Börger, Klaus; Brandert, Sylvia; Görres, Barbara; Kersten, Wilhelm F.; Bothmer, Volker; Hinrichs, Johannes; Mrotzek, Niclas

    2017-04-01

    The project OPTIMAP is a joint initiative of the Bundeswehr GeoInformation Centre (BGIC), the German Space Situational Awareness Centre (GSSAC), the German Geodetic Research Institute of the Technical University Munich (DGFI-TUM) and the Institute for Astrophysics at the University of Göttingen (IAG). The main goal of the project is the development of an operational tool for ionospheric mapping and prediction (OPTIMAP). Two key features of the project are the combination of different satellite observation techniques (GNSS, satellite altimetry, radio occultations and DORIS) and the regional densification as a remedy against problems encountered with the inhomogeneous data distribution. Since the data from space-geoscientific mission which can be used for modeling ionospheric parameters, such as the Vertical Total Electron Content (VTEC) or the electron density, are distributed rather unevenly over the globe at different altitudes, appropriate modeling approaches have to be developed to handle this inhomogeneity. Our approach is based on a two-level strategy. To be more specific, in the first level we compute a global VTEC model with a moderate regional and spectral resolution which will be complemented in the second level by a regional model in a densification area. The latter is a region characterized by a dense data distribution to obtain a high spatial and spectral resolution VTEC product. Additionally, the global representation means a background model for the regional one to avoid edge effects at the boundaries of the densification area. The presented approach based on a global and a regional model part, i.e. the consideration of a regional densification is called the Two-Level VTEC Model (TLVM). The global VTEC model part is based on a series expansion in terms of polynomial B-Splines in latitude direction and trigonometric B-Splines in longitude direction. The additional regional model part is set up by a series expansion in terms of polynomial B-splines for

  5. 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...

  6. Wigner functions for noncommutative quantum mechanics: A group representation based construction

    Energy Technology Data Exchange (ETDEWEB)

    Chowdhury, S. Hasibul Hassan, E-mail: shhchowdhury@gmail.com [Chern Institute of Mathematics, Nankai University, Tianjin 300071 (China); Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada); Ali, S. Twareque, E-mail: twareque.ali@concordia.ca [Department of Mathematics and Statistics, Concordia University, Montréal, Québec H3G 1M8 (Canada)

    2015-12-15

    This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group G{sub NC}, which is the three fold central extension of the Abelian group of ℝ{sup 4}. These representations have been exhaustively studied in earlier papers. The group G{sub NC} is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only.

  7. Human action perspectives based on individual plant examination results

    International Nuclear Information System (INIS)

    Forester, J.; Thompson, C.; Drouin, M.; Lois, E.

    1996-01-01

    This paper provides perspectives on human actions gained from reviewing 76 individual plant examination (IPE) submittals. Human actions found to be important in boiling water reactors (BWRs) and in pressurized water reactors (PWRs) are presented and the events most frequently found important are discussed. Since there are numerous factors that can influence the quantification of human error probabilities (HEPs) and introduce significant variability in the resulting HEPs (which in turn can influence which events are found to be important), the variability in HEPs for similar events across IPEs is examined to assess the extent to which variability in results is due to real versus artifactual differences. Finally, similarities and differences in human action observations across BWRs and PWRs are examined

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

    Directory of Open Access Journals (Sweden)

    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.

  9. Integral representations of solutions of the wave equation based on relativistic wavelets

    International Nuclear Information System (INIS)

    Perel, Maria; Gorodnitskiy, Evgeny

    2012-01-01

    A representation of solutions of the wave equation with two spatial coordinates in terms of localized elementary ones is presented. Elementary solutions are constructed from four solutions with the help of transformations of the affine Poincaré group, i.e. with the help of translations, dilations in space and time and Lorentz transformations. The representation can be interpreted in terms of the initial-boundary value problem for the wave equation in a half-plane. It gives the solution as an integral representation of two types of solutions: propagating localized solutions running away from the boundary under different angles and packet-like surface waves running along the boundary and exponentially decreasing away from the boundary. Properties of elementary solutions are discussed. A numerical investigation of coefficients of the decomposition is carried out. An example of the decomposition of the field created by sources moving along a line with different speeds is considered, and the dependence of coefficients on speeds of sources is discussed. (paper)

  10. 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?...

  11. 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.

  12. Evidence for similar patterns of neural activity elicited by picture- and word-based representations of natural scenes.

    Science.gov (United States)

    Kumar, Manoj; Federmeier, Kara D; Fei-Fei, Li; Beck, Diane M

    2017-07-15

    A long-standing core question in cognitive science is whether different modalities and representation types (pictures, words, sounds, etc.) access a common store of semantic information. Although different input types have been shown to activate a shared network of brain regions, this does not necessitate that there is a common representation, as the neurons in these regions could still differentially process the different modalities. However, multi-voxel pattern analysis can be used to assess whether, e.g., pictures and words evoke a similar pattern of activity, such that the patterns that separate categories in one modality transfer to the other. Prior work using this method has found support for a common code, but has two limitations: they have either only examined disparate categories (e.g. animals vs. tools) that are known to activate different brain regions, raising the possibility that the pattern separation and inferred similarity reflects only large scale differences between the categories or they have been limited to individual object representations. By using natural scene categories, we not only extend the current literature on cross-modal representations beyond objects, but also, because natural scene categories activate a common set of brain regions, we identify a more fine-grained (i.e. higher spatial resolution) common representation. Specifically, we studied picture- and word-based representations of natural scene stimuli from four different categories: beaches, cities, highways, and mountains. Participants passively viewed blocks of either phrases (e.g. "sandy beach") describing scenes or photographs from those same scene categories. To determine whether the phrases and pictures evoke a common code, we asked whether a classifier trained on one stimulus type (e.g. phrase stimuli) would transfer (i.e. cross-decode) to the other stimulus type (e.g. picture stimuli). The analysis revealed cross-decoding in the occipitotemporal, posterior parietal and

  13. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    , and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...

  14. 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.

  15. Neural bases of selective attention in action video game players.

    Science.gov (United States)

    Bavelier, D; Achtman, R L; Mani, M; Föcker, J

    2012-05-15

    Over the past few years, the very act of playing action video games has been shown to enhance several different aspects of visual selective attention, yet little is known about the neural mechanisms that mediate such attentional benefits. A review of the aspects of attention enhanced in action game players suggests there are changes in the mechanisms that control attention allocation and its efficiency (Hubert-Wallander, Green, & Bavelier, 2010). The present study used brain imaging to test this hypothesis by comparing attentional network recruitment and distractor processing in action gamers versus non-gamers as attentional demands increased. Moving distractors were found to elicit lesser activation of the visual motion-sensitive area (MT/MST) in gamers as compared to non-gamers, suggestive of a better early filtering of irrelevant information in gamers. As expected, a fronto-parietal network of areas showed greater recruitment as attentional demands increased in non-gamers. In contrast, gamers barely engaged this network as attentional demands increased. This reduced activity in the fronto-parietal network that is hypothesized to control the flexible allocation of top-down attention is compatible with the proposal that action game players may allocate attentional resources more automatically, possibly allowing more efficient early filtering of irrelevant information. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Scenarios, personas and user stories from design ethnography: Evidence-based design representations of communicable disease investigations

    Science.gov (United States)

    Turner, Anne M; Reeder, Blaine; Ramey, Judith

    2014-01-01

    Purpose Despite years of effort and millions of dollars spent to create a unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of User Center Design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to communicable disease (CD) monitoring and control at a local health department, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. Methods We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health department communicable disease workflow. Informed by principles of design ethnography and user-centered design (UCD) we created persona, scenarios and user stories to accurately represent the user to system designers. Results We sought to convey to designers the key findings from ethnographic studies: 1) that public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed 2) health department efforts are focused on CD investigation and response rather than reporting and 3) current CD information systems must conform to PH workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Conclusions Through application of user centered design principles, we were able to create design representations that illustrate complex public health communicable

  17. Scenarios, personas and user stories: user-centered evidence-based design representations of communicable disease investigations.

    Science.gov (United States)

    Turner, Anne M; Reeder, Blaine; Ramey, Judith

    2013-08-01

    Despite years of effort and millions of dollars spent to create unified electronic communicable disease reporting systems, the goal remains elusive. A major barrier has been a lack of understanding by system designers of communicable disease (CD) work and the public health workers who perform this work. This study reports on the application of user-centered design representations, traditionally used for improving interface design, to translate the complex CD work identified through ethnographic studies to guide designers and developers of CD systems. The purpose of this work is to: (1) better understand public health practitioners and their information workflow with respect to CD monitoring and control at a local health agency, and (2) to develop evidence-based design representations that model this CD work to inform the design of future disease surveillance systems. We performed extensive onsite semi-structured interviews, targeted work shadowing and a focus group to characterize local health agency CD workflow. Informed by principles of design ethnography and user-centered design we created persona, scenarios and user stories to accurately represent the user to system designers. We sought to convey to designers the key findings from ethnographic studies: (1) public health CD work is mobile and episodic, in contrast to current CD reporting systems, which are stationary and fixed, (2) health agency efforts are focused on CD investigation and response rather than reporting and (3) current CD information systems must conform to public health workflow to ensure their usefulness. In an effort to illustrate our findings to designers, we developed three contemporary design-support representations: persona, scenario, and user story. Through application of user-centered design principles, we were able to create design representations that illustrate complex public health communicable disease workflow and key user characteristics to inform the design of CD information

  18. Structural damage detection in wind turbine blades based on time series representations of dynamic responses

    Science.gov (United States)

    Hoell, Simon; Omenzetter, Piotr

    2015-03-01

    The development of large wind turbines that enable to harvest energy more efficiently is a consequence of the increasing demand for renewables in the world. To optimize the potential energy output, light and flexible wind turbine blades (WTBs) are designed. However, the higher flexibilities and lower buckling capacities adversely affect the long-term safety and reliability of WTBs, and thus the increased operation and maintenance costs reduce the expected revenue. Effective structural health monitoring techniques can help to counteract this by limiting inspection efforts and avoiding unplanned maintenance actions. Vibration-based methods deserve high attention due to the moderate instrumentation efforts and the applicability for in-service measurements. The present paper proposes the use of cross-correlations (CCs) of acceleration responses between sensors at different locations for structural damage detection in WTBs. CCs were in the past successfully applied for damage detection in numerical and experimental beam structures while utilizing only single lags between the signals. The present approach uses vectors of CC coefficients for multiple lags between measurements of two selected sensors taken from multiple possible combinations of sensors. To reduce the dimensionality of the damage sensitive feature (DSF) vectors, principal component analysis is performed. The optimal number of principal components (PCs) is chosen with respect to a statistical threshold. Finally, the detection phase uses the selected PCs of the healthy structure to calculate scores from a current DSF vector, where statistical hypothesis testing is performed for making a decision about the current structural state. The method is applied to laboratory experiments conducted on a small WTB with non-destructive damage scenarios.

  19. Adaptive structured dictionary learning for image fusion based on group-sparse-representation

    Science.gov (United States)

    Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

    2018-04-01

    Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

  20. Seismic detection method for small-scale discontinuities based on dictionary learning and sparse representation

    Science.gov (United States)

    Yu, Caixia; Zhao, Jingtao; Wang, Yanfei

    2017-02-01

    Studying small-scale geologic discontinuities, such as faults, cavities and fractures, plays a vital role in analyzing the inner conditions of reservoirs, as these geologic structures and elements can provide storage spaces and migration pathways for petroleum. However, these geologic discontinuities have weak energy and are easily contaminated with noises, and therefore effectively extracting them from seismic data becomes a challenging problem. In this paper, a method for detecting small-scale discontinuities using dictionary learning and sparse representation is proposed that can dig up high-resolution information by sparse coding. A K-SVD (K-means clustering via Singular Value Decomposition) sparse representation model that contains two stage of iteration procedure: sparse coding and dictionary updating, is suggested for mathematically expressing these seismic small-scale discontinuities. Generally, the orthogonal matching pursuit (OMP) algorithm is employed for sparse coding. However, the method can only update one dictionary atom at one time. In order to improve calculation efficiency, a regularized version of OMP algorithm is presented for simultaneously updating a number of atoms at one time. Two numerical experiments demonstrate the validity of the developed method for clarifying and enhancing small-scale discontinuities. The field example of carbonate reservoirs further demonstrates its effectiveness in revealing masked tiny faults and small-scale cavities.

  1. Spectrum recovery method based on sparse representation for segmented multi-Gaussian model

    Science.gov (United States)

    Teng, Yidan; Zhang, Ye; Ti, Chunli; Su, Nan

    2016-09-01

    Hyperspectral images can realize crackajack features discriminability for supplying diagnostic characteristics with high spectral resolution. However, various degradations may generate negative influence on the spectral information, including water absorption, bands-continuous noise. On the other hand, the huge data volume and strong redundancy among spectrums produced intense demand on compressing HSIs in spectral dimension, which also leads to the loss of spectral information. The reconstruction of spectral diagnostic characteristics has irreplaceable significance for the subsequent application of HSIs. This paper introduces a spectrum restoration method for HSIs making use of segmented multi-Gaussian model (SMGM) and sparse representation. A SMGM is established to indicating the unsymmetrical spectral absorption and reflection characteristics, meanwhile, its rationality and sparse property are discussed. With the application of compressed sensing (CS) theory, we implement sparse representation to the SMGM. Then, the degraded and compressed HSIs can be reconstructed utilizing the uninjured or key bands. Finally, we take low rank matrix recovery (LRMR) algorithm for post processing to restore the spatial details. The proposed method was tested on the spectral data captured on the ground with artificial water absorption condition and an AVIRIS-HSI data set. The experimental results in terms of qualitative and quantitative assessments demonstrate that the effectiveness on recovering the spectral information from both degradations and loss compression. The spectral diagnostic characteristics and the spatial geometry feature are well preserved.

  2. Social representations of adolescents on quality of life: structurally-based study

    Directory of Open Access Journals (Sweden)

    Ramon Missias Moreira

    2015-01-01

    Full Text Available This study sought to conduct a comparatively analysis and describe the contents of the structure of the social representations of adolescents on quality of life. It involves descriptive, quantitative research, with the benchmark of a structural approach to social representations. The informants included 316 adolescents from three public schools in Jequié in the State of Bahia. The Spontaneous Word-Choice Eliciting Technique using the key expression "Quality of Life" was used for data collection. The responses were processed using Evoc 2003 software, which generated the Four-House Chart. The results reveal the core nucleus of the terms: healthy eating; physical activity; money; and sex. In the 1st outer circle, the words absence of disease, condoms, liberty, marijuana, housing, work and living well are featured. In the 2nd outer circle, there appeared the words difficulty, family, peace and power, and the contrasting elements of well-being and soccer. The overall consensus is that adolescents associate quality of life with sports and other healthy behavior activities, and are influenced by the desires and curiosities of adolescence.

  3. Non-Markovian reduced dynamics based upon a hierarchical effective-mode representation

    Energy Technology Data Exchange (ETDEWEB)

    Burghardt, Irene [Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt (Germany); Martinazzo, Rocco [Dipartimento di Chimica, Universita degli Studi di Milano, v. Golgi 19, 20133 Milano (Italy); Hughes, Keith H. [School of Chemistry, Bangor University, Bangor, Gwynedd LL57 2UW (United Kingdom)

    2012-10-14

    A reduced dynamics representation is introduced which is tailored to a hierarchical, Mori-chain type representation of a bath of harmonic oscillators which are linearly coupled to a subsystem. We consider a spin-boson system where a single effective mode is constructed so as to absorb all system-environment interactions, while the residual bath modes are coupled bilinearly to the primary mode and among each other. Using a cumulant expansion of the memory kernel, correlation functions for the primary mode are obtained, which can be suitably approximated by truncated chains representing the primary-residual mode interactions. A series of reduced-dimensional bath correlation functions is thus obtained, which can be expressed as Fourier-Laplace transforms of spectral densities that are given in truncated continued-fraction form. For a master equation which is second order in the system-bath coupling, the memory kernel is re-expressed in terms of local-in-time equations involving auxiliary densities and auxiliary operators.

  4. Analysis Sparse Representation for Nonnegative Signals Based on Determinant Measure by DC Programming

    Directory of Open Access Journals (Sweden)

    Yujie Li

    2018-01-01

    Full Text Available Analysis sparse representation has recently emerged as an alternative approach to the synthesis sparse model. Most existing algorithms typically employ the l0-norm, which is generally NP-hard. Other existing algorithms employ the l1-norm to relax the l0-norm, which sometimes cannot promote adequate sparsity. Most of these existing algorithms focus on general signals and are not suitable for nonnegative signals. However, many signals are necessarily nonnegative such as spectral data. In this paper, we present a novel and efficient analysis dictionary learning algorithm for nonnegative signals with the determinant-type sparsity measure which is convex and differentiable. The analysis sparse representation can be cast in three subproblems, sparse coding, dictionary update, and signal update, because the determinant-type sparsity measure would result in a complex nonconvex optimization problem, which cannot be easily solved by standard convex optimization methods. Therefore, in the proposed algorithms, we use a difference of convex (DC programming scheme for solving the nonconvex problem. According to our theoretical analysis and simulation study, the main advantage of the proposed algorithm is its greater dictionary learning efficiency, particularly compared with state-of-the-art algorithms. In addition, our proposed algorithm performs well in image denoising.

  5. Virtual terrain: a security-based representation of a computer network

    Science.gov (United States)

    Holsopple, Jared; Yang, Shanchieh; Argauer, Brian

    2008-03-01

    Much research has been put forth towards detection, correlating, and prediction of cyber attacks in recent years. As this set of research progresses, there is an increasing need for contextual information of a computer network to provide an accurate situational assessment. Typical approaches adopt contextual information as needed; yet such ad hoc effort may lead to unnecessary or even conflicting features. The concept of virtual terrain is, therefore, developed and investigated in this work. Virtual terrain is a common representation of crucial information about network vulnerabilities, accessibilities, and criticalities. A virtual terrain model encompasses operating systems, firewall rules, running services, missions, user accounts, and network connectivity. It is defined as connected graphs with arc attributes defining dynamic relationships among vertices modeling network entities, such as services, users, and machines. The virtual terrain representation is designed to allow feasible development and maintenance of the model, as well as efficacy in terms of the use of the model. This paper will describe the considerations in developing the virtual terrain schema, exemplary virtual terrain models, and algorithms utilizing the virtual terrain model for situation and threat assessment.

  6. Fall Detection for Elderly from Partially Observed Depth-Map Video Sequences Based on View-Invariant Human Activity Representation

    Directory of Open Access Journals (Sweden)

    Rami Alazrai

    2017-03-01

    Full Text Available This paper presents a new approach for fall detection from partially-observed depth-map video sequences. The proposed approach utilizes the 3D skeletal joint positions obtained from the Microsoft Kinect sensor to build a view-invariant descriptor for human activity representation, called the motion-pose geometric descriptor (MPGD. Furthermore, we have developed a histogram-based representation (HBR based on the MPGD to construct a length-independent representation of the observed video subsequences. Using the constructed HBR, we formulate the fall detection problem as a posterior-maximization problem in which the posteriori probability for each observed video subsequence is estimated using a multi-class SVM (support vector machine classifier. Then, we combine the computed posteriori probabilities from all of the observed subsequences to obtain an overall class posteriori probability of the entire partially-observed depth-map video sequence. To evaluate the performance of the proposed approach, we have utilized the Kinect sensor to record a dataset of depth-map video sequences that simulates four fall-related activities of elderly people, including: walking, sitting, falling form standing and falling from sitting. Then, using the collected dataset, we have developed three evaluation scenarios based on the number of unobserved video subsequences in the testing videos, including: fully-observed video sequence scenario, single unobserved video subsequence of random lengths scenarios and two unobserved video subsequences of random lengths scenarios. Experimental results show that the proposed approach achieved an average recognition accuracy of 93 . 6 % , 77 . 6 % and 65 . 1 % , in recognizing the activities during the first, second and third evaluation scenario, respectively. These results demonstrate the feasibility of the proposed approach to detect falls from partially-observed videos.

  7. Improving product development practice: An action-research based approach

    DEFF Research Database (Denmark)

    Harmsen, Hanne

    In studies of new product development it has often been concluded that to a large extent new product suc-cess is tunder the influence of companies and long lists of direct norma-tive guide-lines have been formulated. Nevertheless descriptive studi that deve-lopment practice is still far from...... studies both purely descriptive and studies identifying success and failure factors, but almost no studies of how companies actually undertake improve-ments, which problems they encounter,, and how/whether they overcome these problems. Action research is proposed as a suitable method for studying...

  8. Mechanism of action of mRNA-based vaccines.

    Science.gov (United States)

    Iavarone, Carlo; O'hagan, Derek T; Yu, Dong; Delahaye, Nicolas F; Ulmer, Jeffrey B

    2017-09-01

    The present review summarizes the growing body of work defining the mechanisms of action of this exciting new vaccine technology that should allow rational approaches in the design of next generation mRNA vaccines. Areas covered: Bio-distribution of mRNA, localization of antigen production, role of the innate immunity, priming of the adaptive immune response, route of administration and effects of mRNA delivery systems. Expert commentary: In the last few years, the development of RNA vaccines had a fast growth, the rising number of proof will enable rational approaches to improving the effectiveness and safety of this modern class of medicine.

  9. 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…

  10. Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets

    Science.gov (United States)

    Wu, Yue; Shang, Pengjian; Li, Yilong

    2018-03-01

    A modified multiscale sample entropy measure based on symbolic representation and similarity (MSEBSS) is proposed in this paper to research the complexity of stock markets. The modified algorithm reduces the probability of inducing undefined entropies and is confirmed to be robust to strong noise. Considering the validity and accuracy, MSEBSS is more reliable than Multiscale entropy (MSE) for time series mingled with much noise like financial time series. We apply MSEBSS to financial markets and results show American stock markets have the lowest complexity compared with European and Asian markets. There are exceptions to the regularity that stock markets show a decreasing complexity over the time scale, indicating a periodicity at certain scales. Based on MSEBSS, we introduce the modified multiscale cross-sample entropy measure based on symbolic representation and similarity (MCSEBSS) to consider the degree of the asynchrony between distinct time series. Stock markets from the same area have higher synchrony than those from different areas. And for stock markets having relative high synchrony, the entropy values will decrease with the increasing scale factor. While for stock markets having high asynchrony, the entropy values will not decrease with the increasing scale factor sometimes they tend to increase. So both MSEBSS and MCSEBSS are able to distinguish stock markets of different areas, and they are more helpful if used together for studying other features of financial time series.

  11. Perception of oyster-based products by French consumers. The effect of processing and role of social representations.

    Science.gov (United States)

    Debucquet, Gervaise; Cornet, Josiane; Adam, Isabelle; Cardinal, Mireille

    2012-12-01

    The search for new markets in the seafood sector, associated with the question of the continuity of raw oyster consumption over generations can be an opportunity for processors to extend their ranges with oyster-based products. The twofold aim of this study was to evaluate the impact of processing and social representation on perception of oyster-based products by French consumers and to identify the best means of development in order to avoid possible failure in the market. Five products with different degrees of processing (cooked oysters in a half-shell, hot preparation for toast, potted oyster, oyster butter and oyster-based soup) were presented within focus groups and consumer tests, at home and in canteens with the staff of several companies in order to reach consumers with different ages and professional activities. The results showed that social representation had a strong impact and that behaviours were contrasted according to the initial profile of the consumer (traditional raw oyster consumers or non-consumers) and their age distribution (younger and older people). The degree of processing has to be adapted to each segment. It is suggested to develop early exposure to influence the food choices and preferences of the youngest consumers on a long-term basis. Copyright © 2012 Elsevier Ltd. All rights reserved.

  12. Memetics of representation

    Directory of Open Access Journals (Sweden)

    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.

  13. Dynamics of random Boolean networks under fully asynchronous stochastic update based on linear representation.

    Directory of Open Access Journals (Sweden)

    Chao Luo

    Full Text Available A novel algebraic approach is proposed to study dynamics of asynchronous random Boolean networks where a random number of nodes can be updated at each time step (ARBNs. In this article, the logical equations of ARBNs are converted into the discrete-time linear representation and dynamical behaviors of systems are investigated. We provide a general formula of network transition matrices of ARBNs as well as a necessary and sufficient algebraic criterion to determine whether a group of given states compose an attractor of length[Formula: see text] in ARBNs. Consequently, algorithms are achieved to find all of the attractors and basins in ARBNs. Examples are showed to demonstrate the feasibility of the proposed scheme.

  14. Adaptive compressive ghost imaging based on wavelet trees and sparse representation.

    Science.gov (United States)

    Yu, Wen-Kai; Li, Ming-Fei; Yao, Xu-Ri; Liu, Xue-Feng; Wu, Ling-An; Zhai, Guang-Jie

    2014-03-24

    Compressed sensing is a theory which can reconstruct an image almost perfectly with only a few measurements by finding its sparsest representation. However, the computation time consumed for large images may be a few hours or more. In this work, we both theoretically and experimentally demonstrate a method that combines the advantages of both adaptive computational ghost imaging and compressed sensing, which we call adaptive compressive ghost imaging, whereby both the reconstruction time and measurements required for any image size can be significantly reduced. The technique can be used to improve the performance of all computational ghost imaging protocols, especially when measuring ultra-weak or noisy signals, and can be extended to imaging applications at any wavelength.

  15. An efficient approach for video action classification based on 3d Zernike moments

    OpenAIRE

    Lassoued , Imen; Zagrouba , Ezzedine; Chahir , Youssef

    2011-01-01

    International audience; Action recognition in video and still image is one of the most challenging research topics in pattern recognition and computer vision. This paper proposes a new method for video action classification based on 3D Zernike moments. These last ones aim to capturing both structural and temporal information of a time varying sequence. The originality of this approach consists to represent actions in video sequences by a three-dimension shape obtained from different silhouett...

  16. Mechanisms of Action of Probiotics based on Bacillus subtilis

    Directory of Open Access Journals (Sweden)

    A.V. Savustyanenko

    2016-04-01

    Full Text Available The bacterium B.subtilis is one of the most promi­sing probiotics studied in recent decades. Mechanisms of its probiotic action are associated with the synthesis of antimicrobial agents, increasing of non-specific and specific immunity, stimulation of growth of normal microflora of the intestine and the releasing of digestive enzymes. B.subtilis releases ribosomally synthesized peptides, non-ribosomally synthesized peptides and non-peptide substances with a broad spectrum of antimicrobial activity covering Gram-positive, Gram-negative bacteria, viruses and fungi. Resistance to these antimicrobial agents is rare. Enhancement of non-specific immunity is associated with macrophage activation and the release of pro-inflammatory cytokines from them, increasing of barrier function of the intestinal mucosa, releasing of vitamins and amino acids (including essential ones. Enhancement of specific immunity manifests by activation of T- and B-lymphocytes and the release from the latter of immunoglobulins — IgG and IgA. B.subtilis stimulates the growth of normal intestinal flora, in particular, bacteria of the genus Lactobacillus and Bifidobacterium. Furthermore, probiotic increases the diversity of intestinal microflora. Probiotic secretes all major digestive enzymes to the intestinal lumen: amylases, lipases, proteases, pectinases and cellulases. In addition to digestion, these enzymes destroy antinutritional factors and allergenic substances contained in the food. These mechanisms of action make reasonable the use of B.subtilis in the combination therapy to treat intestinal infections; prevention of respiratory infections during the cold season; prevention of antibiotic-associated diarrhea; for the correction of food digestion and movement impairments of various origin (errors in the diet, changes in the diet, diseases of the gastrointestinal tract, disorders of the autonomic nervous system, etc.. B.subtilis does not usually cause side effects. This

  17. 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.

  18. A novel collaborative representation and SCAD based classification method for fibrosis and inflammatory activity analysis of chronic hepatitis C

    Science.gov (United States)

    Cai, Jiaxin; Chen, Tingting; Li, Yan; Zhu, Nenghui; Qiu, Xuan

    2018-03-01

    In order to analysis the fibrosis stage and inflammatory activity grade of chronic hepatitis C, a novel classification method based on collaborative representation (CR) with smoothly clipped absolute deviation penalty (SCAD) penalty term, called CR-SCAD classifier, is proposed for pattern recognition. After that, an auto-grading system based on CR-SCAD classifier is introduced for the prediction of fibrosis stage and inflammatory activity grade of chronic hepatitis C. The proposed method has been tested on 123 clinical cases of chronic hepatitis C based on serological indexes. Experimental results show that the performance of the proposed method outperforms the state-of-the-art baselines for the classification of fibrosis stage and inflammatory activity grade of chronic hepatitis C.

  19. Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

    Science.gov (United States)

    Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

    2001-03-01

    This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

  20. Trait-based representation of hydrological functional properties of plants in weather and ecosystem models

    Directory of Open Access Journals (Sweden)

    Ashley M. Matheny

    2017-02-01

    Full Text Available Land surface models and dynamic global vegetation models typically represent vegetation through coarse plant functional type groupings based on leaf form, phenology, and bioclimatic limits. Although these groupings were both feasible and functional for early model generations, in light of the pace at which our knowledge of functional ecology, ecosystem demographics, and vegetation-climate feedbacks has advanced and the ever growing demand for enhanced model performance, these groupings have become antiquated and are identified as a key source of model uncertainty. The newest wave of model development is centered on shifting the vegetation paradigm away from plant functional types (PFTs and towards flexible trait-based representations. These models seek to improve errors in ecosystem fluxes that result from information loss due to over-aggregation of dissimilar species into the same functional class. We advocate the importance of the inclusion of plant hydraulic trait representation within the new paradigm through a framework of the whole-plant hydraulic strategy. Plant hydraulic strategy is known to play a critical role in the regulation of stomatal conductance and thus transpiration and latent heat flux. It is typical that coexisting plants employ opposing hydraulic strategies, and therefore have disparate patterns of water acquisition and use. Hydraulic traits are deterministic of drought resilience, response to disturbance, and other demographic processes. The addition of plant hydraulic properties in models may not only improve the simulation of carbon and water fluxes but also vegetation population distributions.

  1. Multiple local feature representations and their fusion based on an SVR model for iris recognition using optimized Gabor filters

    Science.gov (United States)

    He, Fei; Liu, Yuanning; Zhu, Xiaodong; Huang, Chun; Han, Ye; Dong, Hongxing

    2014-12-01

    Gabor descriptors have been widely used in iris texture representations. However, fixed basic Gabor functions cannot match the changing nature of diverse iris datasets. Furthermore, a single form of iris feature cannot overcome difficulties in iris recognition, such as illumination variations, environmental conditions, and device variations. This paper provides multiple local feature representations and their fusion scheme based on a support vector regression (SVR) model for iris recognition using optimized Gabor filters. In our iris system, a particle swarm optimization (PSO)- and a Boolean particle swarm optimization (BPSO)-based algorithm is proposed to provide suitable Gabor filters for each involved test dataset without predefinition or manual modulation. Several comparative experiments on JLUBR-IRIS, CASIA-I, and CASIA-V4-Interval iris datasets are conducted, and the results show that our work can generate improved local Gabor features by using optimized Gabor filters for each dataset. In addition, our SVR fusion strategy may make full use of their discriminative ability to improve accuracy and reliability. Other comparative experiments show that our approach may outperform other popular iris systems.

  2. 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,…

  3. Semi-analytical Karhunen-Loeve representation of irregular waves based on the prolate spheroidal wave functions

    Science.gov (United States)

    Lee, Gibbeum; Cho, Yeunwoo

    2018-01-01

    A new semi-analytical approach is presented to solving the matrix eigenvalue problem or the integral equation in Karhunen-Loeve (K-L) representation of random data such as irregular ocean waves. Instead of direct numerical approach to this matrix eigenvalue problem, which may suffer from the computational inaccuracy for big data, a pair of integral and differential equations are considered, which are related to the so-called prolate spheroidal wave functions (PSWF). First, the PSWF is expressed as a summation of a small number of the analytical Legendre functions. After substituting them into the PSWF differential equation, a much smaller size matrix eigenvalue problem is obtained than the direct numerical K-L matrix eigenvalue problem. By solving this with a minimal numerical effort, the PSWF and the associated eigenvalue of the PSWF differential equation are obtained. Then, the eigenvalue of the PSWF integral equation is analytically expressed by the functional values of the PSWF and the eigenvalues obtained in the PSWF differential equation. Finally, the analytically expressed PSWFs and the eigenvalues in the PWSF integral equation are used to form the kernel matrix in the K-L integral equation for the representation of exemplary wave data such as ordinary irregular waves. It is found that, with the same accuracy, the required memory size of the present method is smaller than that of the direct numerical K-L representation and the computation time of the present method is shorter than that of the semi-analytical method based on the sinusoidal functions.

  4. 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...

  5. Action Plan on Base Erosion and Profit Shifting: An Indian Perspective.

    OpenAIRE

    Rao, R. Kavita; Sengupta, D.P.

    2014-01-01

    The discussion in this paper highlights some evidence to support the notion that there is base erosion in India. On the specific action points listed in the OECD's Action Plan, a perspective from India's stand point has been presented along with a brief discussion on the steps needed to prepare for complying with likely proposed measures.

  6. The emergence of climate change mitigation action by society : An agent-based scenario discovery study

    NARCIS (Netherlands)

    Greeven, Sebastiaan; Kraan, O.D.E.; Chappin, E.J.L.; Kwakkel, J.H.

    2016-01-01

    Developing model-based narratives of society’s response to climate change is challenged by two factors. First, society’s response to possible future climate change is subject to many uncertainties. Second, we argue that society’s mitigation action emerge out of the actions and interactions of the

  7. New solutions of the Yang-Baxter equation based on root of 1 representations of the Para-Bose superalgebra Uq[osp(1/2)

    International Nuclear Information System (INIS)

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

    1995-07-01

    New solutions of the quantum Yang-Baxter equation, depending in general on three arbitrary parameters, are written down. They are based on the root of unity representations of the quantum orthosymplectic superalgebra U q [osp(1/2)], which were found recently. Representations of the braid group B N are defined within any N th tensorial power of root of 1 U q [osp(1/2)] modules. (author). 40 refs

  8. Quiver representations

    CERN Document Server

    Schiffler, Ralf

    2014-01-01

    This book is intended to serve as a textbook for a course in Representation Theory of Algebras at the beginning graduate level. The text has two parts. In Part I, the theory is studied in an elementary way using quivers and their representations. This is a very hands-on approach and requires only basic knowledge of linear algebra. The main tool for describing the representation theory of a finite-dimensional algebra is its Auslander-Reiten quiver, and the text introduces these quivers as early as possible. Part II then uses the language of algebras and modules to build on the material developed before. The equivalence of the two approaches is proved in the text. The last chapter gives a proof of Gabriel’s Theorem. The language of category theory is developed along the way as needed.

  9. Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.

    Science.gov (United States)

    Cang, Zixuan; Mu, Lin; Wei, Guo-Wei

    2018-01-01

    This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination.

  10. Three-dimensional plasma equilibrium model based on the poloidal representation of the magnetic field

    International Nuclear Information System (INIS)

    Gruber, R.; Degtyarev, L.M.; Kuper, A.; Martynov, A.A.; Medvedev, S.Yu.; Shafranov, V.D.

    1996-01-01

    Equations for the three-dimensional equilibrium of a plasma are formulated in the poloidal representation. The magnetic field is expressed in terms of the poloidal magnetic flux Ψ and the poloidal electric current F. As a result, three-dimensional equilibrium configurations are analyzed with the help of a set of equations including the elliptical equation for the poloidal flux, the magnetic differential equation for the parallel current, and the equations for the basis vector field b. To overcome the difficulties associated with peculiarities that can arise in solving the magnetic differential equation at rational toroidal magnetic surfaces, small regulating corrections are introduced into the proposed set of equations. In this case, second-order differential terms with a small parameter appear in the magnetic differential equations. As a result, these equations take the form of elliptical equations. Three versions of regulating corrections are proposed. The equations obtained can be used to develop numerical codes for calculating three-dimensional equilibrium plasma configurations with an island structure

  11. Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening

    Science.gov (United States)

    Mu, Lin

    2018-01-01

    This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules and biomolecular complexes. In contrast to the conventional persistent homology, multi-component persistent homology retains critical chemical and biological information during the topological simplification of biomolecular geometric complexity. Multi-level persistent homology enables a tailored topological description of inter- and/or intra-molecular interactions of interest. Electrostatic persistence incorporates partial charge information into topological invariants. These topological methods are paired with Wasserstein distance to characterize similarities between molecules and are further integrated with a variety of machine learning algorithms, including k-nearest neighbors, ensemble of trees, and deep convolutional neural networks, to manifest their descriptive and predictive powers for protein-ligand binding analysis and virtual screening of small molecules. Extensive numerical experiments involving 4,414 protein-ligand complexes from the PDBBind database and 128,374 ligand-target and decoy-target pairs in the DUD database are performed to test respectively the scoring power and the discriminatory power of the proposed topological learning strategies. It is demonstrated that the present topological learning outperforms other existing methods in protein-ligand binding affinity prediction and ligand-decoy discrimination. PMID:29309403

  12. Structure factors for tunneling ionization rates of molecules: General Hartree-Fock-based integral representation

    Science.gov (United States)

    Madsen, Lars Bojer; Jensen, Frank; Dnestryan, Andrey I.; Tolstikhin, Oleg I.

    2017-07-01

    In the leading-order approximation of the weak-field asymptotic theory (WFAT), the dependence of the tunneling ionization rate of a molecule in an electric field on its orientation with respect to the field is determined by the structure factor of the ionizing molecular orbital. The WFAT yields an expression for the structure factor in terms of a local property of the orbital in the asymptotic region. However, in general quantum chemistry approaches molecular orbitals are expanded in a Gaussian basis which does not reproduce their asymptotic behavior correctly. This hinders the application of the WFAT to polyatomic molecules, which are attracting increasing interest in strong-field physics. Recently, an integral-equation approach to the WFAT for tunneling ionization of one electron from an arbitrary potential has been developed. The structure factor is expressed in an integral form as a matrix element involving the ionizing orbital. The integral is not sensitive to the asymptotic behavior of the orbital, which resolves the difficulty mentioned above. Here, we extend the integral representation for the structure factor to many-electron systems treated within the Hartree-Fock method and show how it can be implemented on the basis of standard quantum chemistry software packages. We validate the methodology by considering noble-gas atoms and the CO molecule, for which accurate structure factors exist in the literature. We also present benchmark results for CO2 and for NH3 in the pyramidal and planar geometries.

  13. Representational Machines

    DEFF Research Database (Denmark)

    Photography not only represents space. Space is produced photographically. Since its inception in the 19th century, photography has brought to light a vast array of represented subjects. Always situated in some spatial order, photographic representations have been operatively underpinned by social...... to the enterprises of the medium. This is the subject of Representational Machines: How photography enlists the workings of institutional technologies in search of establishing new iconic and social spaces. Together, the contributions to this edited volume span historical epochs, social environments, technological...... possibilities, and genre distinctions. Presenting several distinct ways of producing space photographically, this book opens a new and important field of inquiry for photography research....

  14. Group representations

    CERN Document Server

    Karpilovsky, G

    1994-01-01

    This third volume can be roughly divided into two parts. The first part is devoted to the investigation of various properties of projective characters. Special attention is drawn to spin representations and their character tables and to various correspondences for projective characters. Among other topics, projective Schur index and projective representations of abelian groups are covered. The last topic is investigated by introducing a symplectic geometry on finite abelian groups. The second part is devoted to Clifford theory for graded algebras and its application to the corresponding theory

  15. Value Representations

    DEFF Research Database (Denmark)

    Rasmussen, Majken Kirkegaard; Petersen, Marianne Graves

    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...

  16. Graph-based representation of behavior in detection and prediction of daily living activities.

    Science.gov (United States)

    Augustyniak, Piotr; Ślusarczyk, Grażyna

    2018-04-01

    Various surveillance systems capture signs of human activities of daily living (ADLs) and store multimodal information as time line behavioral records. In this paper, we present a novel approach to the analysis of a behavioral record used in a surveillance system designed for use in elderly smart homes. The description of a subject's activity is first decomposed into elementary poses - easily detectable by dedicated intelligent sensors - and represented by the share coefficients. Then, the activity is represented in the form of an attributed graph, where nodes correspond to elementary poses. As share coefficients of poses are expressed as attributes assigned to graph nodes, their change corresponding to a subject's action is represented by flow in graph edges. The behavioral record is thus a time series of graphs, which tiny size facilitates storage and management of long-term monitoring results. At the system learning stage, the contribution of elementary poses is accumulated, discretized and probability-ordered leading to a finite list representing the possible transitions between states. Such a list is independently built for each room in the supervised residence, and employed for assessment of the current action in the context of subject's habits and a room purpose. The proposed format of a behavioral record, applied to an adaptive surveillance system, is particularly advantageous for representing new activities not known at the setup stage, for providing a quantitative measure of transitions between poses and for expressing the difference between a predicted and actual action in a numerical way. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  17. A proactive condition-based maintenance strategy with both perfect and imperfect maintenance actions

    International Nuclear Information System (INIS)

    Do, Phuc; Voisin, Alexandre; Levrat, Eric; Iung, Benoit

    2015-01-01

    This paper deals with a proactive condition-based maintenance (CBM) considering both perfect and imperfect maintenance actions for a deteriorating system. Perfect maintenance actions restore completely the system to the ‘as good as new’ state. Their related cost are however often high. The first objective of the paper is to investigate the impacts of imperfect maintenance actions. In fact, both positive and negative impacts are considered. Positive impact means that the imperfect maintenance cost is usually low. Negative impact implies that (i) the imperfect maintenance restores a system to a state between good-as-new and bad-as-old and (ii) each imperfect preventive action may accelerate the speed of the system's deterioration process. The second objective of the paper is to propose an adaptive maintenance policy which can help to select optimally maintenance actions (perfect or imperfect actions), if needed, at each inspection time. Moreover, the time interval between two successive inspection points is determined according to a remaining useful life (RUL) based-inspection policy. To illustrate the use of the proposed maintenance policy, a numerical example finally is introduced. - Highlights: • A new imperfect maintenance model for deterioration system is proposed. • Both positive and negative impacts of an imperfect maintenance action are investigated. • An adaptive condition-based maintenance policy is introduced. • The optimal number of useful imperfect maintenance actions for each life cycle is optimally provided

  18. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation.

    Science.gov (United States)

    Zhang, Zutao; Luo, Dianyuan; Rasim, Yagubov; Li, Yanjun; Meng, Guanjun; Xu, Jian; Wang, Chunbai

    2016-02-19

    In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  19. A Vehicle Active Safety Model: Vehicle Speed Control Based on Driver Vigilance Detection Using Wearable EEG and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

    Full Text Available In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI system with eight channels is designed for collecting the driver’s EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT is adopted to extract the EEG power spectrum density (PSD. In this step, sparse representation classification combined with k-singular value decomposition (KSVD is firstly introduced in PSD to estimate the driver’s vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model.

  20. Teachers’ individual action theories about competence-based education: the value of the cognitive apprenticeship model

    NARCIS (Netherlands)

    Seezink, Audrey; Poell, Rob; Kirschner, Paul A.

    2009-01-01

    Seezink, A., Poell, R. F., & Kirschner, P. A. (2009). Teachers' individual action theories about competence-based education: The value of the cognitive apprenticeship model. Journal of Vocational Education & Training, 61, 203-215.

  1. Initial Remedial Action Plan for Expanded Bioventing System BX Service Station, Patrick Air Force Base, Florida

    National Research Council Canada - National Science Library

    1995-01-01

    This initial remedial action plan presents the scope for an expanded bioventing system for in situ treatment of fuel-contaminated soils at the BX Service Station at Patrick Air Force Base (AFB), Florida...

  2. Remedial Action Plan for Expanded Bioventing System Buildings 2034/2035, Fairchild Air Force Base, Washington

    National Research Council Canada - National Science Library

    1996-01-01

    This remedial action plan (RAP) presents the scope for an expanded bioventing system for in situ treatment of fuel-contaminated soils in the vicinity of Buildings 2034 and 2035 at Fairchild Air Force Base (AFB), Washington...

  3. 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....

  4. Lambert W-function based exact representation for double diode model of solar cells: Comparison on fitness and parameter extraction

    International Nuclear Information System (INIS)

    Gao, Xiankun; Cui, Yan; Hu, Jianjun; Xu, Guangyin; Yu, Yongchang

    2016-01-01

    Highlights: • Lambert W-function based exact representation (LBER) is presented for double diode model (DDM). • Fitness difference between LBER and DDM is verified by reported parameter values. • The proposed LBER can better represent the I–V and P–V characteristics of solar cells. • Parameter extraction difference between LBER and DDM is validated by two algorithms. • The parameter values extracted from LBER are more accurate than those from DDM. - Abstract: Accurate modeling and parameter extraction of solar cells play an important role in the simulation and optimization of PV systems. This paper presents a Lambert W-function based exact representation (LBER) for traditional double diode model (DDM) of solar cells, and then compares their fitness and parameter extraction performance. Unlike existing works, the proposed LBER is rigorously derived from DDM, and in LBER the coefficients of Lambert W-function are not extra parameters to be extracted or arbitrary scalars but the vectors of terminal voltage and current of solar cells. The fitness difference between LBER and DDM is objectively validated by the reported parameter values and experimental I–V data of a solar cell and four solar modules from different technologies. The comparison results indicate that under the same parameter values, the proposed LBER can better represent the I–V and P–V characteristics of solar cells and provide a closer representation to actual maximum power points of all module types. Two different algorithms are used to compare the parameter extraction performance of LBER and DDM. One is our restart-based bound constrained Nelder-Mead (rbcNM) algorithm implemented in Matlab, and the other is the reported R_c_r-IJADE algorithm executed in Visual Studio. The comparison results reveal that, the parameter values extracted from LBER using two algorithms are always more accurate and robust than those from DDM despite more time consuming. As an improved version of DDM, the

  5. Deep Learning based Super-Resolution for Improved Action Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman

    2015-01-01

    with results of a state-of- the-art deep learning-based super-resolution algorithm, through an alpha-blending approach. The experimental results obtained on down-sampled version of a large subset of Hoolywood2 benchmark database show the importance of the proposed system in increasing the recognition rate...

  6. Performance-Based Measurement: Action for Organizations and HPT Accountability

    Science.gov (United States)

    Larbi-Apau, Josephine A.; Moseley, James L.

    2010-01-01

    Basic measurements and applications of six selected general but critical operational performance-based indicators--effectiveness, efficiency, productivity, profitability, return on investment, and benefit-cost ratio--are presented. With each measurement, goals and potential impact are explored. Errors, risks, limitations to measurements, and a…

  7. Design and Development of a Linked Open Data-Based Health Information Representation and Visualization System: Potentials and Preliminary Evaluation

    Science.gov (United States)

    Kauppinen, Tomi; Keßler, Carsten; Fritz, Fleur

    2014-01-01

    Background Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)—a new Semantic Web set of best practice of standards to publish and link heterogeneous data—can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. Objective The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. Methods We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk—a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. Results We developed an LOD-based

  8. Design and development of a linked open data-based health information representation and visualization system: potentials and preliminary evaluation.

    Science.gov (United States)

    Tilahun, Binyam; Kauppinen, Tomi; Keßler, Carsten; Fritz, Fleur

    2014-10-25

    Healthcare organizations around the world are challenged by pressures to reduce cost, improve coordination and outcome, and provide more with less. This requires effective planning and evidence-based practice by generating important information from available data. Thus, flexible and user-friendly ways to represent, query, and visualize health data becomes increasingly important. International organizations such as the World Health Organization (WHO) regularly publish vital data on priority health topics that can be utilized for public health policy and health service development. However, the data in most portals is displayed in either Excel or PDF formats, which makes information discovery and reuse difficult. Linked Open Data (LOD)-a new Semantic Web set of best practice of standards to publish and link heterogeneous data-can be applied to the representation and management of public level health data to alleviate such challenges. However, the technologies behind building LOD systems and their effectiveness for health data are yet to be assessed. The objective of this study is to evaluate whether Linked Data technologies are potential options for health information representation, visualization, and retrieval systems development and to identify the available tools and methodologies to build Linked Data-based health information systems. We used the Resource Description Framework (RDF) for data representation, Fuseki triple store for data storage, and Sgvizler for information visualization. Additionally, we integrated SPARQL query interface for interacting with the data. We primarily use the WHO health observatory dataset to test the system. All the data were represented using RDF and interlinked with other related datasets on the Web of Data using Silk-a link discovery framework for Web of Data. A preliminary usability assessment was conducted following the System Usability Scale (SUS) method. We developed an LOD-based health information representation, querying

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

    Science.gov (United States)

    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

  10. Numerical model of the nanoindentation test based on the digital material representation of the Ti/TiN multilayers

    Directory of Open Access Journals (Sweden)

    Perzyński Konrad

    2015-06-01

    Full Text Available The developed numerical model of a local nanoindentation test, based on the digital material representation (DMR concept, has been presented within the paper. First, an efficient algorithm describing the pulsed laser deposition (PLD process was proposed to realistically recreate the specific morphology of a nanolayered material in an explicit manner. The nanolayered Ti/TiN composite was selected for the investigation. Details of the developed cellular automata model of the PLD process were presented and discussed. Then, the Ti/TiN DMR was incorporated into the finite element software and numerical model of the nanoindentation test was established. Finally, examples of obtained results presenting capabilities of the proposed approach were highlighted.

  11. Representation of Block-Based Image Features in a Multi-Scale Framework for Built-Up Area Detection

    Directory of Open Access Journals (Sweden)

    Zhongwen Hu

    2016-02-01

    Full Text Available The accurate extraction and mapping of built-up areas play an important role in many social, economic, and environmental studies. In this paper, we propose a novel approach for built-up area detection from high spatial resolution remote sensing images, using a block-based multi-scale feature representation framework. First, an image is divided into small blocks, in which the spectral, textural, and structural features are extracted and represented using a multi-scale framework; a set of refined Harris corner points is then used to select blocks as training samples; finally, a built-up index image is obtained by minimizing the normalized spectral, textural, and structural distances to the training samples, and a built-up area map is obtained by thresholding the index image. Experiments confirm that the proposed approach is effective for high-resolution optical and synthetic aperture radar images, with different scenes and different spatial resolutions.

  12. Discovery Learning, Representation, and Explanation within a Computer-Based Simulation: Finding the Right Mix

    Science.gov (United States)

    Rieber, Lloyd P.; Tzeng, Shyh-Chii; Tribble, Kelly

    2004-01-01

    The purpose of this research was to explore how adult users interact and learn during an interactive computer-based simulation supplemented with brief multimedia explanations of the content. A total of 52 college students interacted with a computer-based simulation of Newton's laws of motion in which they had control over the motion of a simple…

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

    Directory of Open Access Journals (Sweden)

    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

  14. Accounting of the knowledge-based actions and the rules-based actions in frames of accident management guidelines development

    International Nuclear Information System (INIS)

    Lankin, M.Yu.; Bukrinskij, A.M.

    2015-01-01

    The main approaches used in the development of the Safety Guide (SG) “Recommendations to the structure and content of the manual for the management of beyond-design-basis accidents, including severe accidents” (BDBA MG) are described. The manual was developed taking into account the provisions of the current IAEA standards relevant to the affected area, taking into account the specifics of the Russian nuclear power industry. In the draft SG, three types of behavior of personnel are considered - based on skills, rules and knowledge. When developing BDBA MG, it is recommended to give priority to a knowledge-based approach. At the same time, when performing well-designed and worked-out activities, work is possible based on rules and skills (for example, using step-by-step procedures). The SG project provides for a unified organizational structure for managing beyond-design-basis accidents, both at the stage of preventing severe damage to the core, and at the stage of managing a heavy accident. In SG the order of management of beyond-design-basis accidents for both of the indicated stages examined in detail [ru

  15. DEVS representation of dynamical systems - Event-based intelligent control. [Discrete Event System Specification

    Science.gov (United States)

    Zeigler, Bernard P.

    1989-01-01

    It is shown how systems can be advantageously represented as discrete-event models by using DEVS (discrete-event system specification), a set-theoretic formalism. Such DEVS models provide a basis for the design of event-based logic control. In this control paradigm, the controller expects to receive confirming sensor responses to its control commands within definite time windows determined by its DEVS model of the system under control. The event-based contral paradigm is applied in advanced robotic and intelligent automation, showing how classical process control can be readily interfaced with rule-based symbolic reasoning systems.

  16. 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)

  17. LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

    Science.gov (United States)

    Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

    2016-01-11

    Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

  18. Geometric representation of the mean-variance-skewness portfolio frontier based upon the shortage function

    OpenAIRE

    Kerstens, Kristiaan; Mounier, Amine; Van de Woestyne, Ignace

    2008-01-01

    The literature suggests that investors prefer portfolios based on mean, variance and skewness rather than portfolios based on mean-variance (MV) criteria solely. Furthermore, a small variety of methods have been proposed to determine mean-variance-skewness (MVS) optimal portfolios. Recently, the shortage function has been introduced as a measure of efficiency, allowing to characterize MVS optimalportfolios using non-parametric mathematical programming tools. While tracing the MV portfolio fro...

  19. 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.

  20. 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.

  1. 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).

  2. 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...

  3. A Novel Relevance Feedback Approach Based on Similarity Measure Modification in an X-Ray Image Retrieval System Based on Fuzzy Representation Using Fuzzy Attributed Relational Graph

    Directory of Open Access Journals (Sweden)

    Hossien Pourghassem

    2011-04-01

    Full Text Available Relevance feedback approaches is used to improve the performance of content-based image retrieval systems. In this paper, a novel relevance feedback approach based on similarity measure modification in an X-ray image retrieval system based on fuzzy representation using fuzzy attributed relational graph (FARG is presented. In this approach, optimum weight of each feature in feature vector is calculated using similarity rate between query image and relevant and irrelevant images in user feedback. The calculated weight is used to tune fuzzy graph matching algorithm as a modifier parameter in similarity measure. The standard deviation of the retrieved image features is applied to calculate the optimum weight. The proposed image retrieval system uses a FARG for representation of images, a fuzzy matching graph algorithm as similarity measure and a semantic classifier based on merging scheme for determination of the search space in image database. To evaluate relevance feedback approach in the proposed system, a standard X-ray image database consisting of 10000 images in 57 classes is used. The improvement of the evaluation parameters shows proficiency and efficiency of the proposed system.

  4. Tensor Based Representation and Analysis of Diffusion-Weighted Magnetic Resonance Images

    Science.gov (United States)

    Barmpoutis, Angelos

    2009-01-01

    Cartesian tensor bases have been widely used to model spherical functions. In medical imaging, tensors of various orders can approximate the diffusivity function at each voxel of a diffusion-weighted MRI data set. This approximation produces tensor-valued datasets that contain information about the underlying local structure of the scanned tissue.…

  5. Improving Conceptual Understanding and Representation Skills through Excel-Based Modeling

    Science.gov (United States)

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

    2018-01-01

    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…

  6. Scale space representations locally adapted to the geometry of base and target manifold

    NARCIS (Netherlands)

    Florack, L.M.J.

    2010-01-01

    We generalize the Gaussian multi-resolution image paradigm for a Euclidean domain to general Riemannian base manifolds and also account for the codomain by considering the extension into a fibre bundle structure. We elaborate on aspects of parametrization and gauge, as these are important in

  7. Image denoising using new pixon representation based on fuzzy filtering and partial differential equations

    DEFF Research Database (Denmark)

    Nadernejad, Ehsan; Nikpour, Mohsen

    2012-01-01

    In this paper, we have proposed two extensions to pixon-based image modeling. The first one is using bicubic interpolation instead of bilinear interpolation and the second one is using fuzzy filtering method, aiming to improve the quality of the pixonal image. Finally, partial differential...

  8. Memory-Based Decision-Making with Heuristics: Evidence for a Controlled Activation of Memory Representations

    Science.gov (United States)

    Khader, Patrick H.; Pachur, Thorsten; Meier, Stefanie; Bien, Siegfried; Jost, Kerstin; Rosler, Frank

    2011-01-01

    Many of our daily decisions are memory based, that is, the attribute information about the decision alternatives has to be recalled. Behavioral studies suggest that for such decisions we often use simple strategies (heuristics) that rely on controlled and limited information search. It is assumed that these heuristics simplify decision-making by…

  9. Computer-Based Learning: Interleaving Whole and Sectional Representation of Neuroanatomy

    Science.gov (United States)

    Pani, John R.; Chariker, Julia H.; Naaz, Farah

    2013-01-01

    The large volume of material to be learned in biomedical disciplines requires optimizing the efficiency of instruction. In prior work with computer-based instruction of neuroanatomy, it was relatively efficient for learners to master whole anatomy and then transfer to learning sectional anatomy. It may, however, be more efficient to continuously…

  10. Effective representation and storage of mass spectrometry-based proteomic data sets for the scientific community

    DEFF Research Database (Denmark)

    Olsen, Jesper V; Mann, Matthias

    2011-01-01

    Mass spectrometry-based proteomics has emerged as a technology of choice for global analysis of cell signaling networks. However, reporting and sharing of MS data are often haphazard, limiting the usefulness of proteomics to the signaling community. We argue that raw data should always be provided...... mechanisms for community-wide sharing of these data....

  11. Virtual screening applications: a study of ligand-based methods and different structure representations in four different scenarios.

    Science.gov (United States)

    Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann

    2007-01-01

    Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.

  12. 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.

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

    Science.gov (United States)

    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.

  14. Knowledge Representation and Reasoning in Personalized Web-Based e-Learning Applications

    DEFF Research Database (Denmark)

    Dolog, Peter

    2006-01-01

    a user inferred from user interactions with the eLeanrning systems is used to adapt o®ered learning resources and guide a learner through them. This keynote gives an overview about knowledge and rules taken into account in current adaptive eLearning prototypes when adapting learning instructions....... Adaptation is usually based on knowledge about learning esources and users. Rules are used for heuristics to match the learning resources with learners and infer adaptation decisions.......Adaptation that is so natural for teaching by humans is a challenging issue for electronic learning tools. Adaptation in classic teaching is based on observations made about students during teaching. Similar idea was employed in user-adapted (personalized) eLearning applications. Knowledge about...

  15. Tuning of methods for offset free MPC based on ARX model representations

    DEFF Research Database (Denmark)

    Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay

    2010-01-01

    In this paper we investigate model predictive control (MPC) based on ARX models. ARX models can be identified from data using convex optimization technologies and is linear in the system parameters. Compared to other model parameterizations this feature is an advantage in embedded applications...... for robust and automatic system identification. Standard MPC is not able to reject a sustained, unmeasured, non zero mean disturbance and will therefore not provide offset free tracking. Offset free tracking can be guaranteed for this type of disturbances if Δ variables are used or if the state space...... is extended with a disturbance model state. The relation between the base case and the two extended methods are illustrated which provides good understanding and a platform for discussing tuning for good closed loop performance....

  16. ORTHOGONAL REPRESENTATION OF THE PROPER TRANSFORMATION OF A PERSYMMETRIC MATRIX BASED ON ROTATION OPERATORS

    Directory of Open Access Journals (Sweden)

    V. M. Demko

    2018-01-01

    Full Text Available The mathematical substantiation of the algorithm for synthesis of the proper transformation and finding the eigenvalue formulae of a persymmetric matrix of dimension N = 2 k ( k =1, 4 based on orthogonal rotation operators is given. The proposed algorithm made it possible to improve the author's approach to calculating eigenvalues based on numerical examples for the maximal dimension of matrices 64×64, resulting the possibility to obtain analytical relations for calculating the eigenvalues of the persymmetric matrix. It is shown that the proper transformation has a factorized structure in the form of a product of rotation operators, each of which is a direct sum of elementary Givens and Jacobian rotation matrices. 

  17. Object-based selection from spatially-invariant representations: evidence from a feature-report task.

    Science.gov (United States)

    Matsukura, Michi; Vecera, Shaun P

    2011-02-01

    Attention selects objects as well as locations. When attention selects an object's features, observers identify two features from a single object more accurately than two features from two different objects (object-based effect of attention; e.g., Duncan, Journal of Experimental Psychology: General, 113, 501-517, 1984). Several studies have demonstrated that object-based attention can operate at a late visual processing stage that is independent of objects' spatial information (Awh, Dhaliwal, Christensen, & Matsukura, Psychological Science, 12, 329-334, 2001; Matsukura & Vecera, Psychonomic Bulletin & Review, 16, 529-536, 2009; Vecera, Journal of Experimental Psychology: General, 126, 14-18, 1997; Vecera & Farah, Journal of Experimental Psychology: General, 123, 146-160, 1994). In the present study, we asked two questions regarding this late object-based selection mechanism. In Part I, we investigated how observers' foreknowledge of to-be-reported features allows attention to select objects, as opposed to individual features. Using a feature-report task, a significant object-based effect was observed when to-be-reported features were known in advance but not when this advance knowledge was absent. In Part II, we examined what drives attention to select objects rather than individual features in the absence of observers' foreknowledge of to-be-reported features. Results suggested that, when there was no opportunity for observers to direct their attention to objects that possess to-be-reported features at the time of stimulus presentation, these stimuli must retain strong perceptual cues to establish themselves as separate objects.

  18. Caribbean and Central American Women's Feminist Inquiry through Theater-Based Action Research

    Science.gov (United States)

    Sánchez Ares, Rocío

    2015-01-01

    Feminist action research interrogates gendered dynamics in the development of a collective consciousness. A group of immigrant Latina women (Latinas) from the Caribbean and Central America employed community-based theater as an instrument to mobilize diverse audiences against discriminatory practices and policies. Based on their theater work, I…

  19. Representation and Imperialism in Edward Said

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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

  1. 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.

  2. Virtual Reality Based Accurate Radioactive Source Representation and Dosimetry for Training Applications

    International Nuclear Information System (INIS)

    Molto-Caracena, T.; Vendrell Vidal, E.; Goncalves, J.G.M.; Peerani, P.; )

    2015-01-01

    Virtual Reality (VR) technologies have much potential for training applications. Success relies on the capacity to provide a real-time immersive effect to a trainee. For a training application to be an effective/meaningful tool, 3D realistic scenarios are not enough. Indeed, it is paramount having sufficiently accurate models of the behaviour of the instruments to be used by a trainee. This will enable the required level of user's interactivity. Specifically, when dealing with simulation of radioactive sources, a VR model based application must compute the dose rate with equivalent accuracy and in about the same time as a real instrument. A conflicting requirement is the need to provide a smooth visual rendering enabling spatial interactivity and interaction. This paper presents a VR based prototype which accurately computes the dose rate of radioactive and nuclear sources that can be selected from a wide library. Dose measurements reflect local conditions, i.e., presence of (a) shielding materials with any shape and type and (b) sources with any shape and dimension. Due to a novel way of representing radiation sources, the system is fast enough to grant the necessary user interactivity. The paper discusses the application of this new method and its advantages in terms of time setting, cost and logistics. (author)

  3. Detecting Activation in fMRI Data: An Approach Based on Sparse Representation of BOLD Signal

    Directory of Open Access Journals (Sweden)

    Blanca Guillen

    2018-01-01

    Full Text Available This paper proposes a simple yet effective approach for detecting activated voxels in fMRI data by exploiting the inherent sparsity property of the BOLD signal in temporal and spatial domains. In the time domain, the approach combines the General Linear Model (GLM with a Least Absolute Deviation (LAD based regression method regularized by the pseudonorm l0 to promote sparsity in the parameter vector of the model. In the spatial domain, detection of activated regions is based on thresholding the spatial map of estimated parameters associated with a particular stimulus. The threshold is calculated by exploiting the sparseness of the BOLD signal in the spatial domain assuming a Laplacian distribution model. The proposed approach is validated using synthetic and real fMRI data. For synthetic data, results show that the proposed approach is able to detect most activated voxels without any false activation. For real data, the method is evaluated through comparison with the SPM software. Results indicate that this approach can effectively find activated regions that are similar to those found by SPM, but using a much simpler approach. This study may lead to the development of robust spatial approaches to further simplifying the complexity of classical schemes.

  4. Incidence of a didactic sequence, based on multiple representations, for the strengthening of argumentative competence in high school students

    Directory of Open Access Journals (Sweden)

    Gustavo Bonilla

    2018-01-01

    Full Text Available The present article; seeks to identify the way in which a didactic sequence, based on the implementation of multiple representations, can have an impact on the strengthening of the argumentative competence in basic secondary school students. The methodological foundation on which is based the research, taking into account the mixed approach as a perspective that properly oriented, the exercise of research in the field of education. In view of the above, it performs a process of pedagogical intervention related to the general law of ideal gases, through the implementation of the elements presented in the didactic cycle with a research approach and with the application of a pretest and posttest. The techniques to be used for the process of intervention are the participant observation, the discussion group and the survey. Specifically, as instruments for the collection of information; the interview focused, semi-structured interview and the questions guide. The unit of work corresponds to 36 students --240, six students per each group of 9°-- the basic secondary educational institutions belonging to the Citadel New West, located in the Commune 60 and The Heart, located in the commune 13; both in the city of Medellín.

  5. Automatic media-adventitia IVUS image segmentation based on sparse representation framework and dynamic directional active contour model.

    Science.gov (United States)

    Zakeri, Fahimeh Sadat; Setarehdan, Seyed Kamaledin; Norouzi, Somayye

    2017-10-01

    Segmentation of the arterial wall boundaries from intravascular ultrasound images is an important image processing task in order to quantify arterial wall characteristics such as shape, area, thickness and eccentricity. Since manual segmentation of these boundaries is a laborious and time consuming procedure, many researchers attempted to develop (semi-) automatic segmentation techniques as a powerful tool for educational and clinical purposes in the past but as yet there is no any clinically approved method in the market. This paper presents a deterministic-statistical strategy for automatic media-adventitia border detection by a fourfold algorithm. First, a smoothed initial contour is extracted based on the classification in the sparse representation framework which is combined with the dynamic directional convolution vector field. Next, an active contour model is utilized for the propagation of the initial contour toward the interested borders. Finally, the extracted contour is refined in the leakage, side branch openings and calcification regions based on the image texture patterns. The performance of the proposed algorithm is evaluated by comparing the results to those manually traced borders by an expert on 312 different IVUS images obtained from four different patients. The statistical analysis of the results demonstrates the efficiency of the proposed method in the media-adventitia border detection with enough consistency in the leakage and calcification regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Machinery vibration signal denoising based on learned dictionary and sparse representation

    International Nuclear Information System (INIS)

    Guo, Liang; Gao, Hongli; Li, Jun; Huang, Haifeng; Zhang, Xiaochen

    2015-01-01

    Mechanical vibration signal denoising has been an import problem for machine damage assessment and health monitoring. Wavelet transfer and sparse reconstruction are the powerful and practical methods. However, those methods are based on the fixed basis functions or atoms. In this paper, a novel method is presented. The atoms used to represent signals are learned from the raw signal. And in order to satisfy the requirements of real-time signal processing, an online dictionary learning algorithm is adopted. Orthogonal matching pursuit is applied to extract the most pursuit column in the dictionary. At last, denoised signal is calculated with the sparse vector and learned dictionary. A simulation signal and real bearing fault signal are utilized to evaluate the improved performance of the proposed method through the comparison with kinds of denoising algorithms. Then Its computing efficiency is demonstrated by an illustrative runtime example. The results show that the proposed method outperforms current algorithms with efficiency calculation. (paper)

  7. XML representation and management of temporal information for web-based cultural heritage applications

    Directory of Open Access Journals (Sweden)

    Fabio Grandi

    2006-01-01

    Full Text Available In this paper we survey the recent activities and achievements of our research group in the deployment of XMLrelated technologies in Cultural Heritage applications concerning the encoding of temporal semantics in Web documents. In particular we will review "The Valid Web", which is an XML/XSL infrastructure we defined and implemented for the definition and management of historical information within multimedia documents available on the Web, and its further extension to the effective encoding of advanced temporal features like indeterminacy, multiple granularities and calendars, enabling an efficient processing in a user-friendly Web-based environment. Potential uses of the developed infrastructures include a broad range of applications in the cultural heritage domain, where the historical perspective is relevant, with potentially positive impacts on E-Education and E-Science.

  8. Status of the phenomena representation, 3D modeling, and cloud-based software architecture development

    International Nuclear Information System (INIS)

    Smith, Curtis L.; Prescott, Steven; Kvarfordt, Kellie; Sampath, Ram; Larson, Katie

    2015-01-01

    Early in 2013, researchers at the Idaho National Laboratory outlined a technical framework to support the implementation of state-of-the-art probabilistic risk assessment to predict the safety performance of advanced small modular reactors. From that vision of the advanced framework for risk analysis, specific tasks have been underway in order to implement the framework. This report discusses the current development of a several tasks related to the framework implementation, including a discussion of a 3D physics engine that represents the motion of objects (including collision and debris modeling), cloud-based analysis tools such as a Bayesian-inference engine, and scenario simulations. These tasks were performed during 2015 as part of the technical work associated with the Advanced Reactor Technologies Program.

  9. A Physics-Based Deep Learning Approach to Shadow Invariant Representations of Hyperspectral Images.

    Science.gov (United States)

    Windrim, Lloyd; Ramakrishnan, Rishi; Melkumyan, Arman; Murphy, Richard J

    2018-02-01

    This paper proposes the Relit Spectral Angle-Stacked Autoencoder, a novel unsupervised feature learning approach for mapping pixel reflectances to illumination invariant encodings. This work extends the Spectral Angle-Stacked Autoencoder so that it can learn a shadow-invariant mapping. The method is inspired by a deep learning technique, Denoising Autoencoders, with the incorporation of a physics-based model for illumination such that the algorithm learns a shadow invariant mapping without the need for any labelled training data, additional sensors, a priori knowledge of the scene or the assumption of Planckian illumination. The method is evaluated using datasets captured from several different cameras, with experiments to demonstrate the illumination invariance of the features and how they can be used practically to improve the performance of high-level perception algorithms that operate on images acquired outdoors.

  10. [Research of electroencephalography representational emotion recognition based on deep belief networks].

    Science.gov (United States)

    Yang, Hao; Zhang, Junran; Jiang, Xiaomei; Liu, Fei

    2018-04-01

    In recent years, with the rapid development of machine learning techniques,the deep learning algorithm has been widely used in one-dimensional physiological signal processing. In this paper we used electroencephalography (EEG) signals based on deep belief network (DBN) model in open source frameworks of deep learning to identify emotional state (positive, negative and neutrals), then the results of DBN were compared with support vector machine (SVM). The EEG signals were collected from the subjects who were under different emotional stimuli, and DBN and SVM were adopted to identify the EEG signals with changes of different characteristics and different frequency bands. We found that the average accuracy of differential entropy (DE) feature by DBN is 89.12%±6.54%, which has a better performance than previous research based on the same data set. At the same time, the classification effects of DBN are better than the results from traditional SVM (the average classification accuracy of 84.2%±9.24%) and its accuracy and stability have a better trend. In three experiments with different time points, single subject can achieve the consistent results of classification by using DBN (the mean standard deviation is1.44%), and the experimental results show that the system has steady performance and good repeatability. According to our research, the characteristic of DE has a better classification result than other characteristics. Furthermore, the Beta band and the Gamma band in the emotional recognition model have higher classification accuracy. To sum up, the performances of classifiers have a promotion by using the deep learning algorithm, which has a reference for establishing a more accurate system of emotional recognition. Meanwhile, we can trace through the results of recognition to find out the brain regions and frequency band that are related to the emotions, which can help us to understand the emotional mechanism better. This study has a high academic value and

  11. Trait-based representation of biological nitrification: Model development, testing, and predicted community composition

    Directory of Open Access Journals (Sweden)

    Nick eBouskill

    2012-10-01

    Full Text Available Trait-based microbial models show clear promise as tools to represent the diversity and activity of microorganisms across ecosystem gradients. These models parameterize specific traits that determine the relative fitness of an ‘organism’ in a given environment, and represent the complexity of biological systems across temporal and spatial scales. In this study we introduce a microbial community trait-based modeling framework (MicroTrait focused on nitrification (MicroTrait-N that represents the ammonia-oxidizing bacteria (AOB and ammonia-oxidizing archaea (AOA and nitrite oxidizing bacteria (NOB using traits related to enzyme kinetics and physiological properties. We used this model to predict nitrifier diversity, ammonia (NH3 oxidation rates and nitrous oxide (N2O production across pH, temperature and substrate gradients. Predicted nitrifier diversity was predominantly determined by temperature and substrate availability, the latter was strongly influenced by pH. The model predicted that transient N2O production rates are maximized by a decoupling of the AOB and NOB communities, resulting in an accumulation and detoxification of nitrite to N2O by AOB. However, cumulative N2O production (over six month simulations is maximized in a system where the relationship between AOB and NOB is maintained. When the reactions uncouple, the AOB become unstable and biomass declines rapidly, resulting in decreased NH3 oxidation and N2O production. We evaluated this model against site level chemical datasets from the interior of Alaska and accurately simulated NH3 oxidation rates and the relative ratio of AOA:AOB biomass. The predicted community structure and activity indicate (a parameterization of a small number of traits may be sufficient to broadly characterize nitrifying community structure and (b changing decadal trends in climate and edaphic conditions could impact nitrification rates in ways that are not captured by extant biogeochemical models.

  12. A Matrix-Based Structure for Vario-Scale Vector Representation over a Wide Range of Map Scales : The Case of River Network Data

    NARCIS (Netherlands)

    Huang, L.; Ai, Tinghua; van Oosterom, P.J.M.; Yan, Xiongfeng; Yang, Min

    2017-01-01

    The representation of vector data at variable scales has been widely applied in geographic information systems and map-based services. When the scale changes across a wide range, a complex generalization that involves multiple operations is required to transform the data. To present such complex

  13. Design based action research in the world of robot technology and learning

    DEFF Research Database (Denmark)

    Majgaard, Gunver

    2010-01-01

    Why is design based action research method important in the world of robot technology and learning? The article explores how action research and interaction-driven design can be used in development of educational robot technological tools. The actual case is the development of “Fraction Battle......” which is about learning fractions in primary school. The technology is based on robot technology. An outdoor digital playground is taken into to the classroom and then redesigned. The article argues for interaction design takes precedence to technology or goal driven design for development...... of educational tools....

  14. Using listener-based perceptual features as intermediate representations in music information retrieval.

    Science.gov (United States)

    Friberg, Anders; Schoonderwaldt, Erwin; Hedblad, Anton; Fabiani, Marco; Elowsson, Anders

    2014-10-01

    The notion of perceptual features is introduced for describing general music properties based on human perception. This is an attempt at rethinking the concept of features, aiming to approach the underlying human perception mechanisms. Instead of using concepts from music theory such as tones, pitches, and chords, a set of nine features describing overall properties of the music was selected. They were chosen from qualitative measures used in psychology studies and motivated from an ecological approach. The perceptual features were rated in two listening experiments using two different data sets. They were modeled both from symbolic and audio data using different sets of computational features. Ratings of emotional expression were predicted using the perceptual features. The results indicate that (1) at least some of the perceptual features are reliable estimates; (2) emotion ratings could be predicted by a small combination of perceptual features with an explained variance from 75% to 93% for the emotional dimensions activity and valence; (3) the perceptual features could only to a limited extent be modeled using existing audio features. Results clearly indicated that a small number of dedicated features were superior to a "brute force" model using a large number of general audio features.

  15. Dynamic detection-rate-based bit allocation with genuine interval concealment for binary biometric representation.

    Science.gov (United States)

    Lim, Meng-Hui; Teoh, Andrew Beng Jin; Toh, Kar-Ann

    2013-06-01

    Biometric discretization is a key component in biometric cryptographic key generation. It converts an extracted biometric feature vector into a binary string via typical steps such as segmentation of each feature element into a number of labeled intervals, mapping of each interval-captured feature element onto a binary space, and concatenation of the resulted binary output of all feature elements into a binary string. Currently, the detection rate optimized bit allocation (DROBA) scheme is one of the most effective biometric discretization schemes in terms of its capability to assign binary bits dynamically to user-specific features with respect to their discriminability. However, we learn that DROBA suffers from potential discriminative feature misdetection and underdiscretization in its bit allocation process. This paper highlights such drawbacks and improves upon DROBA based on a novel two-stage algorithm: 1) a dynamic search method to efficiently recapture such misdetected features and to optimize the bit allocation of underdiscretized features and 2) a genuine interval concealment technique to alleviate crucial information leakage resulted from the dynamic search. Improvements in classification accuracy on two popular face data sets vindicate the feasibility of our approach compared with DROBA.

  16. Action-Based Jurisprudence: Praxeological Legal Theory in Relation to Economic Theory, Ethics, and Legal Practice

    Directory of Open Access Journals (Sweden)

    Konrad Graf

    2011-08-01

    Full Text Available Action-based legal theory is a discrete branch of praxeology and the basis of an emerging school of jurisprudence related to, but distinct from, natural law. Legal theory and economic theory share content that is part of praxeology itself: the action axiom, the a priori of argumentation, universalizable property theory, and counterfactual-deductive methodology. Praxeological property-norm justification is separate from the strictly ethical “ought” question of selecting ends in an action context. Examples of action-based jurisprudence are found in existing “Austro-libertarian” literature. Legal theory and legal practice must remain distinct and work closely together if justice is to be found in real cases. Legal theorizing was shaped in religious ethical contexts, which contributed to confused field boundaries between law and ethics. The carrot and stick influence of rulers on theorists has distorted conventional economics and jurisprudence in particular directions over the course of centuries. An action-based approach is relatively immune to such sources of distortion in its methods and conclusions, but has tended historically to be marginalized from conventional institutions for this same reason.

  17. Representation of physiological drought at ecosystem level based on model and eddy covariance measurements

    Science.gov (United States)

    Zhang, Y.; Novick, K. A.; Song, C.; Zhang, Q.; Hwang, T.

    2017-12-01

    Drought and heat waves are expected to increase both in frequency and amplitude, exhibiting a major disturbance to global carbon and water cycles under future climate change. However, how these climate anomalies translate into physiological drought, or ecosystem moisture stress are still not clear, especially under the co-limitations from soil moisture supply and atmospheric demand for water. In this study, we characterized the ecosystem-level moisture stress in a deciduous forest in the southeastern United States using the Coupled Carbon and Water (CCW) model and in-situ eddy covariance measurements. Physiologically, vapor pressure deficit (VPD) as an atmospheric water demand indicator largely controls the openness of leaf stomata, and regulates atmospheric carbon and water exchanges during periods of hydrological stress. Here, we tested three forms of VPD-related moisture scalars, i.e. exponent (K2), hyperbola (K3), and logarithm (K4) to quantify the sensitivity of light-use efficiency to VPD along different soil moisture conditions. The sensitivity indicators of K values were calibrated based on the framework of CCW using Monte Carlo simulations on the hourly scale, in which VPD and soil water content (SWC) are largely decoupled and the full carbon and water exchanging information are held. We found that three K values show similar performances in the predictions of ecosystem-level photosynthesis and transpiration after calibration. However, all K values show consistent gradient changes along SWC, indicating that this deciduous forest is less responsive to VPD as soil moisture decreases, a phenomena of isohydricity in which plants tend to close stomata to keep the leaf water potential constant and reduce the risk of hydraulic failure. Our study suggests that accounting for such isohydric information, or spectrum of moisture stress along different soil moisture conditions in models can significantly improve our ability to predict ecosystem responses to future

  18. Developing a vision and strategic action plan for future community-based residency training.

    Science.gov (United States)

    Skelton, Jann B; Owen, James A

    2016-01-01

    The Community Pharmacy Residency Program (CPRP) Planning Committee convened to develop a vision and a strategic action plan for the advancement of community pharmacy residency training. Aligned with the profession's efforts to achieve provider status and expand access to care, the Future Vision and Action Plan for Community-based Residency Training will provide guidance, direction, and a strategic action plan for community-based residency training to ensure that the future needs of community-based pharmacist practitioners are met. National thought leaders, selected because of their leadership in pharmacy practice, academia, and residency training, served on the planning committee. The committee conducted a series of conference calls and an in-person strategic planning meeting held on January 13-14, 2015. Outcomes from the discussions were supplemented with related information from the literature. Results of a survey of CPRP directors and preceptors also informed the planning process. The vision and strategic action plan for community-based residency training is intended to advance training to meet the emerging needs of patients in communities that are served by the pharmacy profession. The group anticipated the advanced skills required of pharmacists serving as community-based pharmacist practitioners and the likely education, training and competencies required by future residency graduates in order to deliver these services. The vision reflects a transformation of community residency training, from CPRPs to community-based residency training, and embodies the concept that residency training should be primarily focused on training the individual pharmacist practitioner based on the needs of patients served within the community, and not on the physical location where pharmacy services are provided. The development of a vision statement, core values statements, and strategic action plan will provide support, guidance, and direction to the profession of pharmacy to

  19. Posture-based processing in visual short-term memory for actions.

    Science.gov (United States)

    Vicary, Staci A; Stevens, Catherine J

    2014-01-01

    Visual perception of human action involves both form and motion processing, which may rely on partially dissociable neural networks. If form and motion are dissociable during visual perception, then they may also be dissociable during their retention in visual short-term memory (VSTM). To elicit form-plus-motion and form-only processing of dance-like actions, individual action frames can be presented in the correct or incorrect order. The former appears coherent and should elicit action perception, engaging both form and motion pathways, whereas the latter appears incoherent and should elicit posture perception, engaging form pathways alone. It was hypothesized that, if form and motion are dissociable in VSTM, then recognition of static body posture should be better after viewing incoherent than after viewing coherent actions. However, as VSTM is capacity limited, posture-based encoding of actions may be ineffective with increased number of items or frames. Using a behavioural change detection task, recognition of a single test posture was significantly more likely after studying incoherent than after studying coherent stimuli. However, this effect only occurred for spans of two (but not three) items and for stimuli with five (but not nine) frames. As in perception, posture and motion are dissociable in VSTM.

  20. 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…

  1. 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.

  2. INTERNET BANKING ACCEPTANCE IN MALAYSIA BASED ON THE THEORY OF REASONED ACTION

    Directory of Open Access Journals (Sweden)

    J Michael Pearson

    2008-09-01

    Full Text Available ABSTRACT The theory of reasoned action originally introduced in the field of Social Psychology has been widely used to explain individuals’ behaviour. The theory postulates that individuals’ behaviour is influenced by their attitude and subjective norm. The purpose of this study was to determine factors that influence an individual’s intention to use a technology based on the theory of reasoned action. We used Internet banking as the target technology and Malaysian subjects as the sampling frame. A principal component analysis was used to validate the constructs and multiple regressions were used to analyze the data. As expected, the results supported the theory’s proposition as that an individuals’ behavioural intention to use Internet banking is influenced by their attitude and subjective norm. Based on the findings, theoretical and practical implications were offered. Keywords: theory of reasoned action, Internet banking, technology acceptance

  3. A reward optimization method based on action subrewards in hierarchical reinforcement learning.

    Science.gov (United States)

    Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming

    2014-01-01

    Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.

  4. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation

    Directory of Open Access Journals (Sweden)

    An Gary

    2008-05-01

    Full Text Available Abstract Background One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. Results and Discussion ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems Conclusion A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior

  5. Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

    Science.gov (United States)

    An, Gary

    2008-05-27

    One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents

  6. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations

    Directory of Open Access Journals (Sweden)

    Jian Ou

    2017-03-01

    Full Text Available The extensive applications of multi-function radars (MFRs have presented a great challenge to the technologies of radar countermeasures (RCMs and electronic intelligence (ELINT. The recently proposed cognitive electronic warfare (CEW provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR. With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

  7. A Slicing Tree Representation and QCP-Model-Based Heuristic Algorithm for the Unequal-Area Block Facility Layout Problem

    Directory of Open Access Journals (Sweden)

    Mei-Shiang Chang

    2013-01-01

    Full Text Available The facility layout problem is a typical combinational optimization problem. In this research, a slicing tree representation and a quadratically constrained program model are combined with harmony search to develop a heuristic method for solving the unequal-area block layout problem. Because of characteristics of slicing tree structure, we propose a regional structure of harmony memory to memorize facility layout solutions and two kinds of harmony improvisation to enhance global search ability of the proposed heuristic method. The proposed harmony search based heuristic is tested on 10 well-known unequal-area facility layout problems from the literature. The results are compared with the previously best-known solutions obtained by genetic algorithm, tabu search, and ant system as well as exact methods. For problems O7, O9, vC10Ra, M11*, and Nug12, new best solutions are found. For other problems, the proposed approach can find solutions that are very similar to previous best-known solutions.

  8. Ionosonde-based indices for improved representation of solar cycle variation in the International Reference Ionosphere model

    Science.gov (United States)

    Brown, Steven; Bilitza, Dieter; Yiǧit, Erdal

    2018-06-01

    A new monthly ionospheric index, IGNS, is presented to improve the representation of the solar cycle variation of the ionospheric F2 peak plasma frequency, foF2. IGNS is calculated using a methodology similar to the construction of the "global effective sunspot number", IG, given by Liu et al. (1983) but selects ionosonde observations based on hemispheres. We incorporated the updated index into the International Reference Ionosphere (IRI) model and compared the foF2 model predictions with global ionospheric observations. We also investigated the influence of the underlying foF2 model on the IG index. IRI has two options for foF2 specification, the CCIR-66 and URSI-88 foF2 models. For the first time, we have calculated IG using URSI-88 and assessed the impact on model predictions. Through a retrospective model-data comparison, results show that the inclusion of the new monthly IGNS index in place of the current 12-month smoothed IG index reduce the foF2 model prediction errors by nearly a factor of two. These results apply to both day-time and nightime predictions. This is due to an overall improved prediction of foF2 seasonal and solar cycle variations in the different hemispheres.

  9. Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

    Science.gov (United States)

    Ou, Jian; Chen, Yongguang; Zhao, Feng; Liu, Jin; Xiao, Shunping

    2017-03-19

    The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.

  10. A randomized trial of computer-based communications using imagery and text information to alter representations of heart disease risk and motivate protective behaviour.

    Science.gov (United States)

    Lee, Tarryn J; Cameron, Linda D; Wünsche, Burkhard; Stevens, Carey

    2011-02-01

    Advances in web-based animation technologies provide new opportunities to develop graphic health communications for dissemination throughout communities. We developed imagery and text contents of brief, computer-based programmes about heart disease risk, with both imagery and text contents guided by the common-sense model (CSM) of self-regulation. The imagery depicts a three-dimensional, beating heart tailored to user-specific information. A 2 × 2 × 4 factorial design was used to manipulate concrete imagery (imagery vs. no imagery) and conceptual information (text vs. no text) about heart disease risk in prevention-oriented programmes and assess changes in representations and behavioural motivations from baseline to 2 days, 2 weeks, and 4 weeks post-intervention. Sedentary young adults (N= 80) were randomized to view one of four programmes: imagery plus text, imagery only, text only, or control. Participants completed measures of risk representations, worry, and physical activity and healthy diet intentions and behaviours at baseline, 2 days post-intervention (except behaviours), and 2 weeks (intentions and behaviours only) and 4 weeks later. The imagery contents increased representational beliefs and mental imagery relating to heart disease, worry, and intentions at post-intervention. Increases in sense of coherence (understanding of heart disease) and worry were sustained after 1 month. The imagery contents also increased healthy diet efforts after 2 weeks. The text contents increased beliefs about causal factors, mental images of clogged arteries, and worry at post-intervention, and increased physical activity 2 weeks later and sense of coherence 1 month later. The CSM-based programmes induced short-term changes in risk representations and behaviour motivation. The combination of CSM-based text and imagery appears to be most effective in instilling risk representations that motivate protective behaviour. ©2010 The British Psychological Society.

  11. Climate Masters of Nebraska: An Innovative Action-Based Approach for Climate Change Education

    Science.gov (United States)

    Pathak, Tapan B.; Bernadt, Tonya; Umphlett, Natalie

    2014-01-01

    Climate Masters of Nebraska is an innovative educational program that strategically trains community volunteers about climate change science and corresponding ways to reduce greenhouse gas emissions in an interactive and action-based teaching environment. As a result of the program, 91% of participants indicated that they made informed changes in…

  12. Innovative mode of action based in vitro assays for detection of marine neurotoxins

    NARCIS (Netherlands)

    Nicolas, J.A.Y.

    2015-01-01

    Innovative mode of action based in vitro assays for detection of marine neurotoxins

    J. Nicolas, P.J.M. Hendriksen, T.F.H. Bovee, I.M.C.M. Rietjens

    Marine biotoxins are naturally occurring compounds produced by particular phytoplankton species. These toxins often accumulate in

  13. Dramatic Impact of Action Research of Arts-Based Teaching on At-Risk Students

    Science.gov (United States)

    Li, Xin; Kenzy, Patty; Underwood, Lucy; Severson, Laura

    2015-01-01

    This study was presented at the American Educational Research Association 2012 conference in Vancouver, Canada. The study explored how action research of arts-based teaching (ABT) impacted at-risk students in three urban public schools in southern California, USA. ABT was defined as using arts, music, drama, and dance in teaching other subjects. A…

  14. A Graph-Based Approach to Action Scheduling in a Parallel Database System

    NARCIS (Netherlands)

    Grefen, P.W.P.J.; Apers, Peter M.G.

    Parallel database machines are meant to obtain high performance in transaction processing, both in terms of response time adn throughput. To obtain high performance, a good scheduling of the execution of the various actions in transactions is crucial. This paper describes a graph-based technique for

  15. Action Research: A Personal Epiphany and Journey with Evidence-Based Practice

    Science.gov (United States)

    Ballard, Susan D.

    2015-01-01

    The author reveals in this article that her action research journey in the land of evidence-based practice was not her own idea. She writes that she was lured by the profession's finest scholars who advocated for reflective dispositions for practitioners to improve their practice and demonstrate the school librarian's critical role in teaching and…

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

    NARCIS (Netherlands)

    Koelstra, Sander; Pantic, Maja; Patras, Ioannis (Yannis)

    2010-01-01

    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

  17. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Z.; Gao, Xin; Hoehndorf, Robert

    2018-01-01

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  18. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations

    KAUST Repository

    Smaili, Fatima Zohra

    2018-01-31

    We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

  19. A fast Na+/Ca2+-based action potential in a marine diatom.

    Directory of Open Access Journals (Sweden)

    Alison R Taylor

    Full Text Available BACKGROUND: Electrical impulses in animals play essential roles in co-ordinating an array of physiological functions including movement, secretion, environmental sensing and development. Underpinning many of these electrical signals is a fast Na+-based action potential that has been fully characterised only in cells associated with the neuromuscular systems of multicellular animals. Such rapid action potentials are thought to have evolved with the first metazoans, with cnidarians being the earliest representatives. The present study demonstrates that a unicellular protist, the marine diatom Odontella sinensis, can also generate a fast Na+/Ca2+ based action potential that has remarkably similar biophysical and pharmacological properties to invertebrates and vertebrate cardiac and skeletal muscle cells. METHODOLOGY/PRINCIPAL FINDINGS: The kinetic, ionic and pharmacological properties of the rapid diatom action potential were examined using single electrode current and voltage clamp techniques. Overall, the characteristics of the fast diatom currents most closely resemble those of vertebrate and invertebrate muscle Na+/Ca2+ currents. CONCLUSIONS/SIGNIFICANCE: This is the first demonstration of voltage-activated Na+ channels and the capacity to generate fast Na+-based action potentials in a unicellular photosynthetic organism. The biophysical and pharmacological characteristics together with the presence of a voltage activated Na+/Ca2+ channel homologue in the recently sequenced genome of the diatom Thalassiosira pseudonana, provides direct evidence supporting the hypothesis that this rapid signalling mechanism arose in ancestral unicellular eukaryotes and has been retained in at least two phylogenetically distant lineages of eukaryotes; opisthokonts and the stramenopiles. The functional role of the fast animal-like action potential in diatoms remains to be elucidated but is likely involved in rapid environmental sensing of these widespread and

  20. Investigating the dental toolkit of primates based on food mechanical properties: Feeding action does matter.

    Science.gov (United States)

    Thiery, Ghislain; Guy, Franck; Lazzari, Vincent

    2017-06-01

    Although conveying an indisputable morphological and behavioral signal, traditional dietary categories such as frugivorous or folivorous tend to group a wide range of food mechanical properties together. Because food/tooth interactions are mostly mechanical, it seems relevant to investigate the dental morphology of primates based on mechanical categories. However, existing mechanical categories classify food by its properties but cannot be used as factors to classify primate dietary habits. This comes from the fact that one primate species might be adapted to a wide range of food mechanical properties. To tackle this issue, what follows is an original framework based on action-related categories. The proposal here is to classify extant primates based on the range of food mechanical properties they can process through one given action. The resulting categories can be used as factors to investigate the dental tools available to primates. Furthermore, cracking, grinding, and shearing categories assigned depending on the hardness and the toughness of food are shown to be supported by morphological data (3D relative enamel thickness) and topographic data (relief index, occlusal complexity, and Dirichlet normal energy). Inferring food mechanical properties from dental morphology is especially relevant for the study of extinct primates, which are mainly documented by dental remains. Hence, we use action-related categories to investigate the molar morphology of an extinct colobine monkey Mesopithecus pentelicus from the Miocene of Pikermi, Greece. Action-related categories show contrasting results compared with classical categories and give us new insights into the dietary adaptations of this extinct primate. Finally, we provide some possible directions for future research aiming to test action-related categories. In particular, we suggest acquiring more data on mechanically challenging fallback foods and advocate the use of other food mechanical properties such as

  1. The semantic representation of event information depends on the cue modality: an instance of meaning-based retrieval.

    Science.gov (United States)

    Karlsson, Kristina; Sikström, Sverker; Willander, Johan

    2013-01-01

    The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues.

  2. The semantic representation of event information depends on the cue modality: an instance of meaning-based retrieval.

    Directory of Open Access Journals (Sweden)

    Kristina Karlsson

    Full Text Available The semantic content, or the meaning, is the essence of autobiographical memories. In comparison to previous research, which has mainly focused on the phenomenological experience and the age distribution of retrieved events, the present study provides a novel view on the retrieval of event information by quantifying the information as semantic representations. We investigated the semantic representation of sensory cued autobiographical events and studied the modality hierarchy within the multimodal retrieval cues. The experiment comprised a cued recall task, where the participants were presented with visual, auditory, olfactory or multimodal retrieval cues and asked to recall autobiographical events. The results indicated that the three different unimodal retrieval cues generate significantly different semantic representations. Further, the auditory and the visual modalities contributed the most to the semantic representation of the multimodally retrieved events. Finally, the semantic representation of the multimodal condition could be described as a combination of the three unimodal conditions. In conclusion, these results suggest that the meaning of the retrieved event information depends on the modality of the retrieval cues.

  3. The modeling and solution of course of action generation based on IN-DEA

    Science.gov (United States)

    Wan, Lujun; Li, Wen; Dai, Jiangbin; Huang, Aqian

    2017-08-01

    The course of action (COA) generation is the course of designing the task planning flow, which is one of the key supporting techniques while the military organization executing aerial operation. Due to the outstanding advantage of influence nets (IN), describing the causal logic between random variable, this proposal will introduce IN into the fast building mechanism of COA model. The COA generation model utilize influence nets is established. The probability propagation method is designed, which is based on influence intensity. An improved differential evolution algorithm (IDEA) is designed to solve the action policy optimized selected model. At last, the simulated result of aerial arrack campaign case show the action policy optimized selected in variety influence constants can improve the capability of cause-effect modeling, and the improved differential evolution algorithm has fine convergent and optimized capability.

  4. RESEARCH ACTION: IMPLEMENTATION ZERO BASED BUDGET (ZBB IN THE PROVIDER SERVICE LEASING EQUIPAMENTS OF CARGO HANDLING.

    Directory of Open Access Journals (Sweden)

    Levi Gimenez

    2013-06-01

    Full Text Available This article aims to present the implementation of zero-based budgeting in a rental service provider of cargo handling equipment using the action research methodology. The goal was to examine the possibility of concomitant use of this instrument in service providers in need of accurate information that enables targeting at the best result in a setting avid for quick decisions and actions. Action research was used as research method. It was concluded that it is suitable for this branch, confirming its position as a useful model for restructuring and cutting costs, improving operational and financial results, and as a factor improving organizational environment (behavioral aspects, indirectly creating value to stakeholders.

  5. Project management in mine actions using Multi-Criteria-Analysis-based decision support system

    Directory of Open Access Journals (Sweden)

    Marko Mladineo

    2014-12-01

    Full Text Available In this paper, a Web-based Decision Support System (Web DSS, that supports humanitarian demining operations and restoration of mine-contaminated areas, is presented. The financial shortage usually triggers a need for priority setting in Project Management in Mine actions. As part of the FP7 Project TIRAMISU, a specialized Web DSS has been developed to achieve a fully transparent priority setting process. It allows stakeholders and donors to actively join the decision making process using a user-friendly and intuitive Web application. The main advantage of this Web DSS is its unique way of managing a mine action project using Multi-Criteria Analysis (MCA, namely the PROMETHEE method, in order to select priorities for demining actions. The developed Web DSS allows decision makers to use several predefined scenarios (different criteria weights or to develop their own, so it allows project managers to compare different demining possibilities with ease.

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

    Science.gov (United States)

    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.

  7. Action video games and improved attentional control: Disentangling selection- and response-based processes.

    Science.gov (United States)

    Chisholm, Joseph D; Kingstone, Alan

    2015-10-01

    Research has demonstrated that experience with action video games is associated with improvements in a host of cognitive tasks. Evidence from paradigms that assess aspects of attention has suggested that action video game players (AVGPs) possess greater control over the allocation of attentional resources than do non-video-game players (NVGPs). Using a compound search task that teased apart selection- and response-based processes (Duncan, 1985), we required participants to perform an oculomotor capture task in which they made saccades to a uniquely colored target (selection-based process) and then produced a manual directional response based on information within the target (response-based process). We replicated the finding that AVGPs are less susceptible to attentional distraction and, critically, revealed that AVGPs outperform NVGPs on both selection-based and response-based processes. These results not only are consistent with the improved-attentional-control account of AVGP benefits, but they suggest that the benefit of action video game playing extends across the full breadth of attention-mediated stimulus-response processes that impact human performance.

  8. Weighted score-level feature fusion based on Dempster-Shafer evidence theory for action recognition

    Science.gov (United States)

    Zhang, Guoliang; Jia, Songmin; Li, Xiuzhi; Zhang, Xiangyin

    2018-01-01

    The majority of human action recognition methods use multifeature fusion strategy to improve the classification performance, where the contribution of different features for specific action has not been paid enough attention. We present an extendible and universal weighted score-level feature fusion method using the Dempster-Shafer (DS) evidence theory based on the pipeline of bag-of-visual-words. First, the partially distinctive samples in the training set are selected to construct the validation set. Then, local spatiotemporal features and pose features are extracted from these samples to obtain evidence information. The DS evidence theory and the proposed rule of survival of the fittest are employed to achieve evidence combination and calculate optimal weight vectors of every feature type belonging to each action class. Finally, the recognition results are deduced via the weighted summation strategy. The performance of the established recognition framework is evaluated on Penn Action dataset and a subset of the joint-annotated human metabolome database (sub-JHMDB). The experiment results demonstrate that the proposed feature fusion method can adequately exploit the complementarity among multiple features and improve upon most of the state-of-the-art algorithms on Penn Action and sub-JHMDB datasets.

  9. Place-based and data-rich citizen science as a precursor for conservation action.

    Science.gov (United States)

    Haywood, Benjamin K; Parrish, Julia K; Dolliver, Jane

    2016-06-01

    Environmental education strategies have customarily placed substantial focus on enhancing ecological knowledge and literacy with the hope that, upon discovering relevant facts and concepts, participants will be better equipped to process and dissect environmental issues and, therefore, make more informed decisions. The assumption is that informed citizens will become active citizens--enthusiastically lobbying for, and participating in, conservation-oriented action. We surveyed and interviewed and used performance data from 432 participants in the Coastal Observation and Seabird Survey Team (COASST), a scientifically rigorous citizen science program, to explore measurable change in and links between understanding and action. We found that participation in rigorous citizen science was associated with significant increases in participant knowledge and skills; a greater connection to place and, secondarily, to community; and an increasing awareness of the relative impact of anthropogenic activities on local ecosystems specifically through increasing scientific understanding of the ecosystem and factors affecting it. Our results suggest that a place-based, data-rich experience linked explicitly to local, regional, and global issues can lead to measurable change in individual and collective action, expressed in our case study principally through participation in citizen science and community action and communication of program results to personal acquaintances and elected officials. We propose the following tenets of conservation literacy based on emergent themes and the connections between them explicit in our data: place-based learning creates personal meaning making; individual experience nested within collective (i.e., program-wide) experience facilitates an understanding of the ecosystem process and function at local and regional scales; and science-based meaning making creates informed concern (i.e., the ability to discern both natural and anthropogenic forcing

  10. [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

  11. Acquiring Knowledge in Learning Concepts from Electrical Circuits: The Use of Multiple Representations in Technology-Based Learning Environments

    Directory of Open Access Journals (Sweden)

    Abdeljalil Métioui

    2012-04-01

    Full Text Available The constructivists approach on the conception of relative software of modelling to training and teaching of the concepts of current and voltage requires appraisal of several disciplinary fields in order to provide to the learners a training adapted to their representations. Thus, this approach requires the researchers to have adequate knowledge or skills in data processing, didactics and science content. In this regard, several researches underline that the acquisition of basic concepts that span a field of a given knowledge, must take into account the student and the scientific representations. The present research appears in this perspective, and aims to present the interactive computer environments that take into account the students (secondary and college and scientific representations related to simple electric circuits. These computer environments will help the students to analyze the functions of the electric circuits adequately.

  12. Attention and Representational Momentum

    OpenAIRE

    Hayes, Amy; Freyd, Jennifer J

    1995-01-01

    Representational momentum, the tendency for memory to be distorted in the direction of an implied transformation, suggests that dynamics are an intrinsic part of perceptual representations. We examined the effect of attention on dynamic representation by testing for representational momentum under conditions of distraction. Forward memory shifts increase when attention is divided. Attention may be involved in halting but not in maintaining dynamic representations.

  13. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation

    Directory of Open Access Journals (Sweden)

    Chan-Uk Yeom

    2017-10-01

    Full Text Available This paper discusses short-term electricity-load forecasting using an extreme learning machine (ELM with automatic knowledge representation from a given input-output data set. For this purpose, we use a Takagi-Sugeno-Kang (TSK-based ELM to develop a systematic approach to generating if-then rules, while the conventional ELM operates without knowledge information. The TSK-ELM design includes a two-phase development. First, we generate an initial random-partition matrix and estimate cluster centers for random clustering. The obtained cluster centers are used to determine the premise parameters of fuzzy if-then rules. Next, the linear weights of the TSK fuzzy type are estimated using the least squares estimate (LSE method. These linear weights are used as the consequent parameters in the TSK-ELM design. The experiments were performed on short-term electricity-load data for forecasting. The electricity-load data were used to forecast hourly day-ahead loads given temperature forecasts; holiday information; and historical loads from the New England ISO. In order to quantify the performance of the forecaster, we use metrics and statistical characteristics such as root mean squared error (RMSE as well as mean absolute error (MAE, mean absolute percent error (MAPE, and R-squared, respectively. The experimental results revealed that the proposed method showed good performance when compared with a conventional ELM with four activation functions such sigmoid, sine, radial basis function, and rectified linear unit (ReLU. It possessed superior prediction performance and knowledge information and a small number of rules.

  14. Integration of laboratory bioassays into the risk-based corrective action process

    International Nuclear Information System (INIS)

    Edwards, D.; Messina, F.; Clark, J.

    1995-01-01

    Recent data generated by the Gas Research Institute (GRI) and others indicate that residual hydrocarbon may be bound/sequestered in soil such that it is unavailable for microbial degradation, and thus possibly not bioavailable to human/ecological receptors. A reduction in bioavailability would directly equate to reduced exposure and, therefore, potentially less-conservative risk-based cleanup soil goals. Laboratory bioassays which measure bioavailability/toxicity can be cost-effectively integrated into the risk-based corrective action process. However, in order to maximize the cost-effective application of bioassays several site-specific parameters should be addressed up front. This paper discusses (1) the evaluation of parameters impacting the application of bioassays to soils contaminated with metals and/or petroleum hydrocarbons and (2) the cost-effective integration of bioassays into a tiered ASTM type framework for risk-based corrective action

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

    Science.gov (United States)

    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.

  16. Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks

    Science.gov (United States)

    Liu, Jun; Wang, Gang; Duan, Ling-Yu; Abdiyeva, Kamila; Kot, Alex C.

    2018-04-01

    Human action recognition in 3D skeleton sequences has attracted a lot of research attention. Recently, Long Short-Term Memory (LSTM) networks have shown promising performance in this task due to their strengths in modeling the dependencies and dynamics in sequential data. As not all skeletal joints are informative for action recognition, and the irrelevant joints often bring noise which can degrade the performance, we need to pay more attention to the informative ones. However, the original LSTM network does not have explicit attention ability. In this paper, we propose a new class of LSTM network, Global Context-Aware Attention LSTM (GCA-LSTM), for skeleton based action recognition. This network is capable of selectively focusing on the informative joints in each frame of each skeleton sequence by using a global context memory cell. To further improve the attention capability of our network, we also introduce a recurrent attention mechanism, with which the attention performance of the network can be enhanced progressively. Moreover, we propose a stepwise training scheme in order to train our network effectively. Our approach achieves state-of-the-art performance on five challenging benchmark datasets for skeleton based action recognition.

  17. 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.

  18. An Ontology-Based Approach to Enable Knowledge Representation and Reasoning in Worker–Cobot Agile Manufacturing

    Directory of Open Access Journals (Sweden)

    Ahmed R. Sadik

    2017-11-01

    accomplish the cooperative manufacturing concept, a proper approach is required to describe the shared environment between the worker and the cobot. The cooperative manufacturing shared environment includes the cobot, the co-worker, and other production components such as the product itself. Furthermore, the whole cooperative manufacturing system components need to communicate and share their knowledge, to reason and process the shared information, which eventually gives the control solution the capability of obtaining collective manufacturing decisions. Putting into consideration that the control solution should also provide a natural language which is human readable and in the same time can be understood by the machine (i.e., the cobot. Accordingly, a distributed control solution which combines an ontology-based Multi-Agent System (MAS and a Business Rule Management System (BRMS is proposed, in order to solve the mentioned challenges in the cooperative manufacturing, which are: manufacturing knowledge representation, sharing, and reasoning.

  19. 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

  20. Corticostriatal circuit mechanisms of value-based action selection: Implementation of reinforcement learning algorithms and beyond.

    Science.gov (United States)

    Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

    2016-09-15

    Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. Copyright © 2016. Published by Elsevier B.V.

  1. Data base management for the Remedial Action Program at Oak Ridge National Laboratory

    International Nuclear Information System (INIS)

    Voorhees, L.D.; Cushman, R.M.; Faulkner, M.A.; Horwedel, B.M.

    1986-08-01

    The Oak Ridge National Laboratory's (ORNL's) Remedial Action Program was established to provide appropriate corrective measures at over 140 sites that were contaminated with radioactive and/or hazardous chemical wastes. To achieve this goal, numerous and varied studies are being conducted which will result in the collection of an unprecedented amount of data for the ORNL site. To manage such data effectively and efficiently, a computerized data base is being developed. The data base provides a unified repository for all data generated within the Remedial Action Program, to allow for necessary storage, manipulation, analyses, assessment, display, and report generation. Data base management for the Remedial Action Program is documented in this report by: (1) defining the organization of the data management staff and the services provided; (2) describing the design of the data base, including its management system, organization, and applications; (3) providing examples of the current and anticipated tasks; and (4) discussing quality assurance measures implemented to control the accuracy of the data entries and the security of the data

  2. Teaching Problem Solving to Students Receiving Tiered Interventions Using the Concrete-Representational-Abstract Sequence and Schema-Based Instruction

    Science.gov (United States)

    Flores, Margaret M.; Hinton, Vanessa M.; Burton, Megan E.

    2016-01-01

    Mathematical word problems are the most common form of mathematics problem solving implemented in K-12 schools. Identifying key words is a frequent strategy taught in classrooms in which students struggle with problem solving and show low success rates in mathematics. Researchers show that using the concrete-representational-abstract (CRA)…

  3. Representations for the decay parameter of a birth-death process based on the Courant-Fischer theorem

    NARCIS (Netherlands)

    van Doorn, Erik A.

    2015-01-01

    We study the decay parameter (the rate of convergence of the transition probabilities) of a birth-death process on $\\{0,1,...\\}$, which we allow to evanesce by escape, via state 0, to an absorbing state -1. Our main results are representations for the decay parameter under four different scenarios,

  4. Representations for the decay parameter of a birth-death process based on the Courant-Fischer Theorem

    NARCIS (Netherlands)

    van Doorn, Erik A.

    We study the decay parameter (the rate of convergence of the transition probabilities) of a birth-death process on $\\{0,1,...\\}$, which we allow to evanesce by escape, via state 0, to an absorbing state -1. Our main results are representations for the decay parameter under four different scenarios,

  5. 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).

  6. 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

  7. 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

  8. A Demonstration of Evidence-Based Action Research Using Information Dashboard in Introductory Programming Education

    OpenAIRE

    Matsuzawa , Yoshiaki; Tanaka , Yoshiki; Kitani , Tomoya; Sakai , Sanshiro

    2017-01-01

    Part 3: Computer Science Education and Its Future Focus and Development; International audience; In this paper, we demonstrated an evidence-based action research in an introductory programming class with the use of an information dashboard which provides coding metrics to visualize students’ engagement of their assignments. The information dashboard was designed for teachers to improve their classroom teaching using the same coding metrics which was verified in our previous research [9]. The ...

  9. Designing Internet Learning for Novice Users -Paper Based on a Action Research Project In India

    DEFF Research Database (Denmark)

    Purushothaman, Aparna

    2012-01-01

    The paper centre on an Action Research project undertaken in India for enabling the female students empowered through Internet use. The paper will discuss the design elements of Internet training for the first time users with limited Internet access based on Blooms Digital Taxonomy of Learning...... Domains.The paper also illustrates the identity formation of students, through learning to use Internet, using wengers social theory of learning with the empirical data....

  10. Actionable gene-based classification toward precision medicine in gastric cancer

    Directory of Open Access Journals (Sweden)

    Hiroshi Ichikawa

    2017-10-01

    Full Text Available Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC. To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV infection and microsatellite instability (MSI status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7% and of 69 actionable genes in 141 GCs (68.1%. We classified the 207 GCs into four The Cancer Genome Atlas (TCGA subtypes using the genomic profiling data; EBV (N = 9, MSI (N = 17, chromosomal instability (N = 119, and genomically stable subtype (N = 62. Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32, while the others (N = 175 were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25, CDKN2A, and CDKN2B (N = 10, KRAS (N = 10, BRCA2 (N = 9, and ATM cluster (N = 12. The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene-based

  11. Human action quality evaluation based on fuzzy logic with application in underground coal mining.

    Science.gov (United States)

    Ionica, Andreea; Leba, Monica

    2015-01-01

    The work system is defined by its components, their roles and the relationships between them. Any work system gravitates around the human resource and the interdependencies between human factor and the other components of it. Researches in this field agreed that the human factor and its actions are difficult to quantify and predict. The objective of this paper is to apply a method of human actions evaluation in order to estimate possible risks and prevent possible system faults, both at human factor level and at equipment level. In order to point out the importance of the human factor influence on all the elements of the working systems we propose a fuzzy logic based methodology for quality evaluation of human actions. This methodology has a multidisciplinary character, as it gathers ideas and methods from: quality management, ergonomics, work safety and artificial intelligence. The results presented refer to a work system with a high degree of specificity, namely, underground coal mining and are valuable for human resources risk evaluation pattern. The fuzzy logic evaluation of the human actions leads to early detection of possible dangerous evolutions of the work system and alarm the persons in charge.

  12. ActionMap: A web-based software that automates loci assignments to framework maps.

    Science.gov (United States)

    Albini, Guillaume; Falque, Matthieu; Joets, Johann

    2003-07-01

    Genetic linkage computation may be a repetitive and time consuming task, especially when numerous loci are assigned to a framework map. We thus developed ActionMap, a web-based software that automates genetic mapping on a fixed framework map without adding the new markers to the map. Using this tool, hundreds of loci may be automatically assigned to the framework in a single process. ActionMap was initially developed to map numerous ESTs with a small plant mapping population and is limited to inbred lines and backcrosses. ActionMap is highly configurable and consists of Perl and PHP scripts that automate command steps for the MapMaker program. A set of web forms were designed for data import and mapping settings. Results of automatic mapping can be displayed as tables or drawings of maps and may be exported. The user may create personal access-restricted projects to store raw data, settings and mapping results. All data may be edited, updated or deleted. ActionMap may be used either online or downloaded for free (http://moulon.inra.fr/~bioinfo/).

  13. 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

  14. Data base management activities for the Remedial Action Program at ORNL: Calendar year 1988

    International Nuclear Information System (INIS)

    Voorhees, L.D.; Hook, L.A.; Gentry, M.J.; McCord, R.A.; Faulkner, M.A.; Bledsoe, J.L.; Newman, K.A.; Owen, P.T.; Rosen, A.E.

    1989-04-01

    The ORNL Remedial Action Program (RAP) was established in 1985 in response to state and federal regulations mandating corrective actions at contaminated sites. To achieve this goal, numerous and varied studies are being conducted to characterize the type and extent of contamination. Environmental data collected in support of other programs at ORNL are also of use to RAP. Collectively, these studies are generating a voluminous amount of data. A computerized Data and Information Management System (DIMS) was developed for RAP to (1) provide a centralized repository for data pertinent to RAP and (2) provide support for the investigations and assessments leading to the long-term remediation of contaminated facilities and sites. The current DIMS and its role in supporting RAP during 1988 are described. The DIMS consists of three components: (1) the Numeric Data Base, (2) the Bibliographic Data Base, and (3) the Records Control Data Base. This report addresses all three data bases, but focuses on a description of the contents of the Numeric Data Base. The types of numeric data currently available are summarized in the tables and figures. More detailed information on the contents of the RAP Numeric Data Base has been assembled in a menu-driven format on IBM PC diskettes, which are available upon request. 6 refs

  15. Patients' anticipated actions following transient ischaemic attack symptoms: a qualitative vignette-based study.

    Science.gov (United States)

    Magin, Parker; Joyce, Terry; Levi, Christopher; Lasserson, Daniel

    2017-02-03

    Transient Ischaemic Attack (TIA) requires urgent investigation and management. Urgent management reduces the risk of subsequent stroke markedly, but non-presentation or delays in patient presentation to health services have been found to compromise timely management. We aimed to explore general practice patients' anticipated responses to TIA symptoms. This was a qualitative study employing semi-structured telephone interviews. Participants were recruited from respondents in an earlier quantitative study based in Australian general practices. Maximum variation purposive sampling of patients from that study (on the basis of age, rurality, gender and previous experience of stroke/TIA) continued until thematic saturation was achieved. After initial interviews explored knowledge of TIA and potential responses, subsequent interviews further explored anticipated responses via clinical vignettes containing TIA and non-TIA symptoms. Transcribed interviews were coded independently by two researchers. Data collection and analysis were concurrent and cumulative, using a process of iterative thematic analysis and constant comparison. A schema explaining participants' anticipated actions emerged during this process and was iteratively tested in later interviews. Thirty-seven interviews were conducted and a 'spectrum of action', from watchful waiting (only responding if symptoms recurred) to summoning an ambulance immediately, was established. Intermediate actions upon the spectrum were: intending to mention the episode to a general practitioner (GP) at a routine appointment; consulting a GP non-urgently; consulting a general practitioner (GP) urgently; and attending an Emergency Department urgently. The substrate for decision-making relating to this spectrum operated via three constructs: the 'individual set' of the participant (their inherent disposition towards action in response to health matters in general), their 'discriminatory power' (the ability to discriminate TIA

  16. Developmental Changes in the Profiles of Dyscalculia: An Explanation Based on a Double Exact-and-Approximate Number Representation Model.

    Science.gov (United States)

    Noël, Marie-Pascale; Rousselle, Laurence

    2011-01-01

    Studies on developmental dyscalculia (DD) have tried to identify a basic numerical deficit that could account for this specific learning disability. The first proposition was that the number magnitude representation of these children was impaired. However, Rousselle and Noël (2007) brought data showing that this was not the case but rather that these children were impaired when processing the magnitude of symbolic numbers only. Since then, incongruent results have been published. In this paper, we will propose a developmental perspective on this issue. We will argue that the first deficit shown in DD regards the building of an exact representation of numerical value, thanks to the learning of symbolic numbers, and that the reduced acuity of the approximate number magnitude system appears only later and is secondary to the first deficit.

  17. 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

  18. Impacts of the aerodynamic force representation on the stability and performance of a galloping-based energy harvester

    Science.gov (United States)

    Javed, U.; Abdelkefi, A.

    2017-07-01

    One of the challenging tasks in the analytical modeling of galloping systems is the representation of the galloping force. In this study, the impacts of using different aerodynamic load representations on the dynamics of galloping oscillations are investigated. A distributed-parameter model is considered to determine the response of a galloping energy harvester subjected to a uniform wind speed. For the same experimental data and conditions, various polynomial expressions for the galloping force are proposed in order to determine the possible differences in the variations of the harvester's outputs as well as the type of instability. For the same experimental data of the galloping force, it is demonstrated that the choice of the coefficients of the polynomial approximation may result in a change in the type of bifurcation, the tip displacement and harvested power amplitudes. A parametric study is then performed to investigate the effects of the electrical load resistance on the harvester's performance when considering different possible representations of the aerodynamic force. It is indicated that for low and high values of the electrical resistance, there is an increase in the range of wind speeds where the response of the energy harvester is not affected. The performed analysis shows the importance of accurately representing the galloping force in order to efficiently design piezoelectric energy harvesters.

  19. Elaborated contextual framing is necessary for action-based attitude acquisition.

    Science.gov (United States)

    Laham, Simon M; Kashima, Yoshihisa; Dix, Jennifer; Wheeler, Melissa; Levis, Bianca

    2014-01-01

    Although arm flexion and extension have been implicated as conditioners of attitudes, recent work casts some doubt on the nature and strength of the coupling of these muscle contractions and stimulus evaluation. We propose that the elaborated contextual framing of flexion and extension actions is necessary for attitude acquisition. Results showed that when flexion and extension were disambiguated via elaborated contextual cues (i.e., framed as collect and discard within a foraging context), neutral stimuli processed under flexion were liked more than neutral stimuli processed under extension. However, when unelaborated framing was used (e.g., mere stimulus zooming effects), stimulus evaluation did not differ as a function of muscle contractions. These results suggest that neither arm contractions per se nor unelaborated framings are sufficient for action-based attitude acquisition, but that elaborated framings are necessary.

  20. 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.