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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

    There has been a recent interest in segmenting action sequences into   meaningful parts (action primitives) and to model actions on a   higher level based on these action primitives. Unlike previous works where action primitives are defined    a-priori and search is made for them later, we presen...

  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...

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

    Directory of Open Access Journals (Sweden)

    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.

  4. 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.

  5. 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.

  6. The role of action representations in thematic object relations.

    Directory of Open Access Journals (Sweden)

    Konstantinos eTsagkaridis

    2014-03-01

    Full Text Available Recent studies assessing the role of associative/event-based (thematic and categorical (taxonomic relations in the organization of object representations suggest that thematic relationships may influence the perceived similarity of manipulable artifacts. At the same time, evidence suggests that action knowledge is an important component of manipulable artifact representations. However, the role that action plays in processing thematic relationships between objects is unclear. In this study, we assessed healthy and left hemisphere stroke participants to explore three questions: 1. Do participants favor thematic relations involving action (Th+A, e.g., wine bottle – corkscrew, thematic relationships without action (Th-A, e.g., wine bottle – cheese, or taxonomic relationships (Tax, e.g., wine bottle – water bottle when choosing between them in an association judgment task? 2. Do the underlying constructs of event, action, and categorical relatedness implicitly determine the choices that participants make? 3. Does degraded action knowledge and/or damage to temporo-parietal cortex (a region of the brain associated with action representations reduce the influence of action on the choice task? Experiment 1 showed that explicit ratings of event, action, and categorical relatedness differentially predicted healthy participants’ choices, with action relatedness determining choices between Th+A and Th-A associations above and beyond event and categorical ratings. Experiment 2 focused more specifically on these Th+A vs. Th-A choices and demonstrated that participants with left temporo-parietal lesions, a brain region known to be involved in sensorimotor processing, were less likely than controls, and tended to be less likely than patients with lesions sparing that region, to implicitly use action knowledge in determining their choices. We conclude that action knowledge plays a critical role in processing of thematic relations for manipulable

  7. The nature of goal-directed action representations in infancy.

    Science.gov (United States)

    Sommerville, Jessica A; Upshaw, Michaela B; Loucks, Jeff

    2012-01-01

    A critical question for developmental psychologists concerns how representations in infancy are best characterized. Past and current research provides paradoxical evidence regarding the nature of early representations: in some ways, infants appear to build concrete and specific representations that guide their online perception and understanding of different events; in other ways, infants appear to possess abstract representations that support inferences regarding unseen event outcomes. Characterizing the nature of early representations across domains is a central charge for developmentalists because this task can provide important information regarding the underlying learning process or processes that drive development. Yet, little existing work has attempted to resolve this paradox by characterizing the ways in which infants' representations may have both abstract and concrete elements. The goal of this chapter is to take a close look at infants' early representations of goal-directed action in order to describe the nature of these representations. We first discuss the nature of representations of action that infants build through acting on the world and argue that these representations possess both concrete and abstract elements. On the one hand, infants appear to build representations of action that stress goal-relevant features of actions in an action- or event-specific fashion, suggesting specificity or concreteness. On the other hand, these representations are sufficiently abstract to not only drive action but also support infants' perception of others actions and to support inferences regarding unseen action outcomes. We next discuss evidence to suggest that by the end of the first year of life, infants possess increasingly abstract representations of the actions of others and use contextual cues, including linguistic statements accompanying action, to flexibly specify the level of representational specificity. We further consider the possibility that

  8. Learning Visual Representations for Perception-Action Systems

    DEFF Research Database (Denmark)

    Piater, Justus; Jodogne, Sebastien; Detry, Renaud;

    2011-01-01

    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 a......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...... perceptual states so as to reduce perceptual aliasing. This results in an adaptive discretization of the perceptual space based on the presence or absence of visual features. Its extension RLJC also handles continuous action spaces. In contrast to the minimalistic visual representations produced by RLVC...

  9. Beyond motor scheme: a supramodal distributed representation in the action-observation network.

    Science.gov (United States)

    Ricciardi, Emiliano; Handjaras, Giacomo; Bonino, Daniela; Vecchi, Tomaso; Fadiga, Luciano; Pietrini, Pietro

    2013-01-01

    The representation of actions within the action-observation network is thought to rely on a distributed functional organization. Furthermore, recent findings indicate that the action-observation network encodes not merely the observed motor act, but rather a representation that is independent from a specific sensory modality or sensory experience. In the present study, we wished to determine to what extent this distributed and 'more abstract' representation of action is truly supramodal, i.e. shares a common coding across sensory modalities. To this aim, a pattern recognition approach was employed to analyze neural responses in sighted and congenitally blind subjects during visual and/or auditory presentation of hand-made actions. Multivoxel pattern analyses-based classifiers discriminated action from non-action stimuli across sensory conditions (visual and auditory) and experimental groups (blind and sighted). Moreover, these classifiers labeled as 'action' the pattern of neural responses evoked during actual motor execution. Interestingly, discriminative information for the action/non action classification was located in a bilateral, but left-prevalent, network that strongly overlaps with brain regions known to form the action-observation network and the human mirror system. The ability to identify action features with a multivoxel pattern analyses-based classifier in both sighted and blind individuals and independently from the sensory modality conveying the stimuli clearly supports the hypothesis of a supramodal, distributed functional representation of actions, mainly within the action-observation network.

  10. Beyond motor scheme: a supramodal distributed representation in the action-observation network.

    Directory of Open Access Journals (Sweden)

    Emiliano Ricciardi

    Full Text Available The representation of actions within the action-observation network is thought to rely on a distributed functional organization. Furthermore, recent findings indicate that the action-observation network encodes not merely the observed motor act, but rather a representation that is independent from a specific sensory modality or sensory experience. In the present study, we wished to determine to what extent this distributed and 'more abstract' representation of action is truly supramodal, i.e. shares a common coding across sensory modalities. To this aim, a pattern recognition approach was employed to analyze neural responses in sighted and congenitally blind subjects during visual and/or auditory presentation of hand-made actions. Multivoxel pattern analyses-based classifiers discriminated action from non-action stimuli across sensory conditions (visual and auditory and experimental groups (blind and sighted. Moreover, these classifiers labeled as 'action' the pattern of neural responses evoked during actual motor execution. Interestingly, discriminative information for the action/non action classification was located in a bilateral, but left-prevalent, network that strongly overlaps with brain regions known to form the action-observation network and the human mirror system. The ability to identify action features with a multivoxel pattern analyses-based classifier in both sighted and blind individuals and independently from the sensory modality conveying the stimuli clearly supports the hypothesis of a supramodal, distributed functional representation of actions, mainly within the action-observation network.

  11. Effective QED Actions Representations, Gauge Invariance, Anomalies and Mass Expansions

    CERN Document Server

    Deser, Stanley D; Seminara, D

    1998-01-01

    We analyze and give explicit representations for the effective abelian vector gauge field actions generated by charged fermions with particular attention to the thermal regime in odd dimensions, where spectral asymmetry can be present. We show, through $\\zeta-$function regularization, that both small and large gauge invariances are preserved at any temperature and for any number of fermions at the usual price of anomalies: helicity/parity invariance will be lost in even/odd dimensions, and in the latter even at zero mass. Gauge invariance dictates a very general ``Fourier'' representation of the action in terms of the holonomies that carry the novel, large gauge invariant, information. We show that large (unlike small) transformations and hence their Ward identities, are not perturbative order-preserving, and clarify the role of (properly redefined) Chern-Simons terms in this context. From a powerful representation of the action in terms of massless heat kernels, we are able to obtain rigorous gauge invariant...

  12. Decoding Concrete and Abstract Action Representations During Explicit and Implicit Conceptual Processing.

    Science.gov (United States)

    Wurm, Moritz F; Ariani, Giacomo; Greenlee, Mark W; Lingnau, Angelika

    2016-08-01

    Action understanding requires a many-to-one mapping of perceived input onto abstract representations that generalize across concrete features. It is debated whether such abstract action concepts are encoded in ventral premotor cortex (PMv; motor hypothesis) or, alternatively, are represented in lateral occipitotemporal cortex (LOTC; cognitive hypothesis). We used fMRI-based multivoxel pattern analysis to decode observed actions at concrete and abstract, object-independent levels of representation. Participants observed videos of 2 actions involving 2 different objects, using either an explicit or implicit task with respect to conceptual action processing. We decoded concrete action representations by training and testing a classifier to discriminate between actions within each object category. To identify abstract action representations, we trained the classifier to discriminate actions in one object and tested the classifier on actions performed on the other object, and vice versa. Region-of-interest and searchlight analyses revealed decoding in LOTC at both concrete and abstract levels during both tasks, whereas decoding in PMv was restricted to the concrete level during the explicit task. In right inferior parietal cortex, decoding was significant for the abstract level during the explicit task. Our findings are incompatible with the motor hypothesis, but support the cognitive hypothesis of action understanding.

  13. Representation of action in Parkinson's disease: imagining, observing, and naming actions.

    Science.gov (United States)

    Poliakoff, Ellen

    2013-09-01

    People with Parkinson's disease (PD) exhibit slowed movements and difficulty in initiating movements. This review addresses the issue of whether or not cognitive representations of actions in PD are affected, alongside these motor problems. In healthy people, the motor system can be involved in tasks such as observing a graspable object or another person's action, or imagining and naming actions, in the absence of overt movement. As described in this review, the fact that the slowed real movements exhibited by PD patients are coupled with slower motor imagery and verb processing provides additional evidence for the involvement of the motor system in these processes. On the other hand, PD patients can still engage in motor imagery and action observation to some extent, which is encouraging for the use of these processes in rehabilitation. Findings across the different domains of action-representation reveal several important factors. First, the nature of action is critical: patients' performance in observation and naming tasks is influenced by whether or not the action is in their repertoire and by the extent of motion required to execute the action. Second, people with PD may use alternative or compensatory mechanisms to represent actions, such as relying more on a third-person perspective or a visual strategy. Third, people with PD show a lack of specificity, responding as strongly to stimuli related and unrelated to actions. Investigating action-representation in PD has implications for our understanding of both the symptoms of PD and the cognitive representation of actions in the healthy system.

  14. 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...

  15. Cognitive representation of human action: theory, applications, and perspectives

    Directory of Open Access Journals (Sweden)

    Christian eSeegelke

    2016-02-01

    Full Text Available In this perspective article, we propose a cognitive architecture model of human action that stresses the importance of cognitive representations stored in long-term memory (LTM as reference structures underlying and guiding voluntary motor performance. We introduce an experimental approach to ascertain cognitive representation structures, and provide evidence from a variety of different studies, ranging from basic research in manual action to application-oriented research such as athlete performance and rehabilitation. As results from these studies strongly support the presence of functional links between cognitive and motor processes, we regard this approach as a suitable and valuable tool for a variety of different disciplines related to cognition and movement. We conclude this article by highlighting current advances in ongoing research projects aimed at improving interaction capabilities in technical systems, particularly for rehabilitation and everyday support of the elderly, and outline future research directions.

  16. Young children's agent-neutral representations of action roles.

    Science.gov (United States)

    Rakoczy, Hannes; Gräfenhain, Maria; Clüver, Annette; Dalhoff, Ann Christin Schulze; Sternkopf, Anika

    2014-12-01

    Recent developmental research has shown that young children coordinate complementary action roles with others. But what do they understand about the logical structure of such roles? Do they have an agent-neutral conception of complementary action roles, grasping that such roles can be variably filled by any two agents or even by one agent over time? Accordingly, can they make use of such representations for planning both their own and others' actions? To address these questions, 3- and 4-year-olds were introduced to an activity comprising two action roles, A and B, by seeing either two agents performing A and B collaboratively or one agent performing A and B individually. Children's flexible inferences from these demonstrations were then tested by asking them later on to plan ahead for the fulfillment of one of the roles either by themselves or by someone else. The 4-year-olds competently drew inferences in all directions, from past individual and collaborative demonstrations, when planning how they or someone else would need to fulfill the roles in the future. The 3-year-olds, in contrast, showed more restricted competence; they were capable of such inferences only when planning in the immediate present. Taken together, these results suggest that children form and use agent-neutral representations of action roles by 3 years of age and flexibly use such representations for episodic memory and future deliberation in planning their own and others' actions by 4 years of age. The findings are discussed in the broader context of the development of understanding self-other equivalence and agent-neutral frames of references.

  17. Components of Action Representations Evoked when Identifying Manipulable Objects

    Directory of Open Access Journals (Sweden)

    Daniel N Bub

    2015-02-01

    Full Text Available We examined the influence of holding planned hand actions in working memory on the time taken to visually identify objects with handles. Features of the hand actions and position of the object's handle were congruent or incongruent on two dimensions: alignment (left vs. right and orientation (horizontal vs. vertical. When an object was depicted in an upright view, subjects were slower to name it when its handle was congruent with the planned hand actions on one dimension but incongruent on the other, relative to when the object handle and actions were congruent on both or neither dimension. This pattern is consistent with many other experiments demonstrating that a cost occurs when there is partial feature overlap between a planned action and a perceived target. An opposite pattern of results was obtained when the depicted object appeared in a 90-degree rotated view (e.g., a beer mug on its side, suggesting that the functional goal associated with the object (e.g., drinking from an upright beer mug was taken into account during object perception and that this knowledge superseded the influence of the action afforded by the depicted view of the object. These results have implications for the relationship between object perception and action representations, and for the mechanisms that support the identification of rotated objects.

  18. A Knowledge Representation Model for Video—Based Animation

    Institute of Scientific and Technical Information of China (English)

    劳志强; 潘云鹤

    1998-01-01

    In this paper,a brief survey on knowledge-based animation techniques is given.Then a VideoStream-based Knowledge Representation Model(VSKRM)for Joint Objects is presented which includes the knowledge representation of :Graphic Object,Action and VideoStream.Next a general description of the UI framework of a system is given based on the VSKRM model.Finally,a conclusion is reached.

  19. Marketing actions can modulate neural representations of experienced pleasantness.

    Science.gov (United States)

    Plassmann, Hilke; O'Doherty, John; Shiv, Baba; Rangel, Antonio

    2008-01-22

    Despite the importance and pervasiveness of marketing, almost nothing is known about the neural mechanisms through which it affects decisions made by individuals. We propose that marketing actions, such as changes in the price of a product, can affect neural representations of experienced pleasantness. We tested this hypothesis by scanning human subjects using functional MRI while they tasted wines that, contrary to reality, they believed to be different and sold at different prices. Our results show that increasing the price of a wine increases subjective reports of flavor pleasantness as well as blood-oxygen-level-dependent activity in medial orbitofrontal cortex, an area that is widely thought to encode for experienced pleasantness during experiential tasks. The paper provides evidence for the ability of marketing actions to modulate neural correlates of experienced pleasantness and for the mechanisms through which the effect operates.

  20. Multilinear Biased Discriminant Analysis: A Novel Method for Facial Action Unit Representation

    CERN Document Server

    Khademi, Mahmoud; Manzuri-Shalmani, Mohammad T

    2010-01-01

    In this paper a novel efficient method for representation of facial action units by encoding an image sequence as a fourth-order tensor is presented. The multilinear tensor-based extension of the biased discriminant analysis (BDA) algorithm, called multilinear biased discriminant analysis (MBDA), is first proposed. Then, we apply the MBDA and two-dimensional BDA (2DBDA) algorithms, as the dimensionality reduction techniques, to Gabor representations and the geometric features of the input image sequence respectively. The proposed scheme can deal with the asymmetry between positive and negative samples as well as curse of dimensionality dilemma. Extensive experiments on Cohn-Kanade database show the superiority of the proposed method for representation of the subtle changes and the temporal information involved in formation of the facial expressions. As an accurate tool, this representation can be applied to many areas such as recognition of spontaneous and deliberate facial expressions, multi modal/media huma...

  1. Simulation of Virtual Maintenance Process based on Parameterized Action Representation%基于参数化动作描述的虚拟维修过程仿真

    Institute of Scientific and Technical Information of China (English)

    王丰产; 孙有朝

    2013-01-01

    Parameterized Action Representation (PAR) designed to bridge the gap between natural language instructions and the virtual agents who are to carry their action for virtual maintenance process. PAR is therefore constructed based jointly on implemented motion capabilities of virtual human or agent action for instruction interpretation. Maintenance Task Decomposition Model and Actions Database (Action-DB) is presented based on the PAR and Intelligent Virtual Maintenance Training System in Delmia environment in this paper. And a real time execution architecture controlling 3D animated virtual human or agent is proposed based on PAR model. Finally, an example is given to verify the simulation process of models and method proposed. And results show that PAR Action-DB is convenient to simulate the virtual maintenance process.%在虚拟人执行维修动作的过程中,参数化动作描述起到了虚拟人动作和自然语言维修指令之间的桥梁作用,是为了规范虚拟人执行维修任务动作.论文在参数化动作描述和智能虚拟维修训练环境的基础上,构建了维修任务分解模型和动作库;以参数化动作描述为基础,提出了用于3D虚拟人维修动作仿真的虚拟维修实时执行层次结构.最后,通过某型起落架维修任务对参数化动作和仿真架构可行性进行验证,结果表明,基于参数化动作描述描述的动作库可以很方便的进行维修过程仿真.

  2. Seduction trauma: representation, deferred action, and pathogenic development.

    Science.gov (United States)

    Blum, H P

    1996-01-01

    Seduction trauma refers to a range of phenomena currently described under the rubric of child abuse. Freud elucidated the fantasy distortion and elaboration of traumatic experience and retained the importance of actual trauma. Psychic trauma is associated with the alteration of self and object representations and ensuing new identifications, e.g., with victim and aggressor. The "deferred action" of psychic trauma is an antiquated concept and psychic trauma has immediate effects as well as far reaching developmental consequences. Prior trauma predisposes to later traumatic vulnerability and to trauma linked to phase specific unconscious conflict. The pathogenesis of child sex abuse and the enactment of oedipal incest extends before and after the oedipal phase, is often associated with other forms of abuse, and has a history of pathogenic parent-child relationship.

  3. Image-based BRDF Representation

    Directory of Open Access Journals (Sweden)

    Mihálik A.

    2015-12-01

    Full Text Available To acquire a certain level of photorealism in computer graphics, it is necessary to analyze, how the materials scatter the incident light. In this work, we propose the method to direct rendering of isotropic bidirectional reflectance function (BRDF from the small set of images. The image-based rendering is focused to synthesize as accurately as possible scenes composed of natural and artificial objects. The realistic image synthesis of BRDF data requires evaluation of radiance over the multiple directions of incident and scattered light from the surface. In our approach the images depict only the material reflectance, the shape is represented as the object geometry. We store the BRDF representation, acquired from the sample material, in a number of two-dimensional textures that contain images of spheres lit from the multiple directions. In order to render particular material, we interpolate between textures in the similar way the image morphing works. Our method allows the real-time rendering of tabulated BRDF data on low memory devices such as mobile phones.

  4. Case Based Reasoning: Case Representation Methodologies

    Directory of Open Access Journals (Sweden)

    Shaker H. El-Sappagh

    2015-11-01

    Full Text Available Case Based Reasoning (CBR is an important technique in artificial intelligence, which has been applied to various kinds of problems in a wide range of domains. Selecting case representation formalism is critical for the proper operation of the overall CBR system. In this paper, we survey and evaluate all of the existing case representation methodologies. Moreover, the case retrieval and future challenges for effective CBR are explained. Case representation methods are grouped in to knowledge-intensive approaches and traditional approaches. The first group overweight the second one. The first methods depend on ontology and enhance all CBR processes including case representation, retrieval, storage, and adaptation. By using a proposed set of qualitative metrics, the existing methods based on ontology for case representation are studied and evaluated in details. All these systems have limitations. No approach exceeds 53% of the specified metrics. The results of the survey explain the current limitations of CBR systems. It shows that ontology usage in case representation needs improvements to achieve semantic representation and semantic retrieval in CBR system.

  5. Representations of general linear groups and categorical actions of Kac-Moody algebras

    OpenAIRE

    Losev, Ivan

    2012-01-01

    This is an expanded version of the lectures given by the author on the 3rd school "Lie algebras, algebraic groups and invariant theory" in Togliatti, Russia. In these notes we explain the concept of a categorical Kac-Moody action by studying an example of the category of rational representations of a general linear group in positive characteristic. We also deal with some more advanced topics: a categorical action on the polynomial representations and crystals of categorical actions.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    Gu, Feng; Flórez-Revuelta, Francisco; Monekosso, Dorothy; Remagnino, Paolo

    2015-07-16

    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.

  8. 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.

  9. Functional Knowledge Representation Based on Problem Reduction

    Institute of Scientific and Technical Information of China (English)

    高济

    1992-01-01

    This paper proposes an approach for functional knowledge representation based on problem reuction,which represents the organization of problem-solving activities in two levels:reduction and reasoning.The former makes the functional plans for problem-solving while the latter constructs functional units, called handlers,for executing subproblems designated by these plans.This approach emphasizes that the representation of domain knowledge should be closely combined with(rather than separated from)its use,therefore provides a set of reasoning-level primitives to construct handlers and formulate the control strategies for executing them,As reduction-level primitives,handlers are used to construct handler-associative networks,which become the executable representation of problem-reduction graphs,in order to realize the problem-solving methods suited to domain features.Besides,handlers and their control slots can be used to focus the attention of knowledge acquisition and reasoning control.

  10. 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.

  11. Toward a brain-based componential semantic representation.

    Science.gov (United States)

    Binder, Jeffrey R; Conant, Lisa L; Humphries, Colin J; Fernandino, Leonardo; Simons, Stephen B; Aguilar, Mario; Desai, Rutvik H

    2016-01-01

    Componential theories of lexical semantics assume that concepts can be represented by sets of features or attributes that are in some sense primitive or basic components of meaning. The binary features used in classical category and prototype theories are problematic in that these features are themselves complex concepts, leaving open the question of what constitutes a primitive feature. The present availability of brain imaging tools has enhanced interest in how concepts are represented in brains, and accumulating evidence supports the claim that these representations are at least partly "embodied" in the perception, action, and other modal neural systems through which concepts are experienced. In this study we explore the possibility of devising a componential model of semantic representation based entirely on such functional divisions in the human brain. We propose a basic set of approximately 65 experiential attributes based on neurobiological considerations, comprising sensory, motor, spatial, temporal, affective, social, and cognitive experiences. We provide normative data on the salience of each attribute for a large set of English nouns, verbs, and adjectives, and show how these attribute vectors distinguish a priori conceptual categories and capture semantic similarity. Robust quantitative differences between concrete object categories were observed across a large number of attribute dimensions. A within- versus between-category similarity metric showed much greater separation between categories than representations derived from distributional (latent semantic) analysis of text. Cluster analyses were used to explore the similarity structure in the data independent of a priori labels, revealing several novel category distinctions. We discuss how such a representation might deal with various longstanding problems in semantic theory, such as feature selection and weighting, representation of abstract concepts, effects of context on semantic retrieval, and

  12. Latent Semantic Learning with Structured Sparse Representation for Human Action Recognition

    CERN Document Server

    Lu, Zhiwu

    2011-01-01

    This paper proposes a novel latent semantic learning method for extracting high-level features (i.e. latent semantics) from a large vocabulary of abundant mid-level features (i.e. visual keywords) with structured sparse representation, which can help to bridge the semantic gap in the challenging task of human action recognition. To discover the manifold structure of midlevel features, we develop a spectral embedding approach to latent semantic learning based on L1-graph, without the need to tune any parameter for graph construction as a key step of manifold learning. More importantly, we construct the L1-graph with structured sparse representation, which can be obtained by structured sparse coding with its structured sparsity ensured by novel L1-norm hypergraph regularization over mid-level features. In the new embedding space, we learn latent semantics automatically from abundant mid-level features through spectral clustering. The learnt latent semantics can be readily used for human action recognition with ...

  13. A shared numerical representation for action and perception.

    Science.gov (United States)

    Anobile, Giovanni; Arrighi, Roberto; Togoli, Irene; Burr, David Charles

    2016-08-09

    Humans and other species have perceptual mechanisms dedicated to estimating approximate quantity: a sense of number. Here we show a clear interaction between self-produced actions and the perceived numerosity of subsequent visual stimuli. A short period of rapid finger-tapping (without sensory feedback) caused subjects to underestimate the number of visual stimuli presented near the tapping region; and a period of slow tapping caused overestimation. The distortions occurred both for stimuli presented sequentially (series of flashes) and simultaneously (clouds of dots); both for magnitude estimation and forced-choice comparison. The adaptation was spatially selective, primarily in external, real-world coordinates. Our results sit well with studies reporting links between perception and action, showing that vision and action share mechanisms that encode numbers: a generalized number sense, which estimates the number of self-generated as well as external events.

  14. Joint Action: Mental Representations, Shared Information and General Mechanisms for Coordinating with Others

    Science.gov (United States)

    Vesper, Cordula; Abramova, Ekaterina; Bütepage, Judith; Ciardo, Francesca; Crossey, Benjamin; Effenberg, Alfred; Hristova, Dayana; Karlinsky, April; McEllin, Luke; Nijssen, Sari R. R.; Schmitz, Laura; Wahn, Basil

    2017-01-01

    In joint action, multiple people coordinate their actions to perform a task together. This often requires precise temporal and spatial coordination. How do co-actors achieve this? How do they coordinate their actions toward a shared task goal? Here, we provide an overview of the mental representations involved in joint action, discuss how co-actors share sensorimotor information and what general mechanisms support coordination with others. By deliberately extending the review to aspects such as the cultural context in which a joint action takes place, we pay tribute to the complex and variable nature of this social phenomenon. PMID:28101077

  15. Collaborative Representation based Classification for Face Recognition

    CERN Document Server

    Zhang, Lei; Feng, Xiangchu; Ma, Yi; Zhang, David

    2012-01-01

    By coding a query sample as a sparse linear combination of all training samples and then classifying it by evaluating which class leads to the minimal coding residual, sparse representation based classification (SRC) leads to interesting results for robust face recognition. It is widely believed that the l1- norm sparsity constraint on coding coefficients plays a key role in the success of SRC, while its use of all training samples to collaboratively represent the query sample is rather ignored. In this paper we discuss how SRC works, and show that the collaborative representation mechanism used in SRC is much more crucial to its success of face classification. The SRC is a special case of collaborative representation based classification (CRC), which has various instantiations by applying different norms to the coding residual and coding coefficient. More specifically, the l1 or l2 norm characterization of coding residual is related to the robustness of CRC to outlier facial pixels, while the l1 or l2 norm c...

  16. An Event Based Approach To Situational Representation

    CERN Document Server

    Ashish, Naveen; Mehrotra, Sharad; Venkatasubramanian, Nalini

    2009-01-01

    Many application domains require representing interrelated real-world activities and/or evolving physical phenomena. In the crisis response domain, for instance, one may be interested in representing the state of the unfolding crisis (e.g., forest fire), the progress of the response activities such as evacuation and traffic control, and the state of the crisis site(s). Such a situation representation can then be used to support a multitude of applications including situation monitoring, analysis, and planning. In this paper, we make a case for an event based representation of situations where events are defined to be domain-specific significant occurrences in space and time. We argue that events offer a unifying and powerful abstraction to building situational awareness applications. We identify challenges in building an Event Management System (EMS) for which traditional data and knowledge management systems prove to be limited and suggest possible directions and technologies to address the challenges.

  17. Emotional Actions Are Coded via Two Mechanisms: With and without Identity Representation

    Science.gov (United States)

    Wincenciak, Joanna; Ingham, Jennie; Jellema, Tjeerd; Barraclough, Nick E.

    2016-01-01

    Accurate perception of an individual's identity and emotion derived from their actions and behavior is essential for successful social functioning. Here we determined the role of identity in the representation of emotional whole-body actions using visual adaptation paradigms. Participants adapted to actors performing different whole-body actions in a happy and sad fashion. Following adaptation subsequent neutral actions appeared to convey the opposite emotion. We demonstrate two different emotional action aftereffects showing distinctive adaptation characteristics. For one short-lived aftereffect, adaptation to the emotion expressed by an individual resulted in biases in the perception of the expression of emotion by other individuals, indicating an identity-independent representation of emotional actions. A second, longer lasting, aftereffect was observed where adaptation to the emotion expressed by an individual resulted in longer-term biases in the perception of the expressions of emotion only by the same individual; this indicated an additional identity-dependent representation of emotional actions. Together, the presence of these two aftereffects indicates the existence of two mechanisms for coding emotional actions, only one of which takes into account the actor's identity. The results that we observe might parallel processing of emotion from face and voice. PMID:27242606

  18. Intentional action, intention in action and motor representations: Some reflections on the Revised Causal Theory and its possible link with the Cognitive Neuroscience of Action.

    Directory of Open Access Journals (Sweden)

    Amoruso, Lucía

    2011-05-01

    Full Text Available By introducing the concept of intention in action John Searle helped to solve some of the main difficulties faced by the Causal Theory of Action. Yet, his modified theory raises new issues. Given this, the main goal of this article is to review certain problems posed by Searle’s Causal Theory taking into account recent advances in the cognitive neuroscience of action. Particularly, by using the concept of motor representation.

  19. From Action Representation to Action Execution: Exploring the Links Between Cognitive and Biomechanical Levels of Motor Control

    Directory of Open Access Journals (Sweden)

    William eLand

    2013-09-01

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

  20. The role of movement representation in episodic memory for actions: A study of patients with apraxia.

    Science.gov (United States)

    Masumoto, Kouhei; Shirakawa, Masayuki; Higashiyama, Takeshi; Yokoyama, Kazumasa

    2015-01-01

    In attempting to memorize a sentence about an action, such as "Pick up the glass," performing the action (motor encoding) results in better memory performance than simply memorizing the words (verbal encoding). Such enhancement of memory is known as the enactment effect. Several theories have been proposed to explain this phenomenon using concepts such as physical motor information associated with speed, form, amplitude of movement and/or movement representations involved in movement imaging, knowledge on manipulating tools, and spatial relationships in the enactment effect. However, there have been no cognitive neuropsychological studies investigating whether the enactment effect is crucially influenced by physical motor information or movement representations. To clarify this issue, we compared healthy adult control participants with two different types of apraxia patients. One patient with left hemisphere lesions caused by cerebral infarction had a disability involving multiple movement representations. The other patient showed symptoms of corticobasal syndrome and was not able to benefit from feedback on the accuracy of her motor movements during enactment. Participants memorized action sentences via either verbal or motor encoding and responded to recall and recognition tests. Results indicated that the patient with the movement representation deficits exhibited worse memory performance than the other patient or control participants following both verbal and motor encoding. Although the enactment effect was present during recall in both patients, the effect was not observed for recognition in the patient with severe movement representation deficits. These results suggest that movement representations are involved in encoding episodic memories of action. Moreover, the role of movement representations appears to depend on the form of retrieval that is being used.

  1. Neural networks for action representation underlying automatic mimicry: A functional magnetic-resonance imaging and dynamic causal modeling study

    Directory of Open Access Journals (Sweden)

    Akihiro T Sasaki

    2012-08-01

    Full Text Available Automatic mimicry is based on the tight linkage between motor and perception action representations in which internal models play a key role. Based on the anatomical connection, we hypothesized that the direct effective connectivity from the posterior superior temporal sulcus (pSTS to the ventral premotor area (PMv formed an inverse internal model, converting visual representation into a motor plan, and that reverse connectivity formed a forward internal model, converting the motor plan into a sensory outcome of action. To test this hypothesis, we employed dynamic causal-modeling analysis with functional magnetic-resonance imaging. Twenty-four normal participants underwent a change-detection task involving two visually-presented balls that were either manually rotated by the investigator’s right hand (‘Hand’ or automatically rotated. The effective connectivity from the pSTS to the PMv was enhanced by hand observation and suppressed by execution, corresponding to the inverse model. Opposite effects were observed from the PMv to the pSTS, suggesting the forward model. Additionally, both execution and hand observation commonly enhanced the effective connectivity from the pSTS to the inferior parietal lobule (IPL, the IPL to the primary sensorimotor cortex (S/M1, the PMv to the IPL, and the PMv to the S/M1. Representation of the hand action therefore was implemented in the motor system including the S/M1. During hand observation, effective connectivity toward the pSTS was suppressed whereas that toward the PMv and S/M1 was enhanced. Thus the action-representation network acted as a dynamic feedback-control system during action observation.

  2. Active vision during action execution, observation and imagery: evidence for shared motor representations.

    Directory of Open Access Journals (Sweden)

    Sheree A McCormick

    Full Text Available The concept of shared motor representations between action execution and various covert conditions has been demonstrated through a number of psychophysiological modalities over the past two decades. Rarely, however, have researchers considered the congruence of physical, imaginary and observed movement markers in a single paradigm and never in a design where eye movement metrics are the markers. In this study, participants were required to perform a forward reach and point Fitts' Task on a digitizing tablet whilst wearing an eye movement system. Gaze metrics were used to compare behaviour congruence between action execution, action observation, and guided and unguided movement imagery conditions. The data showed that participants attended the same task-related visual cues between conditions but the strategy was different. Specifically, the number of fixations was significantly different between action execution and all covert conditions. In addition, fixation duration was congruent between action execution and action observation only, and both conditions displayed an indirect Fitts' Law effect. We therefore extend the understanding of the common motor representation by demonstrating, for the first time, common spatial eye movement metrics across simulation conditions and some specific temporal congruence for action execution and action observation. Our findings suggest that action observation may be an effective technique in supporting motor processes. The use of video as an adjunct to physical techniques may be beneficial in supporting motor planning in both performance and clinical rehabilitation environments.

  3. 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.

  4. Class-Based Affirmative Action.

    Science.gov (United States)

    Roach, Ronald

    2003-01-01

    Discusses class-based, or economic, affirmative action, touted by the Bush administration as a race-neutral alternative to race-conscious affirmative action in college admissions. Explores whether such policies will result in fewer minority admissions and considers the "fairness" of the approach. (SLD)

  5. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    Science.gov (United States)

    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.

  6. Plagiarism Detection Using Graph-Based Representation

    CERN Document Server

    Osman, Ahmed Hamza; Binwahlan, Mohammed Salem

    2010-01-01

    Plagiarism of material from the Internet is a widespread and growing problem. Several methods used to detect the plagiarism and similarity between the source document and suspected documents such as fingerprint based on character or n-gram. In this paper, we discussed a new method to detect the plagiarism based on graph representation; however, Preprocessing for each document is required such as breaking down the document into its constituent sentences. Segmentation of each sentence into separated terms and stop word removal. We build the graph by grouping each sentence terms in one node, the resulted nodes are connected to each other based on order of sentence within the document, all nodes in graph are also connected to top level node "Topic Signature". Topic signature node is formed by extracting the concepts of each sentence terms and grouping them in such node. The main advantage of the proposed method is the topic signature which is main entry for the graph is used as quick guide to the relevant nodes. ...

  7. 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....

  8. Dissociation between Semantic Representations for Motion and Action Verbs: Evidence from Patients with Left Hemisphere Lesions

    Science.gov (United States)

    Taylor, Lawrence J.; Evans, Carys; Greer, Joanna; Senior, Carl; Coventry, Kenny R.; Ietswaart, Magdalena

    2017-01-01

    This multiple single case study contrasted left hemisphere stroke patients (N = 6) to healthy age-matched control participants (N = 15) on their understanding of action (e.g., holding, clenching) and motion verbs (e.g., crumbling, flowing). The tasks required participants to correctly identify the matching verb or associated picture. Dissociations on action and motion verb content depending on lesion site were expected. As predicted for verbs containing an action and/or motion content, modified t-tests confirmed selective deficits in processing motion verbs in patients with lesions involving posterior parietal and lateral occipitotemporal cortex. In contrast, deficits in verbs describing motionless actions were found in patients with more anterior lesions sparing posterior parietal and lateral occipitotemporal cortex. These findings support the hypotheses that semantic representations for action and motion are behaviorally and neuro-anatomically dissociable. The findings clarify the differential and critical role of perceptual and motor regions in processing modality-specific semantic knowledge as opposed to a supportive but not necessary role. We contextualize these results within theories from both cognitive psychology and cognitive neuroscience that make claims over the role of sensory and motor information in semantic representation. PMID:28261070

  9. Mu rhythm suppression demonstrates action representation in pianists during passive listening of piano melodies.

    Science.gov (United States)

    Wu, C Carolyn; Hamm, Jeff P; Lim, Vanessa K; Kirk, Ian J

    2016-08-01

    Musicians undergo extensive training which enhances established neural links between auditory and motor areas of the brain. Long-term training develops, strengthens and enables flexibility in these connections allowing proficiency in performance. Previous research has indicated that passive listening of trained music results in the recruitment of premotor areas. It has been argued that this sound-action representation may rely on activity in mirror neuron systems and that these systems are heavily dependent on actual sensorimotor experience. Action observation studies using electroencephalography have associated changes in mu rhythm activity with the mirror neuron system in the visuomotor domain. We aimed to investigate similar effects in the audiomotor domain. We utilised a mu suppression method in our action-listening study to detect involuntary motor coactivation when pianists passively listened to piano melodies. Wavelet analysis revealed sensorimotor mu rhythm suppression while pianists listened passively to piano melodies. Thus, we show that this spectral analysis method can also be used to demonstrate that auditory stimuli can activate the human mirror neuron system when sounds are linked to actions. Mu suppression could be a useful index for further research on action representation and training-induced plasticity.

  10. Dissociation between Semantic Representations for Motion and Action Verbs: Evidence from Patients with Left Hemisphere Lesions.

    Science.gov (United States)

    Taylor, Lawrence J; Evans, Carys; Greer, Joanna; Senior, Carl; Coventry, Kenny R; Ietswaart, Magdalena

    2017-01-01

    This multiple single case study contrasted left hemisphere stroke patients (N = 6) to healthy age-matched control participants (N = 15) on their understanding of action (e.g., holding, clenching) and motion verbs (e.g., crumbling, flowing). The tasks required participants to correctly identify the matching verb or associated picture. Dissociations on action and motion verb content depending on lesion site were expected. As predicted for verbs containing an action and/or motion content, modified t-tests confirmed selective deficits in processing motion verbs in patients with lesions involving posterior parietal and lateral occipitotemporal cortex. In contrast, deficits in verbs describing motionless actions were found in patients with more anterior lesions sparing posterior parietal and lateral occipitotemporal cortex. These findings support the hypotheses that semantic representations for action and motion are behaviorally and neuro-anatomically dissociable. The findings clarify the differential and critical role of perceptual and motor regions in processing modality-specific semantic knowledge as opposed to a supportive but not necessary role. We contextualize these results within theories from both cognitive psychology and cognitive neuroscience that make claims over the role of sensory and motor information in semantic representation.

  11. 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.

  12. A new representation of acid-base disturbances

    NARCIS (Netherlands)

    M. Hekking (Marcel); E.S. Gelsema; J. Lindemans (Jan)

    1994-01-01

    textabstractThe acid-base status of intensive care patients is monitored on the basis of three quantities. The graphical representation which may be of help for the monitoring task is therefore cumbersome. The classical Siggaard-Andersen acid-base chart is such a representation, but it is only suite

  13. Space-dependent representation of objects and other's action in monkey ventral premotor grasping neurons.

    Science.gov (United States)

    Bonini, Luca; Maranesi, Monica; Livi, Alessandro; Fogassi, Leonardo; Rizzolatti, Giacomo

    2014-03-12

    The macaque ventral premotor area F5 hosts two types of visuomotor grasping neurons: "canonical" neurons, which respond to visually presented objects and underlie visuomotor transformation for grasping, and "mirror" neurons, which respond during the observation of others' action, likely playing a role in action understanding. Some previous evidence suggested that canonical and mirror neurons could be anatomically segregated in different sectors of area F5. Here we investigated the functional properties of single neurons in the hand field of area F5 using various tasks similar to those originally designed to investigate visual responses to objects and actions. By using linear multielectrode probes, we were able to simultaneously record different types of neurons and to precisely localize their cortical depth. We recorded 464 neurons, of which 243 showed visuomotor properties. Canonical and mirror neurons were often present in the same cortical sites; and, most interestingly, a set of neurons showed both canonical and mirror properties, discharging to object presentation as well as during the observation of experimenter's goal-directed acts (canonical-mirror neurons). Typically, visual responses to objects were constrained to the monkey peripersonal space, whereas action observation responses were less space-selective. Control experiments showed that space-constrained coding of objects mostly relies on an operational (action possibility) rather than metric (absolute distance) reference frame. Interestingly, canonical-mirror neurons appear to code object as target for both one's own and other's action, suggesting that they could play a role in predictive representation of others' impending actions.

  14. A shape representation for computer vision based on differential topology.

    Science.gov (United States)

    Blicher, A P

    1995-01-01

    We describe a shape representation for use in computer vision, after a brief review of shape representation and object recognition in general. Our shape representation is based on graph structures derived from level sets whose characteristics are understood from differential topology, particularly singularity theory. This leads to a representation which is both stable and whose changes under deformation are simple. The latter allows smoothing in the representation domain ('symbolic smoothing'), which in turn can be used for coarse-to-fine strategies, or as a discrete analog of scale space. Essentially the same representation applies to an object embedded in 3-dimensional space as to one in the plane, and likewise for a 3D object and its silhouette. We suggest how this can be used for recognition.

  15. 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...

  16. 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.

  17. Logging data representation based on XML

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    As an open standard of data representation, XML breathes new energy to the Web application and the network computing. The development, advantage and status of XML and some standards relating to XML are reviewed. In addition, the authors put forward a method representing logging data and using UML language to establish the conceptual and logical model of logging data; using a logging data, explain how to establish the model as well as how to use XML to display and process geology data.

  18. Revealing action representation processes in audio perception using fractal EEG analysis.

    Science.gov (United States)

    Hadjidimitriou, Stelios K; Zacharakis, Asteris I; Doulgeris, Panagiotis C; Panoulas, Konstantinos J; Hadjileontiadis, Leontios J; Panas, Stavros M

    2011-04-01

    Electroencephalogram (EEG) recordings, and especially the Mu-rhythm over the sensorimotor cortex that relates to the activation of the mirror neuron system (MNS), were acquired from two subject groups (orchestral musicians and nonmusicians), in order to explore action representation processes involved in the perception and performance of musical pieces. Two types of stimuli were used, i.e., an auditory one consisting of an excerpt of Beethoven's fifth symphony and a visual one presenting a conductor directing an orchestra performing the same excerpt of the piece. Three tasks were conducted including auditory stimulation, audiovisual stimulation, and visual stimulation only, and the acquired signals were processed using fractal [time-dependent fractal dimension (FD) estimation] and statistical analysis (analysis of variance, Mann-Whitney). Experimental results showed significant differences between the two groups while desychronization of the Mu-rhythm, which can be linked to MNS activation, was observed during all tasks for the musicians' group, as opposed to the nonmusicians' group who exhibited similar response only when the visual stimulus was present. The mobility of the conductor was also correlated to the estimated FD signals, showing significantly higher correlation for the case of musicians compared to nonmusicians' one. The present study sheds light upon the difference in action representation in auditory perception between musicians and nonmusicians and paves the way for better comprehension of the underlying mechanisms of the MNS.

  19. 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....

  20. 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.

  1. Bases for representations of quantum algebras

    Science.gov (United States)

    Atakishiyev, N. M.; Winternitz, P.

    2000-08-01

    We derive an explicit expression for the eigenfunctions and the corresponding eigenvalues of the operator [q1/4J+(q) + q-1/4J-(q)] qJ3(q)/2 in an arbitrary irreducible representation of the algebra suq(2). The general form of the intertwining operator AJ(q), which is a q-extension of the classical su(2)-operator aJ, J1aJ = aJJ3, is also found. The matrix elements of AJ(q) are expressed in terms of the dual q-Kravchuk polynomials.

  2. Scale-Dependent Representations of Relief Based on Wavelet Analysis

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Automatic generalization of geographic information is the core of multi-scale representation of spatial data,but the scale-dependent generalization methods are far from abundant because of its extreme complicacy.This paper puts forward a new consistency model about scale-dependent representations of relief based on wavelet analysis,and discusses the thresholds in the model so as to acquire the continual representations of relief with different details between scales.The model not only meets the need of automatic generalization but also is scale-dependent completely.Some practical examples are given.

  3. ONTOLOGY BASED SEMANTIC KNOWLEDGE REPRESENTATION FOR SOFTWARE RISK MANAGEMENT

    Directory of Open Access Journals (Sweden)

    C.R.Rene Robin

    2010-10-01

    Full Text Available Domain specific knowledge representation is achieved through the use of ontologies. The ontology model of software risk management is an effective approach for the intercommunion between people from teaching and learning community, the communication and interoperation among various knowledge oriented applications, and the share and reuse of the software. But the lack of formal representation tools for domain modeling results in taking liberties with conceptualization. This paper narrates an ontology based semantic knowledge representation mechanism and the architecture we proposed has been successfully implemented for the domain software riskmanagement.

  4. Grammar Based Genetic Programming Using Linear Representations

    Institute of Scientific and Technical Information of China (English)

    ZHANGHong; LUYinan; WANGFei

    2003-01-01

    In recent years,there has been a great interest in genetic programming(GP),which is used to solve many applications such as data mining,electronic engineering and pattern recognition etc.. Genetic programming paradigm as a from of adaptive learning is a functional approach to many problems that require a nonfixed representation and GP typically operates on a population of parse which usually represent computer programs whose nodes have single data type.In this paper GP using context-free grammars(CFGs) is described.This technique separates search space from solution space through a genotype to phenotype mapping.The genotypes and phenotypes of the individuals both act on different linear representations.A phenotype is postfix expression,a new method of representing which is described by making use of the definition and related features of a context-free grammar,i.e.a genotype is a variable length,linear valid genome determined by a simplifled derivation tree(SDT) generated from a context-free grammar.A CFG is used to specify how the possible solutions are created according to experiential knowledge and to direct legal crossover(ormutation)operations without any explicit reference to the process of program generation and parsing,and automatically ensuring typing and syntax correctness.Some related definitions involving genetic operators are described.Fitness evaluation is given.This technique is applied to a symbol regression problem-the identification of nonlinear dynamic characteristics of cushioning packaging.Experimental results show this method can flnd good relations between variables and is better than basic GP without a grammar.Future research on it is outlined.

  5. An object-based methodology for knowledge representation in SGML

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R.L. [Los Alamos National Lab., NM (United States)|New Mexico State Univ., Las Cruces, NM (United States); Hartley, R.T. [New Mexico State Univ., Las Cruces, NM (United States); Webster, R.B. [Los Alamos National Lab., NM (United States)

    1997-11-01

    An object-based methodology for knowledge representation and its Standard Generalized Markup Language (SGML) implementation is presented. The methodology includes class, perspective domain, and event constructs for representing knowledge within an object paradigm. The perspective construct allows for representation of knowledge from multiple and varying viewpoints. The event construct allows actual use of knowledge to be represented. The SGML implementation of the methodology facilitates usability, structured, yet flexible knowledge design, and sharing and reuse of knowledge class libraries.

  6. 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.

  7. Sparse coding based feature representation method for remote sensing images

    Science.gov (United States)

    Oguslu, Ender

    In this dissertation, we study sparse coding based feature representation method for the classification of multispectral and hyperspectral images (HSI). The existing feature representation systems based on the sparse signal model are computationally expensive, requiring to solve a convex optimization problem to learn a dictionary. A sparse coding feature representation framework for the classification of HSI is presented that alleviates the complexity of sparse coding through sub-band construction, dictionary learning, and encoding steps. In the framework, we construct the dictionary based upon the extracted sub-bands from the spectral representation of a pixel. In the encoding step, we utilize a soft threshold function to obtain sparse feature representations for HSI. Experimental results showed that a randomly selected dictionary could be as effective as a dictionary learned from optimization. The new representation usually has a very high dimensionality requiring a lot of computational resources. In addition, the spatial information of the HSI data has not been included in the representation. Thus, we modify the framework by incorporating the spatial information of the HSI pixels and reducing the dimension of the new sparse representations. The enhanced model, called sparse coding based dense feature representation (SC-DFR), is integrated with a linear support vector machine (SVM) and a composite kernels SVM (CKSVM) classifiers to discriminate different types of land cover. We evaluated the proposed algorithm on three well known HSI datasets and compared our method to four recently developed classification methods: SVM, CKSVM, simultaneous orthogonal matching pursuit (SOMP) and image fusion and recursive filtering (IFRF). The results from the experiments showed that the proposed method can achieve better overall and average classification accuracies with a much more compact representation leading to more efficient sparse models for HSI classification. To further

  8. Robust speech features representation based on computational auditory model

    Institute of Scientific and Technical Information of China (English)

    LU Xugang; JIA Chuan; DANG Jianwu

    2004-01-01

    A speech signal processing and features extracting method based on computational auditory model is proposed. The computational model is based on psychological, physiological knowledge and digital signal processing methods. In each stage of a hearing perception system, there is a corresponding computational model to simulate its function. Based on this model, speech features are extracted. In each stage, the features in different kinds of level are extracted. A further processing for primary auditory spectrum based on lateral inhibition is proposed to extract much more robust speech features. All these features can be regarded as the internal representations of speech stimulation in hearing system. The robust speech recognition experiments are conducted to test the robustness of the features. Results show that the representations based on the proposed computational auditory model are robust representations for speech signals.

  9. 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.

  10. The DTW-based representation space for seismic pattern classification

    Science.gov (United States)

    Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario

    2015-12-01

    Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.

  11. The representation of response effector and response location in episodic memory for newly acquired actions: evidence from retrieval-induced forgetting.

    Science.gov (United States)

    Reppa, Irene; Worth, E Rhian; Greville, W James; Saunders, Jo

    2013-06-01

    Information retrieval can cause forgetting for related but non-retrieved information. Such retrieval-induced forgetting (RIF) has been previously found for semantically and episodically related information. The current study used RIF to examine whether response effector and location are encoded explicitly in action memory. Participants learned unique touchscreen responses to ten novel objects. Correct actions to each object involved left-hand or right-hand pushing of one of four possible object buttons. After learning, participants practiced two of the ten object-specific sequences. Unpracticed actions could share hand only, button only, both hand and button, or neither hand nor button, with the practiced actions. Subsequent testing showed significant RIF (in retrieval accuracy and speed measures) for actions that shared hand only, button only, or both hand and button with the practiced action. The results have implications for understanding the representations mediating episodic action memory, and for the potential of RIF as a tool for elucidating feature-based representations in this and other domains.

  12. Group-based sparse representation for image restoration.

    Science.gov (United States)

    Zhang, Jian; Zhao, Debin; Gao, Wen

    2014-08-01

    Traditional patch-based sparse representation modeling of natural images usually suffer from two problems. First, it has to solve a large-scale optimization problem with high computational complexity in dictionary learning. Second, each patch is considered independently in dictionary learning and sparse coding, which ignores the relationship among patches, resulting in inaccurate sparse coding coefficients. In this paper, instead of using patch as the basic unit of sparse representation, we exploit the concept of group as the basic unit of sparse representation, which is composed of nonlocal patches with similar structures, and establish a novel sparse representation modeling of natural images, called group-based sparse representation (GSR). The proposed GSR is able to sparsely represent natural images in the domain of group, which enforces the intrinsic local sparsity and nonlocal self-similarity of images simultaneously in a unified framework. In addition, an effective self-adaptive dictionary learning method for each group with low complexity is designed, rather than dictionary learning from natural images. To make GSR tractable and robust, a split Bregman-based technique is developed to solve the proposed GSR-driven ℓ0 minimization problem for image restoration efficiently. Extensive experiments on image inpainting, image deblurring and image compressive sensing recovery manifest that the proposed GSR modeling outperforms many current state-of-the-art schemes in both peak signal-to-noise ratio and visual perception.

  13. Dictionary-Based, Clustered Sparse Representation for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Zhen-tao Qin

    2015-01-01

    Full Text Available This paper presents a new, dictionary-based method for hyperspectral image classification, which incorporates both spectral and contextual characteristics of a sample clustered to obtain a dictionary of each pixel. The resulting pixels display a common sparsity pattern in identical clustered groups. We calculated the image’s sparse coefficients using the dictionary approach, which generated the sparse representation features of the remote sensing images. The sparse coefficients are then used to classify the hyperspectral images via a linear SVM. Experiments show that our proposed method of dictionary-based, clustered sparse coefficients can create better representations of hyperspectral images, with a greater overall accuracy and a Kappa coefficient.

  14. Proposed Representation Approach Based on Description Logics Formalism

    Directory of Open Access Journals (Sweden)

    Yasser Yahiaoui

    2016-05-01

    Full Text Available The most familiar concept in Artificial intelligence is the knowledges representation. It aims to find explicit symbolization covering all semantic aspects of knowledge, and to make possible the use of this representation to produce an intelligent behavior like reasoning. The most important constraint is the usability of the representation; it’s why the structures used must be well defined to facilitate manipulation for reasoning algorithms which leads to facilitate their implementation. In this paper we propose a new approach based on the description logics formalism for the goal of simplification of description logics system implementation. This approach can reduce the complexity of reasoning Algorithm by the vectorisation of concept definition based on the subsumption hierarchy.

  15. 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.

  16. Visual Tracking Based on Extreme Learning Machine and Sparse Representation

    Directory of Open Access Journals (Sweden)

    Baoxian Wang

    2015-10-01

    Full Text Available The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM. Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker.

  17. Visual tracking based on extreme learning machine and sparse representation.

    Science.gov (United States)

    Wang, Baoxian; Tang, Linbo; Yang, Jinglin; Zhao, Baojun; Wang, Shuigen

    2015-10-22

    The existing sparse representation-based visual trackers mostly suffer from both being time consuming and having poor robustness problems. To address these issues, a novel tracking method is presented via combining sparse representation and an emerging learning technique, namely extreme learning machine (ELM). Specifically, visual tracking can be divided into two consecutive processes. Firstly, ELM is utilized to find the optimal separate hyperplane between the target observations and background ones. Thus, the trained ELM classification function is able to remove most of the candidate samples related to background contents efficiently, thereby reducing the total computational cost of the following sparse representation. Secondly, to further combine ELM and sparse representation, the resultant confidence values (i.e., probabilities to be a target) of samples on the ELM classification function are used to construct a new manifold learning constraint term of the sparse representation framework, which tends to achieve robuster results. Moreover, the accelerated proximal gradient method is used for deriving the optimal solution (in matrix form) of the constrained sparse tracking model. Additionally, the matrix form solution allows the candidate samples to be calculated in parallel, thereby leading to a higher efficiency. Experiments demonstrate the effectiveness of the proposed tracker.

  18. Explicit representation of confidence informs future value-based decisions

    DEFF Research Database (Denmark)

    Folke, Tomas; Jacobsen, Catrine; Fleming, Stephen M.;

    2016-01-01

    Humans can reflect on decisions and report variable levels of confidence. But why maintain an explicit representation of confidence for choices that have already been made and therefore cannot be undone? Here we show that an explicit representation of confidence is harnessed for subsequent changes...... of mind. Specifically, when confidence is low, participants are more likely to change their minds when the same choice is presented again, an effect that is most pronounced in participants with greater fidelity in their confidence reports. Furthermore, we show that choices reported with high confidence...... of confidence has a positive impact on the quality of future value-based decisions....

  19. The criterion of pulse reconstruction quality based on Wigner representation

    NARCIS (Netherlands)

    Yeremenko, S.; Baltuska, A.; Pshenichnikov, M.S; Wiersma, D. A.

    2000-01-01

    We propose a new criterion for the assessment of ultrashort pulse reconstruction quality. Our idea is based on the use of a two-dimensional Wigner representation of the electric field. This allows introducing a single measure to represent the quality of both phase and amplitude retrieval. The new cr

  20. Ensemble polarimetric SAR image classification based on contextual sparse representation

    Science.gov (United States)

    Zhang, Lamei; Wang, Xiao; Zou, Bin; Qiao, Zhijun

    2016-05-01

    Polarimetric SAR image interpretation has become one of the most interesting topics, in which the construction of the reasonable and effective technique of image classification is of key importance. Sparse representation represents the data using the most succinct sparse atoms of the over-complete dictionary and the advantages of sparse representation also have been confirmed in the field of PolSAR classification. However, it is not perfect, like the ordinary classifier, at different aspects. So ensemble learning is introduced to improve the issue, which makes a plurality of different learners training and obtained the integrated results by combining the individual learner to get more accurate and ideal learning results. Therefore, this paper presents a polarimetric SAR image classification method based on the ensemble learning of sparse representation to achieve the optimal classification.

  1. Signal extrapolation based on wavelet representation

    Science.gov (United States)

    Xia, Xiang-Gen; Kuo, C.-C. Jay; Zhang, Zhen

    1993-11-01

    The Papoulis-Gerchberg (PG) algorithm is well known for band-limited signal extrapolation. We consider the generalization of the PG algorithm to signals in the wavelet subspaces in this research. The uniqueness of the extrapolation for continuous-time signals is examined, and sufficient conditions on signals and wavelet bases for the generalized PG (GPG) algorithm to converge are given. We also propose a discrete GPG algorithm for discrete-time signal extrapolation, and investigate its convergence. Numerical examples are given to illustrate the performance of the discrete GPG algorithm.

  2. 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

  3. Graph-based representation for multiview image geometry.

    Science.gov (United States)

    Maugey, Thomas; Ortega, Antonio; Frossard, Pascal

    2015-05-01

    In this paper, we propose a new geometry representation method for multiview image sets. Our approach relies on graphs to describe the multiview geometry information in a compact and controllable way. The links of the graph connect pixels in different images and describe the proximity between pixels in 3D space. These connections are dependent on the geometry of the scene and provide the right amount of information that is necessary for coding and reconstructing multiple views. Our multiview image representation is very compact and adapts the transmitted geometry information as a function of the complexity of the prediction performed at the decoder side. To achieve this, our graph-based representation (GBR) carefully selects the amount of geometry information needed before coding. This is in contrast with depth coding, which directly compresses with losses the original geometry signal, thus making it difficult to quantify the impact of coding errors on geometry-based interpolation. We present the principles of this GBR and we build an efficient coding algorithm to represent it. We compare our GBR approach to classical depth compression methods and compare their respective view synthesis qualities as a function of the compactness of the geometry description. We show that GBR can achieve significant gains in geometry coding rate over depth-based schemes operating at similar quality. Experimental results demonstrate the potential of this new representation.

  4. TARGET-ORIENTED GENERIC FINGERPRINT-BASED MOLECULAR REPRESENTATION

    Directory of Open Access Journals (Sweden)

    Petr Skoda

    2014-12-01

    Full Text Available 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 greatly influencing the performance of ligand-based virtual screening is the chosen chemical compound representation. In this paper, we introduce a fragment-based representation of chemical compounds. Our representation utilizes fragments to represent a compound where each fragment is represented by its physico-chemical descriptors. The representation is highly parametrizable, especially in the area of physico-chemical descriptors selection and application. In order to test the performance of our method, we utilized an existing framework for virtual screening benchmarking. The results show that our method is comparable to the best existing approaches and on some data sets it outperforms them.

  5. 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

    2016-11-24

    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.

  6. Theatricality and representation of History: Ethics, memory and suspended action in Mayorga's dramaturgy

    Directory of Open Access Journals (Sweden)

    Ana Gorría Ferrín

    2012-06-01

    Full Text Available Reflection on the image reaches the second half of the twentieth century zenith an episode, one of whose chief representatives is to be the theoretical and literature emerged around the photographic image. The ontology of the photographic image, thus, represents a fundamental event in the critical theoretical framework and on the imagination. The notion of image and reflection on it is established that permeates not only the field of theory and practice of art but also affects the coding literature assuming a source of epistemological reflection about representation and authenticity phenomenological of this. The purpose of this paper is to show the importance of thinking about the photographic image and its practical demonstration as action in the specific case of Juan Mayorga’s drama, where the analysis of the photographic ontology is at the service of understanding not only of reality but also of history, memory and emotions through the dialectical imagination as proposed in the play El cartógrafo.

  7. The representation of syntactic action at a distance: Multidominance versus the Copy Theory

    Directory of Open Access Journals (Sweden)

    Brooke Larson

    2016-10-01

    Full Text Available It is a common understanding that Merge (Chomsky 1995 effectively explains the preponderance of displacement in language. That is, at least since Chomsky (2001, the mechanism that captures displacement (Internal Merge has been recognized as something that comes ‘for free’ along with Merge. However, the particular representation of that displacement has been subject to disagreement with some researchers assuming a copy-theoretic view and others a multidominance view. In this paper I offer arguments that support the copy theory of movement over that of multidominance. Multidominance demands that the grammar operate over positions instead of terms, which is incompatible with a Merge-based approach to structure building, and the copy theory demands no such thing. I also argue that the discontinuous interpretation of moved elements can be seen as evidence in favor of the copy theory. Additionally I note that previous arguments comparing the two representations fail on one of two counts. They either 1 rely on interface-dependent notions about which too little is known to be used to distinguish the two or 2 depend on issues of mathematical power that are not a priori relevant. The new arguments presented here rely on syntax-internal notions and interface notions that are on more solid empirical footing.

  8. Rendering Optical Effects Based on Spectra Representation in Complex Scenes

    OpenAIRE

    Dong, Weiming

    2006-01-01

    http://www.springerlink.com/; Rendering the structural color of natural objects or modern industrial products in the 3D environment is not possible with RGB-based graphics platforms and software and very time consuming, even with the most efficient spectra representation based methods previously proposed. Our framework allows computing full spectra light object interactions only when it is needed, i.e. for the part of the scene that requires simulating special spectra sensitive phenomena. Ach...

  9. An Ontology-Based Representation Architecture of Unstructured Information

    Institute of Scientific and Technical Information of China (English)

    GU Jin-guang; CHEN He-ping; CHEN Xin-meng

    2004-01-01

    Integrating with the respective advantages of XML Schema and Ontology, this paper puts forward a semantic information processing architecture-OBSA to solve the problem of heterogeneity of information sources and uncertainty of semantic.It introduces an F-Logic based semantic information presentation mechanism, presents a design of an ontology-based semantic representation language and a mapping algorithm converting Ontology to XML DTD/Schema, and an adapter framework for accessing distributed and heterogeneous information.

  10. 3D ear identification based on sparse representation.

    Science.gov (United States)

    Zhang, Lin; Ding, Zhixuan; Li, Hongyu; Shen, Ying

    2014-01-01

    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.

  11. Towards Web-based representation and processing of health information

    Directory of Open Access Journals (Sweden)

    Oldfield Eddie

    2009-01-01

    Full Text Available Abstract 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 at their fingertips. Increasingly complex problems in the health field require increasingly sophisticated computer software, distributed computing power, and standardized data sharing. To address this need, Web-based mapping is now emerging as an important tool to enable health practitioners, policy makers, and the public to understand spatial health risks, population health trends and vulnerabilities. Today several web-based health applications generate dynamic maps; however, for people to fully interpret the maps they need data source description and the method used in the data analysis or statistical modeling. 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 adequately applied to support flexible health data processing and mapping online. Results The authors of this study designed a HEalth Representation XML (HERXML schema that consists of the semantic (e.g., health activity description, the data sources description, the statistical methodology used for analysis, geometric, and cartographical representations of health data. A case study has been carried on the development of web application and services within the Canadian Geospatial Data Infrastructure (CGDI framework for community health programs of the New Brunswick Lung Association. This study facilitated the online processing, mapping and sharing of health information, with the use of HERXML and Open Geospatial Consortium (OGC services

  12. Texture Classification Using Sparse Frame-Based Representations

    Directory of Open Access Journals (Sweden)

    Skretting Karl

    2006-01-01

    Full Text Available A new method for supervised texture classification, denoted by frame texture classification method (FTCM, is proposed. The method is based on a deterministic texture model in which a small image block, taken from a texture region, is modeled as a sparse linear combination of frame elements. FTCM has two phases. In the design phase a frame is trained for each texture class based on given texture example images. The design method is an iterative procedure in which the representation error, given a sparseness constraint, is minimized. In the classification phase each pixel in a test image is labeled by analyzing its spatial neighborhood. This block is represented by each of the frames designed for the texture classes under consideration, and the frame giving the best representation gives the class. The FTCM is applied to nine test images of natural textures commonly used in other texture classification work, yielding excellent overall performance.

  13. Sparse representation-based image restoration via nonlocal supervised coding

    Science.gov (United States)

    Li, Ao; Chen, Deyun; Sun, Guanglu; Lin, Kezheng

    2016-09-01

    Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.

  14. 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.

  15. NEW APPROACH FOR IMAGE REPRESENTATION BASED ON GEOMETRIC STRUCTURAL CONTENTS

    Institute of Scientific and Technical Information of China (English)

    Jia Xiaomeng; Wang Guoyu

    2003-01-01

    This paper presents a novel approach for representation of image contents based on edge structural features. Edge detection is carried out for an image in the pre-processing stage.For feature representation, edge pixels are grouped into a set of segments through geometrical partitioning of the whole edge image. Then the invariant feature vector is computed for each edge-pixel segment. Thereby the image is represented with a set of spatially distributed feature vectors, each of which describes the local pattern of edge structures. Matching of two images can be achieved by the correspondence of two sets of feature vectors. Without the difficulty of image segmentation and object extraction due to the complexity of the real world images, the proposed approach provides a simple and flexible description for the image with complex scene, in terms of structural features of the image content. Experiments with real images illustrate the effectiveness of this new method.

  16. Time-frequency representation measurement based on temporal Fourier transformation

    Science.gov (United States)

    Suen, Yifan; Xiao, Shaoqiu; Hao, Sumin; Zhao, Xiaoxiang; Xiong, Yigao; Liu, Shenye

    2016-10-01

    We propose a new scheme to physically realize the short-time Fourier transform (STFT) of chirped optical pulse using time-lens array that enables us to get time-frequency representation without using FFT algorithm. The time-lens based upon the four-wave mixing is used to perform the process of temporal Fourier transformation. Pump pulse is used for both providing the quadratic phase and being the window function of STFT. The idea of STFT is physically realized in our scheme. Simulations have been done to investigate performance of the time-frequency representation scheme (TFRS) in comparison with STFT using FFT algorithm. Optimal measurement of resolution in time and frequency has been discussed.

  17. Teachers' Classroom-Based Action Research

    Science.gov (United States)

    Cain, Tim

    2011-01-01

    Teachers' classroom-based action research is sometimes misunderstood by those who undertake it and support it, in three respects. First, it is wrongly assumed to fall into either positivist or interpretive paradigms (or perhaps a mixture of both) or to be critical. Second, there is little understanding as to why action research is necessarily…

  18. Design of Multi-attribute Knowledge Base Based on Hybrid Knowledge Representation

    Institute of Scientific and Technical Information of China (English)

    TANG Zhi-jie; YANG Bao-an; ZHANG Ke-jing

    2006-01-01

    Based on the knowledge representation and knowledge reasoning, this paper addresses the creation of the multiattribute knowledge base on the basis of hybrid knowledge representation, with the help of object-oriented programming language and relational database. Compared with general knowledge base, multi-attribute knowledge base can enhance the ability of knowledge processing and application;integrate the heterogeneous knowledge, such as model,symbol, case-based sample knowledge; and support the whole decision process by integrated reasoning.

  19. Modeling the Maturation of Grip Selection Planning and Action Representation: Insights from Typical and Atypical Motor Development.

    Directory of Open Access Journals (Sweden)

    Ian eFuelscher

    2016-02-01

    Full Text Available We investigated the purported association between developmental changes in grip selection planning and improvements in an individual’s capacity to represent action at an internal level (i.e., motor imagery. Participants were groups of healthy children aged 6-7 years and 8-12 years respectively, while a group of adolescents (13-17 years and adults (18-34 years allowed for consideration of childhood development in the broader context of motor maturation. A group of children aged 8-12 years with probable DCD (pDCD was included as a reference group for atypical motor development. Participants’ proficiency to generate and/or engage internal action representations was inferred from performance on the hand rotation task, a well-validated measure of motor imagery. A grip selection task designed to elicit the end-state comfort (ESC effect provided a window into the integrity of grip selection planning. Consistent with earlier accounts, the efficiency of grip selection planning followed a non-linear developmental progression in neurotypical individuals. As expected, analysis confirmed that these developmental improvements were predicted by an increased capacity to generate and/or engage internal action representations. The profile of this association remained stable throughout the (typical developmental spectrum. These findings are consistent with computational accounts of action planning that argue that internal action representations are associated with the expression and development of grip selection planning across typical development. However, no such association was found for our sample of children with pDCD, suggesting that individuals with atypical motor skill may adopt an alternative, sub-optimal strategy to plan their grip selection compared to their same-age control peers.

  20. Modeling the Maturation of Grip Selection Planning and Action Representation: Insights from Typical and Atypical Motor Development

    Science.gov (United States)

    Fuelscher, Ian; Williams, Jacqueline; Wilmut, Kate; Enticott, Peter G.; Hyde, Christian

    2016-01-01

    We investigated the purported association between developmental changes in grip selection planning and improvements in an individual’s capacity to represent action at an internal level [i.e., motor imagery (MI)]. Participants were groups of healthy children aged 6–7 years and 8–12 years respectively, while a group of adolescents (13–17 years) and adults (18–34 years) allowed for consideration of childhood development in the broader context of motor maturation. A group of children aged 8–12 years with probable DCD (pDCD) was included as a reference group for atypical motor development. Participants’ proficiency to generate and/or engage internal action representations was inferred from performance on the hand rotation task, a well-validated measure of MI. A grip selection task designed to elicit the end-state comfort (ESC) effect provided a window into the integrity of grip selection planning. Consistent with earlier accounts, the efficiency of grip selection planning followed a non-linear developmental progression in neurotypical individuals. As expected, analysis confirmed that these developmental improvements were predicted by an increased capacity to generate and/or engage internal action representations. The profile of this association remained stable throughout the (typical) developmental spectrum. These findings are consistent with computational accounts of action planning that argue that internal action representations are associated with the expression and development of grip selection planning across typical development. However, no such association was found for our sample of children with pDCD, suggesting that individuals with atypical motor skill may adopt an alternative, sub-optimal strategy to plan their grip selection compared to their same-age control peers. PMID:26903915

  1. 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.

  2. 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.

  3. Online Signature Verification Based on DCT and Sparse Representation.

    Science.gov (United States)

    Liu, Yishu; Yang, Zhihua; Yang, Lihua

    2015-11-01

    In this paper, a novel online signature verification technique based on discrete cosine transform (DCT) and sparse representation is proposed. We find a new property of DCT, which can be used to obtain a compact representation of an online signature using a fixed number of coefficients, leading to simple matching procedures and providing an effective alternative to deal with time series of different lengths. The property is also used to extract energy features. Furthermore, a new attempt to apply sparse representation to online signature verification is made, and a novel task-specific method for building overcomplete dictionaries is proposed, then sparsity features are extracted. Finally, energy features and sparsity features are concatenated to form a feature vector. Experiments are conducted on the Sabancı University's Signature Database (SUSIG)-Visual and SVC2004 databases, and the results show that our proposed method authenticates persons very reliably with a verification performance which is better than those of state-of-the-art methods on the same databases.

  4. A Collaborative Neighbor Representation Based Face Recognition Algorithm

    Directory of Open Access Journals (Sweden)

    Zhengming Li

    2013-01-01

    Full Text Available We propose a new collaborative neighbor representation algorithm for face recognition based on a revised regularized reconstruction error (RRRE, called the two-phase collaborative neighbor representation algorithm (TCNR. Specifically, the RRRE is the division of  l2-norm of reconstruction error of each class into a linear combination of  l2-norm of reconstruction coefficients of each class, which can be used to increase the discrimination information for classification. The algorithm is as follows: in the first phase, the test sample is represented as a linear combination of all the training samples by incorporating the neighbor information into the objective function. In the second phase, we use the k classes to represent the test sample and calculate the collaborative neighbor representation coefficients. TCNR not only can preserve locality and similarity information of sparse coding but also can eliminate the side effect on the classification decision of the class that is far from the test sample. Moreover, the rationale and alternative scheme of TCNR are given. The experimental results show that TCNR algorithm achieves better performance than seven previous algorithms.

  5. 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.

  6. Improved Spectral Representation for Birdcall Based on Fractional Fourier Transform

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A novel spectral representation based on fractional Fourier transform (FrFT) is proposed and applied to birdcall analysis. The FrFT-based spectrogram of a signal is derived and compared with its FT-based counterpart, and the spectrum gathering method is used to show the energy distribution related to the pitch frequency. The fixed transform order and adaptive orders for FrFT are tested. The fixed order can be obtained empirically or calculated according to the known chirp rate. The adaptive optimal orders are determined by using ambiguity function. Experimental results with birdcalls show that the FrFT-based spectrogram with an optimal transform order has higher resolution than its STFT-based counterpart, and the better performance can be achieved if adaptive orders are used.

  7. DOPPLERLET BASED TIME-FREQUENCY REPRESENTATION VIA MATCHING PURSUITS

    Institute of Scientific and Technical Information of China (English)

    Zou Hongxing; Zhou Xiaobo; Dai Qionghai; Li Yanda

    2001-01-01

    A new time-frequency representation called Dopplerlet transform, which uses the dilated, translated and modulated windowed Doppler signals as its basis functions, is proposed, and the Fourier transform, short-time Fourier transform (including Gabor transform), wavelet transform, and chirplet transform are formulated in one framework of Dopplerlet transform accordingly.It is proved that the matching pursuits based on Dopplerlet basis functions are convergent, and that the energy of residual signals yielded in the decomposition process decays exponentially. Simulation results show that the matching pursuits with Dopplerlet basis functions can characterize compactly a nonstationary signal.

  8. USING MORPHLET-BASED IMAGE REPRESENTATION FOR OBJECT DETECTION

    Directory of Open Access Journals (Sweden)

    V. S. Gorbatsevich

    2016-06-01

    Full Text Available In this paper, we propose an original method for objects detection based on a special tree-structured image representation – the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  9. An object-based methodology for knowledge representation

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R.L. [Los Alamos National Lab., NM (United States)|New Mexico State Univ., Las Cruces, NM (United States); Hartley, R.T. [New Mexico State Univ., Las Cruces, NM (United States); Webster, R.B. [Los Alamos National Lab., NM (United States)

    1997-11-01

    An object based methodology for knowledge representation is presented. The constructs and notation to the methodology are described and illustrated with examples. The ``blocks world,`` a classic artificial intelligence problem, is used to illustrate some of the features of the methodology including perspectives and events. Representing knowledge with perspectives can enrich the detail of the knowledge and facilitate potential lines of reasoning. Events allow example uses of the knowledge to be represented along with the contained knowledge. Other features include the extensibility and maintainability of knowledge represented in the methodology.

  10. 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.

  11. Room Categorization Based on a Hierarchical Representation of Space

    Directory of Open Access Journals (Sweden)

    Peter Uršič

    2013-02-01

    Full Text Available For successful operation in real‐world environments, a mobile robot requires an effective spatial model. The model should be compact, should possess large expressive power and should scale well with respect to the number of modelled categories. In this paper we propose a new compositional hierarchical representation of space that is based on learning statistically significant observations, in terms of the frequency of occurrence of various shapes in the environment. We have focused on a two‐dimensional space, since many robots perceive their surroundings in two dimensions with the use of a laser range finder or sonar. We also propose a new low‐level image descriptor, by which we demonstrate the performance of our representation in the context of a room categorization problem. Using only the lower layers of the hierarchy, we obtain state‐of‐the‐art categorization results in two different experimental scenarios. We also present a large, freely available, dataset, which is intended for room categorization experiments based on data obtained with a laser range finder.

  12. Finger vein verification system based on sparse representation.

    Science.gov (United States)

    Xin, Yang; Liu, Zhi; Zhang, Haixia; Zhang, Hong

    2012-09-01

    Finger vein verification is a promising biometric pattern for personal identification in terms of security and convenience. The recognition performance of this technology heavily relies on the quality of finger vein images and on the recognition algorithm. To achieve efficient recognition performance, a special finger vein imaging device is developed, and a finger vein recognition method based on sparse representation is proposed. The motivation for the proposed method is that finger vein images exhibit a sparse property. In the proposed system, the regions of interest (ROIs) in the finger vein images are segmented and enhanced. Sparse representation and sparsity preserving projection on ROIs are performed to obtain the features. Finally, the features are measured for recognition. An equal error rate of 0.017% was achieved based on the finger vein image database, which contains images that were captured by using the near-IR imaging device that was developed in this study. The experimental results demonstrate that the proposed method is faster and more robust than previous methods.

  13. Magnetic resonance brain tissue segmentation based on sparse representations

    Science.gov (United States)

    Rueda, Andrea

    2015-12-01

    Segmentation or delineation of specific organs and structures in medical images is an important task in the clinical diagnosis and treatment, since it allows to characterize pathologies through imaging measures (biomarkers). In brain imaging, segmentation of main tissues or specific structures is challenging, due to the anatomic variability and complexity, and the presence of image artifacts (noise, intensity inhomogeneities, partial volume effect). In this paper, an automatic segmentation strategy is proposed, based on sparse representations and coupled dictionaries. Image intensity patterns are singly related to tissue labels at the level of small patches, gathering this information in coupled intensity/segmentation dictionaries. This dictionaries are used within a sparse representation framework to find the projection of a new intensity image onto the intensity dictionary, and the same projection can be used with the segmentation dictionary to estimate the corresponding segmentation. Preliminary results obtained with two publicly available datasets suggest that the proposal is capable of estimating adequate segmentations for gray matter (GM) and white matter (WM) tissues, with an average overlapping of 0:79 for GM and 0:71 for WM (with respect to original segmentations).

  14. 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.

  15. Manipulation of patient-provider interaction: discussing illness representations or action plans concerning adherence.

    NARCIS (Netherlands)

    Theunissen, N.C.M.; Ridder, D.T.D. de; Bensing, J.M.; Rutten, G.E.H.M.

    2003-01-01

    According to Leventhal's Self-Regulatory Model of Illness, patients have ideas and action plans related to the management of their disease. The aim of this study is to examine whether ideas and action plans relating to hypertension change as a result of general practitioner's (GP's) discussing them

  16. Manipulation of patient–provider interaction: discussing illness representations or action plans concerning adherence

    NARCIS (Netherlands)

    Theunissen, N.C.M.; Ridder, D.T.D. de; Bensing, J.; Rutten, G.E.H.M.

    2003-01-01

    According to Leventhal’s Self-Regulatory Model of Illness, patients have ideas and action plans related to the management of their disease. The aim of this study is to examine whether ideas and action plans relating to hypertension change as a result of general practitioner’s (GP’s) discussing them

  17. A continuous semantic space describes the representation of thousands of object and action categories across the human brain.

    Science.gov (United States)

    Huth, Alexander G; Nishimoto, Shinji; Vu, An T; Gallant, Jack L

    2012-12-20

    Humans can see and name thousands of distinct object and action categories, so it is unlikely that each category is represented in a distinct brain area. A more efficient scheme would be to represent categories as locations in a continuous semantic space mapped smoothly across the cortical surface. To search for such a space, we used fMRI to measure human brain activity evoked by natural movies. We then used voxelwise models to examine the cortical representation of 1,705 object and action categories. The first few dimensions of the underlying semantic space were recovered from the fit models by principal components analysis. Projection of the recovered semantic space onto cortical flat maps shows that semantic selectivity is organized into smooth gradients that cover much of visual and nonvisual cortex. Furthermore, both the recovered semantic space and the cortical organization of the space are shared across different individuals.

  18. Fingerprint Representation Methods Based on B-Spline Functions

    Institute of Scientific and Technical Information of China (English)

    Ruan Ke; Xia De-lin; Yan Pu-liu

    2004-01-01

    The global characteristics of a fingerprint image such as the ridge shape and ridge topology are often ignored in most automatic fingerprint verification system. In this paper, a new representative method based on B-Spline curve is proposed to address this problem. The resultant B-Spline curves can represent the global characteristics completely and the curves are analyzable and precise. An algorithm is also proposed to extract the curves from the fingerprint image. In addition to preserve the most information of the fingerprint image, the knot-points number of the B-Spline curve is reduced to minimum in this algorithm. At the same time, the influence of the fingerprint image noise is discussed. In the end, an example is given to demonstrate the effectiveness of the representation method.

  19. Sparse representation-based spectral clustering for SAR image segmentation

    Science.gov (United States)

    Zhang, Xiangrong; Wei, Zhengli; Feng, Jie; Jiao, Licheng

    2011-12-01

    A new method, sparse representation based spectral clustering (SC) with Nyström method, is proposed for synthetic aperture radar (SAR) image segmentation. Different from the conventional SC, this proposed technique is developed by using the sparse coefficients which obtained by solving l1 minimization problem to construct the affinity matrix and the Nyström method is applied to alleviate the segmentation process. The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially. We apply the proposed method, k-means and the classic spectral clustering algorithm with Nyström method to SAR image segmentation. The results show that compared with the other two methods, the proposed method can obtain much better segmentation results.

  20. Signal overcomplete representation and sparse decomposition based on redundant dictionaries

    Institute of Scientific and Technical Information of China (English)

    ZHANG Chunmei; YIN Zhongke; CHEN Xiangdong; XIAO Mingxia

    2005-01-01

    Decomposing a signal based upon redundant dictionaries is a new method for data representation on signal processing. It approximates a signal with an overcomplete system instead of an orthonormal basis to provide a sufficient choice for adaptive sparse decompositions. Replacing the original data with a sparse approximation can result in not only a higher compression ratio, but also greater flexibility in capturing the inherent structure of the natural signals with the redundancy of dictionaries. This paper gives an overview of a series of recent results in this field, and deals with the relationship between sparsity of signal decomposition and incoherence of dictionaries with BP and MP algorithms. The current and future challenges of the dictionary construction are discussed.

  1. Improvement in image resolution based on dispersive representation of data

    Science.gov (United States)

    Kravchenko, V. F.; Ponomaryov, V. I.; Pustovoit, V. I.

    2016-10-01

    A method for reconstructing the resolution of images, based on selection and optimization of significant local features and sparse representation of processed-image blocks (using optimized low- and high-resolution dictionaries), has been substantiated for the first time. This method, making it possible to improve significantly the resolution of images of various nature, is interpreted physically. A block diagram of the processing system corresponding to the new approach to image reconstruction has been developed. A simulation of the new method for reconstructing images of different physical natures and known algorithms showed an advantage of the new scheme for reconstructing resolution in terms of universally recognized criteria (peak signal-to-noise ratio, mean absolute error, and structural similarity index measure) and in visual comparison of the processed images.

  2. Representation of actions in rats: The role of cerebellum in learning spatial performances by observation

    OpenAIRE

    2000-01-01

    Experimental evidence demonstrates that cerebellar networks are involved in spatial learning, controlling the acquisition of exploration strategies without blocking motor execution of the task. Action learning by observation has been considered somehow related to motor physiology, because it provides a way of learning performances that is almost as effective as the actual execution of actions. Neuroimaging studies demonstrate that observation of movements performed by others, imagination of a...

  3. Representation of actions in rats: the role of cerebellum in learning spatial performances by observation.

    Science.gov (United States)

    Leggio, M G; Molinari, M; Neri, P; Graziano, A; Mandolesi, L; Petrosini, L

    2000-02-29

    Experimental evidence demonstrates that cerebellar networks are involved in spatial learning, controlling the acquisition of exploration strategies without blocking motor execution of the task. Action learning by observation has been considered somehow related to motor physiology, because it provides a way of learning performances that is almost as effective as the actual execution of actions. Neuroimaging studies demonstrate that observation of movements performed by others, imagination of actions, and actual execution of motor performances share common neural substrates and that the cerebellum is among these shared areas. The present paper analyzes the effects of observation in learning a spatial task, focusing on the cerebellar role in learning a spatial ability through observation. We allowed normal rats to observe 200 Morris water maze trials performed by companion rats. After this observation training, "observer" rats underwent a hemicerebellectomy and then were tested in the Morris water maze. In spite of the cerebellar lesion, they displayed no spatial defects, exhibiting exploration abilities comparable to controls. When the cerebellar lesion preceded observation training, a complete lack of spatial observational learning was observed. Thus, as demonstrated already for the acquisition of spatial procedures through actual execution, cerebellar circuits appear to play a key role in the acquisition of spatial procedures also through observation. In conclusion, the present results provide strong support for a common neural basis in the observation of actions that are to be reproduced as well as in the actual production of the same actions.

  4. Action semantics modulate action prediction.

    Science.gov (United States)

    Springer, Anne; Prinz, Wolfgang

    2010-11-01

    Previous studies have demonstrated that action prediction involves an internal action simulation that runs time-locked to the real action. The present study replicates and extends these findings by indicating a real-time simulation process (Graf et al., 2007), which can be differentiated from a similarity-based evaluation of internal action representations. Moreover, results showed that action semantics modulate action prediction accuracy. The semantic effect was specified by the processing of action verbs and concrete nouns (Experiment 1) and, more specifically, by the dynamics described by action verbs (Experiment 2) and the speed described by the verbs (e.g., "to catch" vs. "to grasp" vs. "to stretch"; Experiment 3). These results propose a linkage between action simulation and action semantics as two yet unrelated domains, a view that coincides with a recent notion of a close link between motor processes and the understanding of action language.

  5. Having a goal to stop action is associated with advance control of specific motor representations.

    Science.gov (United States)

    Claffey, Michael P; Sheldon, Sarah; Stinear, Cathy M; Verbruggen, Frederick; Aron, Adam R

    2010-01-01

    An important aspect of cognitive control consists in the ability to stop oneself from making inappropriate responses. In an earlier study we demonstrated that there are different mechanisms for stopping: global and selective [Aron, A. R., Verbruggen, F. (2008). Stop the presses: Dissociating a selective from a global mechanism for stopping. Psychological Science, 19(11) 1146-1153]. We argued that participants are more likely to use a global mechanism when speed is of the essence, whereas they are more likely to use a selective mechanism when they have foreknowledge of which response tendency they may need to stop. Here we further investigate the relationship between foreknowledge and selective stopping. In Experiment 1 we adapted the earlier design to show that individual differences in recall accuracy for the stopping goal correlate with the selectivity of the stopping. This confirms that encoding and using a foreknowledge memory cue is a key enabler for a selective stopping mechanism. In Experiment 2, we used transcranial magnetic stimulation (TMS), to test the hypothesis that foreknowledge "sets up" a control set whereby control is applied onto the response representation that may need to be stopped in the future. We applied TMS to the left motor cortex and measured motor evoked potentials (MEPs) from the right hand while participants performed a similar behavioral paradigm as Experiment 1. In the foreknowledge period, MEPs were significantly reduced for trials where the right hand was the one that might need to be stopped relative to when it was not. This shows that having a goal of what response may need to be stopped in the future consists in applying advance control onto a specific motor representation.

  6. 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.

  7. 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.

  8. Towards Web-based representation and processing of health information

    DEFF Research Database (Denmark)

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

    2009-01-01

    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 at their fing......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...... at their fingertips. Increasingly complex problems in the health field require increasingly sophisticated computer software, distributed computing power, and standardized data sharing. To address this need, Web-based mapping is now emerging as an important tool to enable health practitioners, policy makers...... 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...

  9. CONTENT BASED VIDEO RETRIEVAL BASED ON HDWT AND SPARSE REPRESENTATION

    Directory of Open Access Journals (Sweden)

    Sajad Mohamadzadeh

    2016-04-01

    Full Text Available Video retrieval has recently attracted a lot of research attention due to the exponential growth of video datasets and the internet. Content based video retrieval (CBVR systems are very useful for a wide range of applications with several type of data such as visual, audio and metadata. In this paper, we are only using the visual information from the video. Shot boundary detection, key frame extraction, and video retrieval are three important parts of CBVR systems. In this paper, we have modified and proposed new methods for the three important parts of our CBVR system. Meanwhile, the local and global color, texture, and motion features of the video are extracted as features of key frames. To evaluate the applicability of the proposed technique against various methods, the P(1 metric and the CC_WEB_VIDEO dataset are used. The experimental results show that the proposed method provides better performance and less processing time compared to the other methods.

  10. Stimulus devaluation induced by action stopping is greater for explicit value representations

    Directory of Open Access Journals (Sweden)

    Jan R Wessel

    2015-10-01

    Full Text Available We recently showed that rapidly stopping an action in the face of a reward-related stimulus reduces the subjective value of that stimulus (Wessel et al., 2014. In that study, there were three phases. In an initial learning phase, geometric shapes were associated with monetary value via implicit learning. In a subsequent treatment phase, half the shapes were paired with action-stopping, and half were not. In a final auction phase, shapes that had been paired with stopping in the treatment phase were subjectively perceived as less valuable compared to those that were not. Exploratory post-hoc analysis showed that the stopping-induced devaluation effect was larger for participants with greater explicit knowledge of stimulus values. Here, we repeated the study in 65 participants to systematically test whether the level of explicit knowledge influences the degree of devaluation. The results replicated the core result that action-stopping reduces stimulus value. Furthermore, they showed that this effect was indeed significantly larger in participants with more explicit knowledge of the relative stimulus values in the learning phase. These results speak to the robustness of the stopping-induced devaluation effect, and furthermore imply that behavioral therapies using stopping could be successful in devaluing real-world stimuli, insofar as stimulus values are explicitly represented. Finally, to facilitate future investigations into the applicability of these findings as well as the mechanisms underlying stopping-induced stimulus devaluation, we herein provide open source code for the behavioral paradigm.

  11. Stimulus devaluation induced by action stopping is greater for explicit value representations.

    Science.gov (United States)

    Wessel, Jan R; Tonnesen, Alexandra L; Aron, Adam R

    2015-01-01

    We recently showed that rapidly stopping an action in the face of a reward-related stimulus reduces the subjective value of that stimulus (Wessel et al., 2014). In that study, there were three phases. In an initial learning phase, geometric shapes were associated with monetary value via implicit learning. In a subsequent treatment phase, half the shapes were paired with action stopping, and half were not. In a final auction phase, shapes that had been paired with stopping in the treatment phase were subjectively perceived as less valuable compared to those that were not. Exploratory post hoc analyses showed that the stopping-induced devaluation effect was larger for participants with greater explicit knowledge of stimulus values. Here, we repeated the study in 65 participants to systematically test whether the level of explicit knowledge influences the degree of devaluation. The results replicated the core result that action stopping reduces stimulus value. Furthermore, they showed that this effect was indeed significantly larger in participants with more explicit knowledge of the relative stimulus values in the learning phase. These results speak to the robustness of the stopping-induced devaluation effect, and furthermore imply that behavioral therapies using stopping could be successful in devaluing real-world stimuli, insofar as stimulus values are explicitly represented. Finally, to facilitate future investigations into the applicability of these findings, as well as the mechanisms underlying stopping-induced stimulus devaluation, we herein provide open source code for the behavioral paradigm.

  12. 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.

  13. Miura-type transformations for lattice equations and Lie group actions associated with Darboux-Lax representations

    Science.gov (United States)

    Berkeley, George; Igonin, Sergei

    2016-07-01

    Miura-type transformations (MTs) are an essential tool in the theory of integrable nonlinear partial differential and difference equations. We present a geometric method to construct MTs for differential-difference (lattice) equations from Darboux-Lax representations (DLRs) of such equations. The method is applicable to parameter-dependent DLRs satisfying certain conditions. We construct MTs and modified lattice equations from invariants of some Lie group actions on manifolds associated with such DLRs. Using this construction, from a given suitable DLR one can obtain many MTs of different orders. The main idea behind this method is closely related to the results of Drinfeld and Sokolov on MTs for the partial differential KdV equation. Considered examples include the Volterra, Narita-Itoh-Bogoyavlensky, Toda, and Adler-Postnikov lattices. Some of the constructed MTs and modified lattice equations seem to be new.

  14. Graph-based knowledge representation computational foundations of conceptual graphs

    CERN Document Server

    Chein, Michel; Chein, Michel

    2008-01-01

    In addressing the question of how far it is possible to go in knowledge representation and reasoning through graphs, the authors cover basic conceptual graphs, computational aspects, and kernel extensions. The basic mathematical notions are summarized.

  15. A communication-channel-based representation system for software

    NARCIS (Netherlands)

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

    2014-01-01

    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

  16. Representation functions of additive bases for abelian semigroups

    Directory of Open Access Journals (Sweden)

    Melvyn B. Nathanson

    2004-01-01

    function has only finitely many zeros. It is proved that for a large class of countably infinite abelian semigroups, there exists a basis whose representation function is exactly equal to the given function for every element in the semigroup.

  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. Knowledge Representation in KDD Based on Linguistic Atoms

    Institute of Scientific and Technical Information of China (English)

    李德毅

    1997-01-01

    An important issue in Knowledge Discovery in Databases is to allo the discovered knowledge to be as close as possible to natural languages to satisfy user needs with tractability on one hand,and to offer KDD systems robustness on the other hand.At this junction,this paper describes a new concept of linguistic atoms with three digital characteristics:expected value Ex,entropy En,anddeviation D.The mathematical description has effectively integrated the fuzziness and randomness of linguistic terms in a unified way.Based on this model a method of knowledge representation in KDD is developed which bridges the gap between quantitative knowledge and qualitative knowledge.Mapping between quantitatives and qualitatives becomes much easier and interchangeable.In order to discover generalized knowledge from a database,one may use virtual linguistic terms and cloud transforms for the auto-generation of concept hierarchies to attributes.Predictive data mining with the cloud model is given for implementation.This further illustrates the advantages of this linguistic model in KDD.

  19. Perceptual hashing of sheet music based on graphical representation

    Science.gov (United States)

    Kremser, Gert; Schmucker, Martin

    2006-02-01

    For the protection of Intellectual Property Rights (IPR), different passive protection methods have been developed. These watermarking and fingerprinting technologies protect content beyond access control and thus tracing illegal distributions as well as the identification of people who are responsible for a illegal distribution is possible. The public's attention was attracted especially to the second application by the illegal distribution of the so called 'Hollywood screeners'. The focus of current research is on audio and video content and images. These are the common content types we are faced with every day, and which mostly have a huge commercial value. Especially the illegal distribution of content that has not been officially published shows the potential commercial impact of illegal distributions. Content types, however, are not limited to audio, video and images. There is a range of other content types, which also deserve the development of passive protection technologies. For sheet music for instance, different watermarking technologies have been developed, which up to this point only function within certain limitations. This is the reason why we wanted to find out how to develop a fingerprinting or perceptual hashing method for sheet music. In this article, we describe the development of our algorithm for sheet music, which is based on simple graphical features. We describe the selection of these features and the subsequent processing steps. The resulting compact representation is analyzed and the first performance results are reported.

  20. Multisensory representation of the space near the hand: from perception to action and interindividual interactions.

    Science.gov (United States)

    Brozzoli, Claudio; Ehrsson, H Henrik; Farnè, Alessandro

    2014-04-01

    When interacting with objects and other people, the brain needs to locate our limbs and the relevant visual information surrounding them. Studies on monkeys showed that information from different sensory modalities converge at the single cell level within a set of interconnected multisensory frontoparietal areas. It is largely accepted that this network allows for multisensory processing of the space surrounding the body (peripersonal space), whose function has been linked to the sensory guidance of appetitive and defensive movements, and localization of the limbs in space. In the current review, we consider multidisciplinary findings about the processing of the space near the hands in humans and offer a convergent view of its functions and underlying neural mechanisms. We will suggest that evolution has provided the brain with a clever tool for representing visual information around the hand, which takes the hand itself as a reference for the coding of surrounding visual space. We will contend that the hand-centered representation of space, known as perihand space, is a multisensory-motor interface that allows interaction with the objects and other persons around us.

  1. Class actions in Argentina: standing to sue and adequacy of representation

    Directory of Open Access Journals (Sweden)

    Francisco Verbic

    2014-01-01

    Full Text Available The paper describes how Argentine policy makers have thought about and enacted rules on collective litigation in the field of consumer and environmental protection. It presents an overview of the scope and content of those rules, with special focus on standing to sue and adequacy of representation. It also explains how the Supreme Court of Justice of Argentina has reacted when facing collective conflicts even in absence of adequate procedural rules to deal with collective conflicts. The case law of this high Court has provided relevant guidance to lower courts as well as to litigants regarding case management and constitutional requisites of collective litigation mechanisms. It has also summoned Congress due to the lack of a comprehensive and adequate procedural regulation in this field of law. In doing that, it has shaped a system quite similar to that enacted in the US Federal Rule of Civil Procedure 23. Almost 20 years after the constitutional amendment which has given constitutional status to collective standing to sue, it may be said that this kind of representative proceedings is just going through a developing and experimental phase in Argentina. Thanks to the role of the Supreme Court in the last 10 years, however, there are good reasons to have great expectations about what is coming up in the near future.

  2. Method of Dynamic Knowledge Representation and Learning Based on Fuzzy Petri Nets

    Institute of Scientific and Technical Information of China (English)

    WEI Sheng-jun; HU Chang-zhen; SUN Ming-qian

    2008-01-01

    A method of knowledge representation and learning based on fuzzy Petri nets was designed. In this way the parameters of weights, threshold value and certainty factor in knowledge model can be adjusted dynamically. The advantages of knowledge representation based on production rules and neural networks were integrated into this method. Just as production knowledge representation, this method has clear structure and specific parameters meaning. In addition, it has learning and parallel reasoning ability as neural networks knowledge representation does. The result of simulation shows that the learning algorithm can converge, and the parameters of weights, threshold value and certainty factor can reach the ideal level after training.

  3. Generating action descriptions from statistically integrated representations of human motions and sentences.

    Science.gov (United States)

    Takano, Wataru; Kusajima, Ikuo; Nakamura, Yoshihiko

    2016-08-01

    It is desirable for robots to be able to linguistically understand human actions during human-robot interactions. Previous research has developed frameworks for encoding human full body motion into model parameters and for classifying motion into specific categories. For full understanding, the motion categories need to be connected to the natural language such that the robots can interpret human motions as linguistic expressions. This paper proposes a novel framework for integrating observation of human motion with that of natural language. This framework consists of two models; the first model statistically learns the relations between motions and their relevant words, and the second statistically learns sentence structures as word n-grams. Integration of these two models allows robots to generate sentences from human motions by searching for words relevant to the motion using the first model and then arranging these words in appropriate order using the second model. This allows making sentences that are the most likely to be generated from the motion. The proposed framework was tested on human full body motion measured by an optical motion capture system. In this, descriptive sentences were manually attached to the motions, and the validity of the system was demonstrated.

  4. Representation of 1/f signal with wavelet bases

    Institute of Scientific and Technical Information of China (English)

    刘峰; 刘贵忠; 张茁生

    2000-01-01

    The representation of 1/f signal with wavelet transformation is explored. It is shown that a class of 1/f signal can be represented via wavelet synthetic formula and that a statistically self-similar property of signals may be characterized by the correlation functions of wavelet coefficients in the wavelet domain.

  5. 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.

  6. A 2-D graphical representation of protein sequences based on nucleotide triplet codons

    Science.gov (United States)

    Bai, Fenglan; Wang, Tianming

    2005-09-01

    Graphical representation of DNA provides a simple way of viewing, sorting and comparing various gene structures. A 2-D graphical representation of protein sequences based on nucleotide triplet codons has been derived for similarity analysis of protein sequences. This approach is based on a graphical representation of triplets of DNA in which the interior of the left half plane of the complex plane is used to accommodate 64 sites for the 64 codons. We associate a directed curve, numerical value, or matrix with a protein as a descriptor. The approach is illustrated on the Homo sapiens X-linked nuclear protein (ATRX) gene.

  7. Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

    Science.gov (United States)

    2012-09-01

    different decisions as com- pared to an unmanned aerial vehicle (UAV) mission reconfig- uration based on prognostics indication on power train fail- ures...Degradation Modeling Training Trajectories Test Trajectory Parameter Estimation State-space Representation Prognostics Dynamic System Realization Health...and ASME. Kai Goebel received the degree of Diplom-Ingenieur from the Technische University Munchen, Germany in 1990. He received the M.S. and Ph.D

  8. Spectral Collaborative Representation based Classification for Hand Gestures recognition on Electromyography Signals

    OpenAIRE

    Boyali, Ali

    2015-01-01

    In this study, we introduce a novel variant and application of the Collaborative Representation based Classification in spectral domain for recognition of the hand gestures using the raw surface Electromyography signals. The intuitive use of spectral features are explained via circulant matrices. The proposed Spectral Collaborative Representation based Classification (SCRC) is able to recognize gestures with higher levels of accuracy for a fairly rich gesture set. The worst recognition result...

  9. Spatiotemporal dynamics of similarity-based neural representations of facial identity.

    Science.gov (United States)

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

    2017-01-10

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

  10. Robust Face Recognition using Voting by Bit-plane Images based on Sparse Representation

    Directory of Open Access Journals (Sweden)

    Dongmei Wei

    2015-08-01

    Full Text Available Plurality voting is widely employed as combination strategies in pattern recognition. As a technology proposed recently, sparse representation based classification codes the query image as a sparse linear combination of entire training images and classifies the query sample class by class exploiting the class representation error. In this paper, an improvement face recognition approach using sparse representation and plurality voting based on the binary bit-plane images is proposed. After being equalized, gray images are decomposed into eight bit-plane images, sparse representation based classification is exploited respectively on the five bit-plane images that have more discrimination information. Finally, the true identity of query image is voted by these five identities obtained. Experiment results shown that this proposed approach is preferable both in recognition accuracy and in recognition speed.

  11. An Accurate Projector Calibration Method Based on Polynomial Distortion Representation

    Directory of Open Access Journals (Sweden)

    Miao Liu

    2015-10-01

    Full Text Available In structure light measurement systems or 3D printing systems, the errors caused by optical distortion of a digital projector always affect the precision performance and cannot be ignored. Existing methods to calibrate the projection distortion rely on calibration plate and photogrammetry, so the calibration performance is largely affected by the quality of the plate and the imaging system. This paper proposes a new projector calibration approach that makes use of photodiodes to directly detect the light emitted from a digital projector. By analyzing the output sequence of the photoelectric module, the pixel coordinates can be accurately obtained by the curve fitting method. A polynomial distortion representation is employed to reduce the residuals of the traditional distortion representation model. Experimental results and performance evaluation show that the proposed calibration method is able to avoid most of the disadvantages in traditional methods and achieves a higher accuracy. This proposed method is also practically applicable to evaluate the geometric optical performance of other optical projection system.

  12. Robust phase-domain transmission line representation based on time-domain fitting

    Energy Technology Data Exchange (ETDEWEB)

    Nobre, Diana M.; Neves, Washington L.A. [Federal University of Campina Grande (UFCG), Electrical Engineering Department, Av Aprigio Veloso, 882 Campina Grande, PB 58.109-970 (Brazil); Boaventura, Wallace do C. [Federal University of Minas Gerais (UFMG), Electrical Engineering Department, Av Antonio Carlos, 6627 Pampulha, Belo Horizonte, MG 31.270-010 (Brazil)

    2006-05-15

    This work presents a methodology for deriving a phase-domain transmission line representation based on time-domain fitting. A polynomial matrix in the discrete-time domain describes the resulting model. The robustness of the representation, its stability and passivity, is attained by imbedding a set of constraints in the solution of the fitting equations, which are solved using quadratic programming. Results demonstrating from transient simulations the features of the derived representation are presented for the case of an asymmetric, untransposed two-phase transmission line. (author)

  13. Domain adaptation of image classification based on collective target nearest-neighbor representation

    Science.gov (United States)

    Tang, Song; Ye, Mao; Liu, Qihe; Li, Fan

    2016-05-01

    In many practical applications, we frequently face the awkward problem in which an image classifier trained in a scenario is difficult to use in a new scenario. Traditionally, the probability inference-based methods are used to solve this problem. From the point of image representation, we propose an approach for domain adaption of image classification. First, all source samples are supposed to form the dictionary. Then, we encode the target sample by combining this dictionary and the local geometric information. Based on this new representation, called target nearest-neighbor representation, image classification can obtain good performance in the target domain. Our core contribution is that the nearest-neighbor information of the target sample is technically exploited to form more robust representation. Experimental results confirm the effectiveness of our method.

  14. Maximum-margin based representation learning from multiple atlases for Alzheimer's disease classification.

    Science.gov (United States)

    Min, Rui; Cheng, Jian; Price, True; Wu, Guorong; Shen, Dinggang

    2014-01-01

    In order to establish the correspondences between different brains for comparison, spatial normalization based morphometric measurements have been widely used in the analysis of Alzheimer's disease (AD). In the literature, different subjects are often compared in one atlas space, which may be insufficient in revealing complex brain changes. In this paper, instead of deploying one atlas for feature extraction and classification, we propose a maximum-margin based representation learning (MMRL) method to learn the optimal representation from multiple atlases. Unlike traditional methods that perform the representation learning separately from the classification, we propose to learn the new representation jointly with the classification model, which is more powerful in discriminating AD patients from normal controls (NC). We evaluated the proposed method on the ADNI database, and achieved 90.69% for AD/NC classification and 73.69% for p-MCI/s-MCI classification.

  15. A feature representation method for biomedical scientific data based on composite text description

    Institute of Scientific and Technical Information of China (English)

    SUN; Wei

    2009-01-01

    Feature representation is one of the key issues in data clustering.The existing feature representation of scientific data is not sufficient,which to some extent affects the result of scientific data clustering.Therefore,the paper proposes a concept of composite text description(CTD)and a CTD-based feature representation method for biomedical scientific data.The method mainly uses different feature weight algorisms to represent candidate features based on two types of data sources respectively,combines and finally strengthens the two feature sets.Experiments show that comparing with traditional methods,the feature representation method is more effective than traditional methods and can significantly improve the performance of biomedcial data clustering.

  16. Towards OWL-based Knowledge Representation in Petrology

    CERN Document Server

    Shkotin, Alex; Kudryavtsev, Dmitry

    2011-01-01

    This paper presents our work on development of OWL-driven systems for formal representation and reasoning about terminological knowledge and facts in petrology. The long-term aim of our project is to provide solid foundations for a large-scale integration of various kinds of knowledge, including basic terms, rock classification algorithms, findings and reports. We describe three steps we have taken towards that goal here. First, we develop a semi-automated procedure for transforming a database of igneous rock samples to texts in a controlled natural language (CNL), and then a collection of OWL ontologies. Second, we create an OWL ontology of important petrology terms currently described in natural language thesauri. We describe a prototype of a tool for collecting definitions from domain experts. Third, we present an approach to formalization of current industrial standards for classification of rock samples, which requires linear equations in OWL 2. In conclusion, we discuss a range of opportunities arising ...

  17. Wavelet-based integral representation for solutions of the wave equation

    Energy Technology Data Exchange (ETDEWEB)

    Perel, Maria V; Sidorenko, Mikhail S [Department of Mathematical Physics, Physics Faculty, St Petersburg University, Ulyanovskaya 1-1, Petrodvorets, St Petersburg 198904 (Russian Federation)], E-mail: perel@mph.phys.spbu.ru, E-mail: M-Sidorenko@yandex.ru

    2009-09-18

    An integral representation of solutions of the wave equation as a superposition of other solutions of this equation is built. The solutions from a wide class can be used as building blocks for the representation. Considerations are based on mathematical techniques of continuous wavelet analysis. The formulae obtained are justified from the point of view of distribution theory. A comparison of the results with those by G Kaiser is carried out. Methods of obtaining physical wavelets are discussed.

  18. 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 usin......, by masking the energy from less structured music instruments. We present four examples for visualizing structured content, including vocal and single instrument....

  19. Goal-directed attention alters the tuning of object-based representations in extrastriate cortex

    Directory of Open Access Journals (Sweden)

    Anthony J.-W. Chen

    2012-06-01

    Full Text Available Humans survive in environments that contain a vast quantity and variety of visual information. All items of perceived visual information must be represented within a limited number of brain networks. The human brain requires mechanisms for selecting only a relevant fraction of perceived information for more in-depth processing, where neural representations of that information may be actively maintained and utilized for goal-directed behavior. Object-based attention is crucial for goal-directed behavior and yet remains poorly understood. Thus, in the study we investigate how neural representations of visual object information are guided by selective attention. The magnitude of activation in human extrastriate cortex has been shown to be modulated by attention; however object-based attention is not likely to be fully explained by a localized gain mechanism. Thus, we measured information coded in spatially distributed patterns of brain activity with fMRI while human participants performed a task requiring selective processing of a relevant visual object category that differed across conditions. Using pattern classification and spatial correlation techniques, we found that the direction of selective attention is implemented as a shift in the tuning of object-based information representations within extrastriate cortex. In contrast, we found that representations within lateral prefrontal cortex coded for the attention condition rather than the concrete representations of object category. In sum, our findings are consistent with a model of object-based selective attention in which representations coded within extrastriate cortex are tuned to favor the representation of goal-relevant information, guided by more abstract representations within lateral prefrontal cortex.

  20. To move or not to move, that is the question! Body schema and non-action oriented body representations: An fMRI meta-analytic study.

    Science.gov (United States)

    Di Vita, Antonella; Boccia, Maddalena; Palermo, Liana; Guariglia, Cecilia

    2016-09-01

    Many studies have attempted to identify the different cognitive components of body representation (BR). Due to methodological issues, the data reported in these studies are often confusing. Here we summarize the fMRI data from previous studies and explore the possibility of a neural segregation between BR supporting actions (body-schema, BS) or not (non-oriented-to-action-body-representation, NA). We performed a general activation likelihood estimation meta-analysis of 59 fMRI experiments and two individual meta-analyses to identify the neural substrates of different BR. Body processing involves a wide network of areas in occipital, parietal, frontal and temporal lobes. NA selectively activates the somatosensory primary cortex and the supramarginal gyrus. BS involves the primary motor area and the right extrastriate body area. Our data suggest that motor information and recognition of body parts are fundamental to build BS. Instead, sensory information and processing of the egocentric perspective are more important for NA. In conclusion, our results strongly support the idea that different and segregated neural substrates are involved in body representations orient or not to actions.

  1. Improving the Representational Strategies of Children in a Music-Listening and Playing Task: An Intervention-Based Study

    Science.gov (United States)

    Gil, Vicent; Reybrouck, Mark; Tejada, Jesús; Verschaffel, Lieven

    2015-01-01

    This intervention-based study focuses on the relation between music and its graphic representation from a meta-representational point of view. It aims to determine whether middle school students show an increase in meta-representational competence (MRC) after an educational intervention. Three classes of 11 to 14-year-old students participated in…

  2. Intensity Estimation of Spontaneous Facial Action Units Based on Their Sparsity Properties.

    Science.gov (United States)

    Mohammadi, Mohammad Reza; Fatemizadeh, Emad; Mahoor, Mohammad H

    2016-03-01

    Automatic measurement of spontaneous facial action units (AUs) defined by the facial action coding system (FACS) is a challenging problem. The recent FACS user manual defines 33 AUs to describe different facial activities and expressions. In spontaneous facial expressions, a subset of AUs are often occurred or activated at a time. Given this fact that AUs occurred sparsely over time, we propose a novel method to detect the absence and presence of AUs and estimate their intensity levels via sparse representation (SR). We use the robust principal component analysis to decompose expression from facial identity and then estimate the intensity of multiple AUs jointly using a regression model formulated based on dictionary learning and SR. Our experiments on Denver intensity of spontaneous facial action and UNBC-McMaster shoulder pain expression archive databases show that our method is a promising approach for measurement of spontaneous facial AUs.

  3. 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.

  4. Efficient Learning of VAM-Based Representation of 3D Targets and its Active Vision Applications.

    Science.gov (United States)

    Sharma, Rajeev; Srinivasa, Narayan

    1998-01-01

    There has been a considerable interest in using active vision for various applications. This interest is primarily because active vision can enhance machine vision capabilities by dynamically changing the camera parameters based on the content of the scene. An important issue in active vision is that of representing 3D targets in a manner that is invariant to changing camera configurations. This paper addresses this representation issue for a robotic active vision system. An efficient Vector Associative Map (VAM)-based learning scheme is proposed to learn a joint-based representation. Computer simulations and experiments are first performed to evaluate the effectiveness of this scheme using the University of Illinois Active Vision System (UIAVS). The invariance property of the learned representation is then exploited to develop several robotic applications. These include, detecting moving targets, saccade control, planning saccade sequences and controlling a robot manipulator.

  5. Implicit kernel sparse shape representation: a sparse-neighbors-based objection segmentation framework.

    Science.gov (United States)

    Yao, Jincao; Yu, Huimin; Hu, Roland

    2017-01-01

    This paper introduces a new implicit-kernel-sparse-shape-representation-based object segmentation framework. Given an input object whose shape is similar to some of the elements in the training set, the proposed model can automatically find a cluster of implicit kernel sparse neighbors to approximately represent the input shape and guide the segmentation. A distance-constrained probabilistic definition together with a dualization energy term is developed to connect high-level shape representation and low-level image information. We theoretically prove that our model not only derives from two projected convex sets but is also equivalent to a sparse-reconstruction-error-based representation in the Hilbert space. Finally, a "wake-sleep"-based segmentation framework is applied to drive the evolutionary curve to recover the original shape of the object. We test our model on two public datasets. Numerical experiments on both synthetic images and real applications show the superior capabilities of the proposed framework.

  6. Assessing a New Approach to Class-Based Affirmative Action

    Science.gov (United States)

    Gaertner, Matthew N.

    2011-01-01

    In November, 2008, Colorado and Nebraska voted on amendments that sought to end race-based affirmative action at public universities. In anticipation of the vote, Colorado's flagship public institution--The University of Colorado at Boulder (CU)--explored statistical approaches to support class-based affirmative action. This paper details CU's…

  7. Edge detection based on object tree image representation and wavelet transform

    Institute of Scientific and Technical Information of China (English)

    屈彦呈; 王常虹; 庄显义

    2003-01-01

    In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time-consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.

  8. Low-rank and eigenface based sparse representation for face recognition.

    Science.gov (United States)

    Hou, Yi-Fu; Sun, Zhan-Li; Chong, Yan-Wen; Zheng, Chun-Hou

    2014-01-01

    In this paper, based on low-rank representation and eigenface extraction, we present an improvement to the well known Sparse Representation based Classification (SRC). Firstly, the low-rank images of the face images of each individual in training subset are extracted by the Robust Principal Component Analysis (Robust PCA) to alleviate the influence of noises (e.g., illumination difference and occlusions). Secondly, Singular Value Decomposition (SVD) is applied to extract the eigenfaces from these low-rank and approximate images. Finally, we utilize these eigenfaces to construct a compact and discriminative dictionary for sparse representation. We evaluate our method on five popular databases. Experimental results demonstrate the effectiveness and robustness of our method.

  9. Low-rank and eigenface based sparse representation for face recognition.

    Directory of Open Access Journals (Sweden)

    Yi-Fu Hou

    Full Text Available In this paper, based on low-rank representation and eigenface extraction, we present an improvement to the well known Sparse Representation based Classification (SRC. Firstly, the low-rank images of the face images of each individual in training subset are extracted by the Robust Principal Component Analysis (Robust PCA to alleviate the influence of noises (e.g., illumination difference and occlusions. Secondly, Singular Value Decomposition (SVD is applied to extract the eigenfaces from these low-rank and approximate images. Finally, we utilize these eigenfaces to construct a compact and discriminative dictionary for sparse representation. We evaluate our method on five popular databases. Experimental results demonstrate the effectiveness and robustness of our method.

  10. Low-dose computed tomography image denoising based on joint wavelet and sparse representation.

    Science.gov (United States)

    Ghadrdan, Samira; Alirezaie, Javad; Dillenseger, Jean-Louis; Babyn, Paul

    2014-01-01

    Image denoising and signal enhancement are the most challenging issues in low dose computed tomography (CT) imaging. Sparse representational methods have shown initial promise for these applications. In this work we present a wavelet based sparse representation denoising technique utilizing dictionary learning and clustering. By using wavelets we extract the most suitable features in the images to obtain accurate dictionary atoms for the denoising algorithm. To achieve improved results we also lower the number of clusters which reduces computational complexity. In addition, a single image noise level estimation is developed to update the cluster centers in higher PSNRs. Our results along with the computational efficiency of the proposed algorithm clearly demonstrates the improvement of the proposed algorithm over other clustering based sparse representation (CSR) and K-SVD methods.

  11. Consonant-vowel interactions in Modern Standard Latvian: a representational and constraint-based account

    Directory of Open Access Journals (Sweden)

    Olga Urek

    2016-07-01

    Full Text Available In this article I provide a representational and a constraint-based analysis of four interacting palatalization processes operative in Modern Standard Latvian: velar affrication, velar palatalization, yod-palatalization and front vowel raising. The main advantage of the representational account developed here is that it treats all of the mentioned Latvian processes as strictly assimilatory, and at the same time avoids purely stipulative mechanisms characteristic of many feature-geometric approaches to cross-category interactions. The article also contributes to the debate on the role of geometric subsegmental representations in constraint-based computational models, by demonstrating that a principled account of locality, transparency and blocking effects in Latvian palatalization requires the reference to hierarchical autosegmental structures.

  12. Extracting bimodal representations for language-based image text retrieval

    NARCIS (Netherlands)

    Westerveld, T.H.W.; Hiemstra, D.; Jong, de F.M.G.; Correia, N.; Chambel, T.; Davenport, G.

    2000-01-01

    This paper explores two approaches to multimedia indexing that might contribute to the advancement of text-based conceptual search for pictorial information. Insights from relatively mature retrieval areas (spoken document retrieval and cross-language retrieval) are taken as a starting point for an

  13. Modeling representation uncertainty in concept-based multimedia retrieval

    NARCIS (Netherlands)

    Aly, Robin Benjamin Niko

    2010-01-01

    This thesis considers concept-based multimedia retrieval, where documents are represented by the occurrence of concepts (also referred to as semantic concepts or high-level features). A concept can be thought of as a kind of label, which is attached to (parts of) the multimedia documents in which it

  14. Teaching Representations of Competency-Based Education. A Case Study

    Science.gov (United States)

    Covarrubias-Papahiu, Patricia

    2016-01-01

    The aim of this research was to know how the Competency-Based Education (CBE) approach is represented by professors who are part of the professional education of psychologists, and the challenges and implications of, in their opinion, incorporating it in the classroom practice. Therefore, a research was conducted to know the type of…

  15. 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 rece

  16. 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.

  17. Quad Tree-based Level-of-details Representation of Digital Globe

    Directory of Open Access Journals (Sweden)

    Sudhir Porwal

    2013-01-01

    Full Text Available Three-dimensional visualization of the geographic data using a digital globe model has been an integral part of a modern GIS system. The visualization of the digital globe model presents many challenges not found in traditional terrain visualization system. The representation of the digital earth (globe model is important to efficiently render the geographical data without any distortion either at equator or Polar Regions. This paper presents a uniform scheme for efficient quad tree based level-of-details (LOD representation of the digital globe to minimize the distortion at Polar Regions and meets the requirement of fast frame rate rendering.

  18. 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...

  19. 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.

  20. Is Mathematical Representation of Problems an Evidence-Based Strategy for Students with Mathematics Difficulties?

    Science.gov (United States)

    Jitendra, Asha K.; Nelson, Gena; Pulles, Sandra M.; Kiss, Allyson J.; Houseworth, James

    2016-01-01

    The purpose of the present review was to evaluate the quality of the research and evidence base for representation of problems as a strategy to enhance the mathematical performance of students with learning disabilities and those at risk for mathematics difficulties. The authors evaluated 25 experimental and quasiexperimental studies according to…

  1. Comparison of color representations for content-based image retrieval in dermatology

    NARCIS (Netherlands)

    Bosman, Hedde H.W.J.; Petkov, Nicolai; Jonkman, Marcel F.

    2010-01-01

    Background/purpose: We compare the effectiveness of 10 different color representations in a content-based image retrieval task for dermatology. Methods: As features, we use the average colors of healthy and lesion skin in an image. The extracted features are used to retrieve similar images from a da

  2. Growth Points in Linking Representations of Function: A Research-Based Framework

    Science.gov (United States)

    Ronda, Erlina

    2015-01-01

    This paper describes five growth points in linking representations of function developed from a study of secondary school learners. Framed within the cognitivist perspective and process-object conception of function, the growth points were identified and described based on linear and quadratic function tasks learners can do and their strategies…

  3. An Unsupervised Graph Based Continuous Word Representation Method for Biomedical Text Mining.

    Science.gov (United States)

    Jiang, Zhenchao; Li, Lishuang; Huang, Degen

    2016-01-01

    In biomedical text mining tasks, distributed word representation has succeeded in capturing semantic regularities, but most of them are shallow-window based models, which are not sufficient for expressing the meaning of words. To represent words using deeper information, we make explicit the semantic regularity to emerge in word relations, including dependency relations and context relations, and propose a novel architecture for computing continuous vector representation by leveraging those relations. The performance of our model is measured on word analogy task and Protein-Protein Interaction Extraction (PPIE) task. Experimental results show that our method performs overall better than other word representation models on word analogy task and have many advantages on biomedical text mining.

  4. THEORY OF GEOTROPISM BASED ON MASS ACTION.

    Science.gov (United States)

    Loeb, J

    1923-07-20

    1. It is shown that the rate of geotropic curvature of a piece of stem of Bryophyllum calycinum when suspended horizontally increases with the mass of an apical leaf attached to the stem. 2. It is shown that the dry weight of the stem increases with the mass of the leaf attached and also that the degree of curvature increases with this increase in the dry weight of the stem. 3. The conclusion is drawn that geotropic curvature is in this case a function of mass action of the material sent by the leaf into the basal part of the stem. 4. The material sent by a leaf into the apical part of a stem does not lead to the same geotropic curvature.

  5. 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.; Karban, Robert

    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.

  6. Soft-assignment random-forest with an application to discriminative representation of human actions in videos

    NARCIS (Netherlands)

    Burghouts, G.J.

    2013-01-01

    The bag-of-features model is a distinctive and robust approach to detect human actions in videos. The discriminative power of this model relies heavily on the quantization of the video features into visual words. The quantization determines how well the visual words describe the human action. Random

  7. Shape representation for efficient landmark-based segmentation in 3-d.

    Science.gov (United States)

    Ibragimov, Bulat; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2014-04-01

    In this paper, we propose a novel approach to landmark-based shape representation that is based on transportation theory, where landmarks are considered as sources and destinations, all possible landmark connections as roads, and established landmark connections as goods transported via these roads. Landmark connections, which are selectively established, are identified through their statistical properties describing the shape of the object of interest, and indicate the least costly roads for transporting goods from sources to destinations. From such a perspective, we introduce three novel shape representations that are combined with an existing landmark detection algorithm based on game theory. To reduce computational complexity, which results from the extension from 2-D to 3-D segmentation, landmark detection is augmented by a concept known in game theory as strategy dominance. The novel shape representations, game-theoretic landmark detection and strategy dominance are combined into a segmentation framework that was evaluated on 3-D computed tomography images of lumbar vertebrae and femoral heads. The best shape representation yielded symmetric surface distance of 0.75 mm and 1.11 mm, and Dice coefficient of 93.6% and 96.2% for lumbar vertebrae and femoral heads, respectively. By applying strategy dominance, the computational costs were further reduced for up to three times.

  8. 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.

  9. 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

  10. Development of action representation during adolescence as assessed from anticipatory control in a bimanual load-lifting task.

    Science.gov (United States)

    Barlaam, F; Fortin, C; Vaugoyeau, M; Schmitz, C; Assaiante, C

    2012-09-27

    The aim of this study was to explore, during adolescence, alterations in the use of a sensori-motor representation as unveiled by the measurement of anticipatory postural control in a bimanual load-lifting task. We hypothesised that adolescence constitutes a period of refinement of anticipatory postural control due to on-going updates of the body schema and sensori-motor representations. The anticipatory postural control was assessed using a bimanual load-lifting paradigm in which subjects stabilise their left postural forearm, which is supporting an object, while they use their right hand to lift up the object. Kinematics and electromyographic data were recorded in two groups of adolescents (11-13 and 14-16 years of age) and a group of adults. Age and gender effects were tested. During voluntary unloading, the postural forearm stabilisation in adolescents was still different from the adult one, suggesting that further improvement of the postural forearm stabilisation must take place after the age of 16. No differences occur in the two adolescent groups. Moreover, girls presented a better stabilisation of the postural forearm than boys, indicating an earlier refinement of anticipatory postural control. The decrease of activity over postural flexors, which ensure postural stabilisation, appeared later in adolescents with respect to adults. Delayed timing adjustments and increased variability could reflect intense developmental processes underlain by an intense period of CNS maturation during adolescence. We discuss the role of brain maturation in the refinement of sensori-motor representations and the update of body schema.

  11. Knowledge representation and rule-based solution system for dynamic programming model

    Institute of Scientific and Technical Information of China (English)

    胡祥培; 王旭茵

    2003-01-01

    A knowledge representation has been proposed using the state-space theory of Artificial Intelligencefor Dynamic Programming Model, in which a model can be defined as a six-tuple M = (I,G,O,T,D,S). Abuilding block modeling method uses the modules of a six-tuple to form a rule-based solution model. Moreover,a rule-based system has been designed and set up to solve the Dynamic Programming Model. This knowledge-based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynam-ic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Program-ming Model can also be conveniently realized in computer.

  12. Robotic applications of VAM-based invariant representation for active vision

    Science.gov (United States)

    Srinivasa, Narayan; Sharma, Rajeev

    1996-03-01

    Active vision refers to a purposeful change in the camera setup to aid the processing of visual information. An important issue in using active vision is the need to represent the 3D environment in a manner that is invariant to changing camera configurations. Conventional methods require precise knowledge of various camera parameters in order to build this representation. However, these parameters are prone to calibration errors. This motivates us to explore a neural network based approach using Vector Associative Map to learn the invariant representation of 3D point targets for active vision. An efficient learning scheme is developed that is suitable for robotic implementation. The representation thus learned is also independent of the intrinsic parameters of the imaging system, making it immune to systematic calibration errors. To evaluate the effectiveness of this scheme, computer simulations were first performed using a detailed model of the University of Illinois Active Vision System (UIAVS). This is followed by an experimental verification on the actual UIAVS. Several robotic applications are then explored that utilize the invariance property of the learned representation. These applications include motion detection, active vision based robot control, robot motion planning, and saccade sequence planning.

  13. Virtual images inspired consolidate collaborative representation-based classification method for face recognition

    Science.gov (United States)

    Liu, Shigang; Zhang, Xinxin; Peng, Yali; Cao, Han

    2016-07-01

    The collaborative representation-based classification method performs well in the field of classification of high-dimensional images such as face recognition. It utilizes training samples from all classes to represent a test sample and assigns a class label to the test sample using the representation residuals. However, this method still suffers from the problem that limited number of training sample influences the classification accuracy when applied to image classification. In this paper, we propose a modified collaborative representation-based classification method (MCRC), which exploits novel virtual images and can obtain high classification accuracy. The procedure to produce virtual images is very simple but the use of them can bring surprising performance improvement. The virtual images can sufficiently denote the features of original face images in some case. Extensive experimental results doubtlessly demonstrate that the proposed method can effectively improve the classification accuracy. This is mainly attributed to the integration of the collaborative representation and the proposed feature-information dominated virtual images.

  14. Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

    Science.gov (United States)

    Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

    2016-10-01

    Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

  15. A HIGHLY TIME-EFFICIENT DIGITAL MULTIPLIER BASED ON THE A2 BINARY REPRESENTATION

    OpenAIRE

    Hatem BOUKADIDA,; Nejib HASSEN,; Zied GAFSI,; Besbes, Kamel

    2011-01-01

    A comparative study of different types of digital multipliers based on the A2 redundant binary representation is investigated in this paper. Some techniques have been proposed and implemented using different ALTERA Stratix FPGA platforms. The principle is to try to reduce the number of partial products terms to be summed with addition trees. These techniques are based on exploiting the associative and commutative properties of the addition operation. The multiplication was achieved using four...

  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. 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.

  18. 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 abi

  19. [Antibacterial actions of denture base resin on oral bacteria].

    Science.gov (United States)

    Yamauchi, M; Nigauri, A; Yamamoto, K; Nakazato, G; Kawano, J; Kimura, K

    1989-06-01

    Antibacterial action of various denture base resins on thirteen species of bacteria were studied in vitro. Antibacterial effect of 5% tannin-fluoride preparation, 5% tannic acid and 5% chlorhexidine added to resins on these thirteen bacterial species were also investigated using heat-curing denture base resins. Fresh microwave-curing resin and pour-type resin each showed an antibacterial action on one bacterial strain. Fresh self-curing resins had antibacterial actions on several bacterial strains. However, after storage in water at 37 degrees C for one week, antibacterial action of microwave-curing and pour-type resin were diminished and self-curing resins partially lost their antibacterial actions. Denture base resin containing tannin-fluoride preparation or tannic acid showed an antibacterial effect on one bacterial strain. On the other hand, denture base resin containing chlorhexidine had an antibacterial action on eleven bacterial strains. However, color and mechanical properties of the drug-containing resins were not satisfactory.

  20. 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.

  1. Sparse Representation-Based Image Quality Index With Adaptive Sub-Dictionaries.

    Science.gov (United States)

    Li, Leida; Cai, Hao; Zhang, Yabin; Lin, Weisi; Kot, Alex C; Sun, Xingming

    2016-08-01

    Distortions cause structural changes in digital images, leading to degraded visual quality. Dictionary-based sparse representation has been widely studied recently due to its ability to extract inherent image structures. Meantime, it can extract image features with slightly higher level semantics. Intuitively, sparse representation can be used for image quality assessment, because visible distortions can cause significant changes to the sparse features. In this paper, a new sparse representation-based image quality assessment model is proposed based on the construction of adaptive sub-dictionaries. An overcomplete dictionary trained from natural images is employed to capture the structure changes between the reference and distorted images by sparse feature extraction via adaptive sub-dictionary selection. Based on the observation that image sparse features are invariant to weak degradations and the perceived image quality is generally influenced by diverse issues, three auxiliary quality features are added, including gradient, color, and luminance information. The proposed method is not sensitive to training images, so a universal dictionary can be adopted for quality evaluation. Extensive experiments on five public image quality databases demonstrate that the proposed method produces the state-of-the-art results, and it delivers consistently well performances when tested in different image quality databases.

  2. A Comparison of Parametric and Sample-Based Message Representation in Cooperative Localization

    Directory of Open Access Journals (Sweden)

    Jaime Lien

    2012-01-01

    Full Text Available Location awareness is a key enabling feature and fundamental challenge in present and future wireless networks. Most existing localization methods rely on existing infrastructure and thus lack the flexibility and robustness necessary for large ad hoc networks. In this paper, we build upon SPAWN (sum-product algorithm over a wireless network, which determines node locations through iterative message passing, but does so at a high computational cost. We compare different message representations for SPAWN in terms of performance and complexity and investigate several types of cooperation based on censoring. Our results, based on experimental data with ultra-wideband (UWB nodes, indicate that parametric message representation combined with simple censoring can give excellent performance at relatively low complexity.

  3. Optimizing Kernel PCA Using Sparse Representation-Based Classifier for MSTAR SAR Image Target Recognition

    Directory of Open Access Journals (Sweden)

    Chuang Lin

    2013-01-01

    Full Text Available Different kernels cause various class discriminations owing to their different geometrical structures of the data in the feature space. In this paper, a method of kernel optimization by maximizing a measure of class separability in the empirical feature space with sparse representation-based classifier (SRC is proposed to solve the problem of automatically choosing kernel functions and their parameters in kernel learning. The proposed method first adopts a so-called data-dependent kernel to generate an efficient kernel optimization algorithm. Then, a constrained optimization function using general gradient descent method is created to find combination coefficients varied with the input data. After that, optimized kernel PCA (KOPCA is obtained via combination coefficients to extract features. Finally, the sparse representation-based classifier is used to perform pattern classification task. Experimental results on MSTAR SAR images show the effectiveness of the proposed method.

  4. A HIGHLY TIME-EFFICIENT DIGITAL MULTIPLIER BASED ON THE A2 BINARY REPRESENTATION

    Directory of Open Access Journals (Sweden)

    Hatem BOUKADIDA,

    2011-05-01

    Full Text Available A comparative study of different types of digital multipliers based on the A2 redundant binary representation is investigated in this paper. Some techniques have been proposed and implemented using different ALTERA Stratix FPGA platforms. The principle is to try to reduce the number of partial products terms to be summed with addition trees. These techniques are based on exploiting the associative and commutative properties of the addition operation. The multiplication was achieved using four schemes which are respectively the trivial scheme, the BRAUN scheme, the BOOTH scheme and finally the Carry-Save Wallace scheme. Two input A2- Natural transcoders and one output Natural-A2 transcoder are deployed to translate between the classical and the new A2 redundant binary representation. Synthesis results show that the A2-BRAUN multiplier requires lessarea than the conventional one. It was also noticed that the A2-Wallace multiplier offers better speed performance with respect to others schemes.

  5. Uniform and Non-Uniform Single Image Deblurring Based on Sparse Representation and Adaptive Dictionary Learning

    Directory of Open Access Journals (Sweden)

    Ashwini M. Deshpande

    2014-02-01

    Full Text Available Considering the sparseness property of images, a sparse representation based iterative deblurring method is presented for single image deblurring under uniform and non-uniform motion blur. The approach taken is based on sparse and redundant representations over adaptively training dictionaries from single blurred-noisy image itself. Further, the K-SVD algorithm is used to obtain a dictionary that describes the image contents effectively. Comprehensive experimental evaluation demonstrate that the proposed framework integrating the sparseness property of images, adaptive dictionary training and iterative deblurring scheme together significantly improves the deblurring performance and is comparable with the state-of-the art deblurring algorithms and seeks a powerful solution to an ill-conditioned inverse problem.

  6. Comparison of color representations for content-based image retrieval in dermatology

    OpenAIRE

    Bosman, Hedde H.W.J.; Petkov, Nicolai; Jonkman, Marcel F.

    2010-01-01

    Background/purpose: We compare the effectiveness of 10 different color representations in a content-based image retrieval task for dermatology. Methods: As features, we use the average colors of healthy and lesion skin in an image. The extracted features are used to retrieve similar images from a database using a k-nearest-neighbor search and Euclidean distance. The images in the database are divided into four different color categories. We measure the effectiveness of retrieval by the averag...

  7. Ontology-Based Representation and Reasoning in Building Construction Cost Estimation in China

    OpenAIRE

    Xin Liu; Zhongfu Li; Shaohua Jiang

    2016-01-01

    Cost estimation is one of the most critical tasks for building construction project management. The existing building construction cost estimation methods of many countries, including China, require information from several sources, including material, labor, and equipment, and tend to be manual, time-consuming, and error-prone. To solve these problems, a building construction cost estimation model based on ontology representation and reasoning is established, which includes three major compo...

  8. Uncovering the Connection between Artist and Audience: Viewing Painted Brushstrokes Evokes Corresponding Action Representations in the Observer

    Science.gov (United States)

    Taylor, J. Eric T.; Witt, Jessica K.; Grimaldi, Phillip J.

    2012-01-01

    Observed actions are covertly and involuntarily simulated within the observer's motor system. It has been argued that simulation is involved in processing abstract, gestural paintings, as the artist's movements can be simulated by observing static brushstrokes. Though this argument is grounded in theory, empirical research has yet to examine the…

  9. Constructing visual representations

    DEFF Research Database (Denmark)

    Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

    2014-01-01

    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...... 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...

  10. Quantum representation and watermark strategy for color images based on the controlled rotation of qubits

    Science.gov (United States)

    Li, Panchi; Xiao, Hong; Li, Binxu

    2016-11-01

    In this paper, a novel quantum representation and watermarking scheme based on the controlled rotation of qubits are proposed. Firstly, a flexible representation for quantum color image (FRQCI) is proposed to facilitate the image processing tasks. Some basic image processing operations based on FRQCI representation are introduced. Then, a novel watermarking scheme for quantum images is presented. In our scheme, the carrier image is stored in the phase θ of a qubit; at the same time, the watermark image is embedded into the phase φ of a qubit, which will not affect the carrier image's visual effect. Before being embedded into the carrier image, the watermark image is scrambled to be seemingly meaningless using quantum circuits, which further ensures the security of the watermark image. All the operations mentioned above are implemented by the controlled rotation of qubits. The experimental results on the classical computer show that the proposed watermarking scheme has better visual quality under a higher embedding capacity and outperforms the existing schemes in the literature.

  11. Representation-based user interfaces for the audiovisual library of the year 2000

    Science.gov (United States)

    Aigrain, Philippe; Joly, Philippe; Lepain, Philippe; Longueville, Veronique

    1995-03-01

    The audiovisual library of the future will be based on computerized access to digitized documents. In this communication, we address the user interface issues which will arise from this new situation. One cannot simply transfer a user interface designed for the piece by piece production of some audiovisual presentation and make it a tool for accessing full-length movies in an electronic library. One cannot take a digital sound editing tool and propose it as a means to listen to a musical recording. In our opinion, when computers are used as mediations to existing contents, document representation-based user interfaces are needed. With such user interfaces, a structured visual representation of the document contents is presented to the user, who can then manipulate it to control perception and analysis of these contents. In order to build such manipulable visual representations of audiovisual documents, one needs to automatically extract structural information from the documents contents. In this communication, we describe possible visual interfaces for various temporal media, and we propose methods for the economically feasible large scale processing of documents. The work presented is sponsored by the Bibliotheque Nationale de France: it is part of the program aiming at developing for image and sound documents an experimental counterpart to the digitized text reading workstation of this library.

  12. Quantum representation and watermark strategy for color images based on the controlled rotation of qubits

    Science.gov (United States)

    Li, Panchi; Xiao, Hong; Li, Binxu

    2016-08-01

    In this paper, a novel quantum representation and watermarking scheme based on the controlled rotation of qubits are proposed. Firstly, a flexible representation for quantum color image (FRQCI) is proposed to facilitate the image processing tasks. Some basic image processing operations based on FRQCI representation are introduced. Then, a novel watermarking scheme for quantum images is presented. In our scheme, the carrier image is stored in the phase θ of a qubit; at the same time, the watermark image is embedded into the phase φ of a qubit, which will not affect the carrier image's visual effect. Before being embedded into the carrier image, the watermark image is scrambled to be seemingly meaningless using quantum circuits, which further ensures the security of the watermark image. All the operations mentioned above are implemented by the controlled rotation of qubits. The experimental results on the classical computer show that the proposed watermarking scheme has better visual quality under a higher embedding capacity and outperforms the existing schemes in the literature.

  13. 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; Smith, Sandra; Sevcikova, Zed

    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.

  14. 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%.

  15. A Novel Permutation Based Approach for Effective and Efficient Representation of Face Images under Varying Illuminations

    Directory of Open Access Journals (Sweden)

    S Natarajan

    2013-08-01

    Full Text Available Paramount importance for an automated face recognition system is the ability to enhance discriminatory power with a low-dimensional feature representation. Keeping this as a focal point, we present a novel approach for face recognition by formulating the problem of face tagging in terms of permutation. Using a fundamental concept that, dominant pixels of a person will remain dominant under varying illuminations, we develop a Permutation Matrix (PM based approach for representing face images. The proposed method is extensively evaluated on several benchmark databases under different exemplary evaluation protocols reported in the literature. Experimental results and comparative study with state-of-the-art methods suggest that the proposed approach provides a better representation of face, thereby achieving higher efficacy and lower error rates.

  16. 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.

  17. Hyperspectral image classification based on spatial and spectral features and sparse representation

    Institute of Scientific and Technical Information of China (English)

    Yang Jing-Hui; Wang Li-Guo; Qian Jin-Xi

    2014-01-01

    To minimize the low classification accuracy and low utilization of spatial information in traditional hyperspectral image classification methods, we propose a new hyperspectral image classification method, which is based on the Gabor spatial texture features and nonparametric weighted spectral features, and the sparse representation classification method (Gabor–NWSF and SRC), abbreviated GNWSF–SRC. The proposed (GNWSF–SRC) method first combines the Gabor spatial features and nonparametric weighted spectral features to describe the hyperspectral image, and then applies the sparse representation method. Finally, the classification is obtained by analyzing the reconstruction error. We use the proposed method to process two typical hyperspectral data sets with different percentages of training samples. Theoretical analysis and simulation demonstrate that the proposed method improves the classification accuracy and Kappa coefficient compared with traditional classification methods and achieves better classification performance.

  18. A joint sparse representation-based method for double-trial evoked potentials estimation.

    Science.gov (United States)

    Yu, Nannan; Liu, Haikuan; Wang, Xiaoyan; Lu, Hanbing

    2013-12-01

    In this paper, we present a novel approach to solving an evoked potentials estimating problem. Generally, the evoked potentials in two consecutive trials obtained by repeated identical stimuli of the nerves are extremely similar. In order to trace evoked potentials, we propose a joint sparse representation-based double-trial evoked potentials estimation method, taking full advantage of this similarity. The estimation process is performed in three stages: first, according to the similarity of evoked potentials and the randomness of a spontaneous electroencephalogram, the two consecutive observations of evoked potentials are considered as superpositions of the common component and the unique components; second, making use of their characteristics, the two sparse dictionaries are constructed; and finally, we apply the joint sparse representation method in order to extract the common component of double-trial observations, instead of the evoked potential in each trial. A series of experiments carried out on simulated and human test responses confirmed the superior performance of our method.

  19. Research on the Sparse Representation for Gearbox Compound Fault Features Using Wavelet Bases

    Directory of Open Access Journals (Sweden)

    Chunyan Luo

    2015-01-01

    Full Text Available The research on gearbox fault diagnosis has been gaining increasing attention in recent years, especially on single fault diagnosis. In engineering practices, there is always more than one fault in the gearbox, which is demonstrated as compound fault. Hence, it is equally important for gearbox compound fault diagnosis. Both bearing and gear faults in the gearbox tend to result in different kinds of transient impulse responses in the captured signal and thus it is necessary to propose a potential approach for compound fault diagnosis. Sparse representation is one of the effective methods for feature extraction from strong background noise. Therefore, sparse representation under wavelet bases for compound fault features extraction is developed in this paper. With the proposed method, the different transient features of both bearing and gear can be separated and extracted. Both the simulated study and the practical application in the gearbox with compound fault verify the effectiveness of the proposed method.

  20. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    This article is based on a Danish research project with young people in vulnerable positions. Young people are involved throughout the research process, including the interpretation of material produced through interviews, and discussions on how reflections and conclusions from the research should......, 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...

  1. Network Analysis Shows Novel Molecular Mechanisms of Action for Copper-Based Chemotherapy

    Science.gov (United States)

    Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique; Mejía, Carmen; Ruiz-Azuara, Lena

    2016-01-01

    The understanding of the mechanisms associated with the action of chemotherapeutic agents is fundamental to assess and account for possible side-effects of such treatments. Casiopeínas have demonstrated a cytotoxic effect by activation of pro-apoptotic processes in malignant cells. Such processes have been proved to activate the apoptotic intrinsic route, as well as cell cycle arrest. Despite this knowledge, the whole mechanism of action of Casiopeínas is yet to be completely understood. In this work we implement a systems biology approach based on two pathway analysis tools (Over-Representation Analysis and Causal Network Analysis) to observe changes in some hallmarks of cancer, induced by this copper-based chemotherapeutic agent in HeLa cell lines. We find that the metabolism of metal ions is exacerbated, as well as cell division processes being globally diminished. We also show that cellular migration and proliferation events are decreased. Moreover, the molecular mechanisms of liver protection are increased in the cell cultures under the actions of Casiopeínas, unlike the case in many other cytotoxic drugs. We argue that this chemotherapeutic agent may be promising, given its protective hepatic function, concomitant with its cytotoxic participation in the onset of apoptotic processes in malignant cells. PMID:26793116

  2. PRODUCT GENE REPRESENTATION AND ACQUISITION METHOD BASED ON POPULATION OF PRODUCT CASES

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The representation and acquisition of a product gene is a crucial problem in product evolutionary design. A new methodology of product gene representation and acquisition from a population of product cases is proposed, and the methodology for product evolutionary design based on a population of product cases is realized. By properly classifying product cases according to its product species, the populations of product cases are divided and a model is established. Knowledge of the scheme design is extracted and formulated as the function base, principle base, and structure base, which are then combined to form a product gene. Subsequently, the product gene tree is created and represented by object-oriented method. Then combining this method with the evolutionary reasoning technology, an intelligent and automatic evolutionary scheme design of product based on the population of product cases is realized. This design method will be helpful in the processing of knowledge formulation, accumulation, and reuse, and in addressing the difficulty of acquiring design knowledge in traditional design. In addition, the disadvantages of manual case adaptation and update in case-based reasoning can be eliminated. Moreover, by optimizing the design scheme in multiple levels and aspects of product function, principle, and structure etc., the level of creativity in the scheme design can be improved.

  3. Modeling the Maturation of Grip Selection Planning and Action Representation: Insights from Typical and Atypical Motor Development.

    OpenAIRE

    Ian eFuelscher; Jacqueline eWilliams; Kate eWilmut; Enticott, Peter G.; Christian eHyde

    2016-01-01

    We investigated the purported association between developmental changes in grip selection planning and improvements in an individual’s capacity to represent action at an internal level (i.e., motor imagery). Participants were groups of healthy children aged 6-7 years and 8-12 years respectively, while a group of adolescents (13-17 years) and adults (18-34 years) allowed for consideration of childhood development in the broader context of motor maturation. A group of children aged 8-12 years w...

  4. Modeling the Maturation of Grip Selection Planning and Action Representation: Insights from Typical and Atypical Motor Development

    OpenAIRE

    Fuelscher, Ian; Williams, Jacqueline; Wilmut, Kate; Enticott, Peter G.; Hyde, Christian

    2016-01-01

    We investigated the purported association between developmental changes in grip selection planning and improvements in an individual’s capacity to represent action at an internal level [i.e., motor imagery (MI)]. Participants were groups of healthy children aged 6–7 years and 8–12 years respectively, while a group of adolescents (13–17 years) and adults (18–34 years) allowed for consideration of childhood development in the broader context of motor maturation. A group of children aged 8–12 ye...

  5. 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.

  6. Exploring the potential of the theory of social representations in community-based health research--and vice versa?

    Science.gov (United States)

    Howarth, Caroline; Foster, Juliet; Dorrer, Nike

    2004-03-01

    This article seeks to demonstrate the importance of developing a dialogue between social representations theory and community approaches to researching issues of health. We show how we have used the theory within our own research to ground our findings at the level of community. The article is divided into three sections: the recognition of competing systems of knowledge; the role of representations in maintaining stigmatizing practices; and the impact of representations on identities. Each section is illustrated with material drawn from Foster's research on mental illness and Dorrer's research on women's representations of healthy eating. We conclude by arguing that, while social representations theory is a valuable tool for community-based health research, the theory would benefit from developing a more participatory methodology.

  7. Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis.

    Science.gov (United States)

    Liu, Mingxia; Zhang, Daoqiang; Adeli, Ehsan; Shen, Dinggang

    2016-07-01

    Multitemplate-based brain morphometric pattern analysis using magnetic resonance imaging has been recently proposed for automatic diagnosis of Alzheimer's disease (AD) and its prodromal stage (i.e., mild cognitive impairment or MCI). In such methods, multiview morphological patterns generated from multiple templates are used as feature representation for brain images. However, existing multitemplate-based methods often simply assume that each class is represented by a specific type of data distribution (i.e., a single cluster), while in reality, the underlying data distribution is actually not preknown. In this paper, we propose an inherent structure-based multiview leaning method using multiple templates for AD/MCI classification. Specifically, we first extract multiview feature representations for subjects using multiple selected templates and then cluster subjects within a specific class into several subclasses (i.e., clusters) in each view space. Then, we encode those subclasses with unique codes by considering both their original class information and their own distribution information, followed by a multitask feature selection model. Finally, we learn an ensemble of view-specific support vector machine classifiers based on their, respectively, selected features in each view and fuse their results to draw the final decision. Experimental results on the Alzheimer's Disease Neuroimaging Initiative database demonstrate that our method achieves promising results for AD/MCI classification, compared to the state-of-the-art multitemplate-based methods.

  8. 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.

  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. A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations.

    Science.gov (United States)

    Chen, Tao; Wu, Huanxin; Guo, Limin; Liu, Lutao

    2015-11-24

    In this paper we address the problem of off-grid direction of arrival (DOA) estimation based on sparse representations in the situation of multiple measurement vectors (MMV). A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV) to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV) problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA) is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity.

  11. A Modified Rife Algorithm for Off-Grid DOA Estimation Based on Sparse Representations

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2015-11-01

    Full Text Available In this paper we address the problem of off-grid direction of arrival (DOA estimation based on sparse representations in the situation of multiple measurement vectors (MMV. A novel sparse DOA estimation method which changes MMV problem to SMV is proposed. This method uses sparse representations based on weighted eigenvectors (SRBWEV to deal with the MMV problem. MMV problem can be changed to single measurement vector (SMV problem by using the linear combination of eigenvectors of array covariance matrix in signal subspace as a new SMV for sparse solution calculation. So the complexity of this proposed algorithm is smaller than other DOA estimation algorithms of MMV. Meanwhile, it can overcome the limitation of the conventional sparsity-based DOA estimation approaches that the unknown directions belong to a predefined discrete angular grid, so it can further improve the DOA estimation accuracy. The modified Rife algorithm for DOA estimation (MRife-DOA is simulated based on SRBWEV algorithm. In this proposed algorithm, the largest and sub-largest inner products between the measurement vector or its residual and the atoms in the dictionary are utilized to further modify DOA estimation according to the principle of Rife algorithm and the basic idea of coarse-to-fine estimation. Finally, simulation experiments show that the proposed algorithm is effective and can reduce the DOA estimation error caused by grid effect with lower complexity.

  12. An Approach to Improve the Representation of the User Model in the Web-Based Systems

    Directory of Open Access Journals (Sweden)

    Yasser A. Nada

    2011-12-01

    Full Text Available A major shortcoming of content-based approaches exists in the representation of the user model. Content-based approaches often employ term vectors to represent each user’s interest. In doing so, they ignore the semantic relations between terms of the vector space model in which indexed terms are not orthogonal and often have semantic relatedness between one another. In this paper, we improve the representation of a user model during building user model in content-based approaches by performing these steps. First is the domain concept filtering in which concepts and items of interests are compared to the domain ontology to check the relevant items to our domain using ontology based semantic similarity. Second, is incorporating semantic content into the term vectors. We use word definitions and relations provided by WordNet to perform word sense disambiguation and employ domain-specific concepts as category labels for the semantically enhanced user models. The implicit information pertaining to the user behavior was extracted from click stream data or web usage sessions captured within the web server logs. Also, our proposed approach aims to update user model, we should analysis user's history query keywords. For a certain keyword, we extract the words which have the semantic relationships with the keyword and add them into the user interest model as nodes according to semantic relationships in the WordNet.

  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. Multi-leg Searching by Adopting Graph-based Knowledge Representation

    Directory of Open Access Journals (Sweden)

    Siti Zarinah Mohd Yusof

    2011-01-01

    Full Text Available This research explores the development of multi-leg searching concept by adopting graph-based knowledge representation. The research is aimed at proposing a searching concept that is capable of providing advanced information through retrieving not only direct but continuous related information from a point. It applies maximal join concept to merge multiple information networks for supporting multi-leg searching process. Node and edge similarity concept are also applied to determine transit node and alternative edges of the same route. A working prototype of flight networks domain is developed to represent the overview of the research.

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

    Directory of Open Access Journals (Sweden)

    Helena Gómez-Adorno

    2016-01-01

    Full Text Available 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.

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

    Science.gov (United States)

    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.

  17. The role of surface-based representations of shape in visual object recognition.

    Science.gov (United States)

    Reppa, Irene; Greville, W James; Leek, E Charles

    2015-01-01

    This study contrasted the role of surfaces and volumetric shape primitives in three-dimensional object recognition. Observers (N = 50) matched subsets of closed contour fragments, surfaces, or volumetric parts to whole novel objects during a whole-part matching task. Three factors were further manipulated: part viewpoint (either same or different between component parts and whole objects), surface occlusion (comparison parts contained either visible surfaces only, or a surface that was fully or partially occluded in the whole object), and target-distractor similarity. Similarity was varied in terms of systematic variation in nonaccidental (NAP) or metric (MP) properties of individual parts. Analysis of sensitivity (d') showed a whole-part matching advantage for surface-based parts and volumes over closed contour fragments--but no benefit for volumetric parts over surfaces. We also found a performance cost in matching volumetric parts to wholes when the volumes showed surfaces that were occluded in the whole object. The same pattern was found for both same and different viewpoints, and regardless of target-distractor similarity. These findings challenge models in which recognition is mediated by volumetric part-based shape representations. Instead, we argue that the results are consistent with a surface-based model of high-level shape representation for recognition.

  18. Ontology-Based Representation and Reasoning in Building Construction Cost Estimation in China

    Directory of Open Access Journals (Sweden)

    Xin Liu

    2016-08-01

    Full Text Available Cost estimation is one of the most critical tasks for building construction project management. The existing building construction cost estimation methods of many countries, including China, require information from several sources, including material, labor, and equipment, and tend to be manual, time-consuming, and error-prone. To solve these problems, a building construction cost estimation model based on ontology representation and reasoning is established, which includes three major components, i.e., concept model ontology, work item ontology, and construction condition ontology. Using this model, the cost estimation information is modeled into OWL axioms and SWRL rules that leverage the semantically rich ontology representation to reason about cost estimation. Based on OWL axioms and SWRL rules, the cost estimation information can be translated into a set of concept models, work items, and construction conditions associated with the specific construction conditions. The proposed method is demonstrated in Protégé 3.4.8 through case studies based on the Measurement Specifications of Building Construction and Decoration Engineering taken from GB 50500-2013 (the Chinese national mandatory specifications. Finally, this research discusses the limitations of the proposed method and future research directions. The proposed method can help a building construction cost estimator extract information more easily and quickly.

  19. [Identification of transmission fluid based on NIR spectroscopy by combining sparse representation method with manifold learning].

    Science.gov (United States)

    Jiang, Lu-Lu; Luo, Mei-Fu; Zhang, Yu; Yu, Xin-Jie; Kong, Wen-Wen; Liu, Fei

    2014-01-01

    An identification method based on sparse representation (SR) combined with autoencoder network (AN) manifold learning was proposed for discriminating the varieties of transmission fluid by using near infrared (NIR) spectroscopy technology. NIR transmittance spectra from 600 to 1 800 nm were collected from 300 transmission fluid samples of five varieties (each variety consists of 60 samples). For each variety, 30 samples were randomly selected as training set (totally 150 samples), and the rest 30 ones as testing set (totally 150 samples). Autoencoder network manifold learning was applied to obtain the characteristic information in the 600-1800 nm spectra and the number of characteristics was reduced to 10. Principal component analysis (PCA) was applied to extract several relevant variables to represent the useful information of spectral variables. All of the training samples made up a data dictionary of the sparse representation (SR). Then the transmission fluid variety identification problem was reduced to the problem as how to represent the testing samples from the data dictionary (training samples data). The identification result thus could be achieved by solving the L-1 norm-based optimization problem. We compared the effectiveness of the proposed method with that of linear discriminant analysis (LDA), least squares support vector machine (LS-SVM) and sparse representation (SR) using the relevant variables selected by principal component analysis (PCA) and AN. Experimental results demonstrated that the overall identification accuracy of the proposed method for the five transmission fluid varieties was 97.33% by AN-SR, which was significantly higher than that of LDA or LS-SVM. Therefore, the proposed method can provide a new effective method for identification of transmission fluid variety.

  20. 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.

  1. 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

  2. Action prediction based on anticipatory brain potentials during simulated driving

    Science.gov (United States)

    Khaliliardali, Zahra; Chavarriaga, Ricardo; Gheorghe, Lucian Andrei; Millán, José del R.

    2015-12-01

    Objective. The ability of an automobile to infer the driver’s upcoming actions directly from neural signals could enrich the interaction of the car with its driver. Intelligent vehicles fitted with an on-board brain-computer interface able to decode the driver’s intentions can use this information to improve the driving experience. In this study we investigate the neural signatures of anticipation of specific actions, namely braking and accelerating. Approach. We investigated anticipatory slow cortical potentials in electroencephalogram recorded from 18 healthy participants in a driving simulator using a variant of the contingent negative variation (CNV) paradigm with Go and No-go conditions: count-down numbers followed by ‘Start’/‘Stop’ cue. We report decoding performance before the action onset using a quadratic discriminant analysis classifier based on temporal features. Main results. (i) Despite the visual and driving related cognitive distractions, we show the presence of anticipatory event related potentials locked to the stimuli onset similar to the widely reported CNV signal (with an average peak value of -8 μV at electrode Cz). (ii) We demonstrate the discrimination between cases requiring to perform an action upon imperative subsequent stimulus (Go condition, e.g. a ‘Red’ traffic light) versus events that do not require such action (No-go condition; e.g. a ‘Yellow’ light); with an average single trial classification performance of 0.83 ± 0.13 for braking and 0.79 ± 0.12 for accelerating (area under the curve). (iii) We show that the centro-medial anticipatory potentials are observed as early as 320 ± 200 ms before the action with a detection rate of 0.77 ± 0.12 in offline analysis. Significance. We show for the first time the feasibility of predicting the driver’s intention through decoding anticipatory related potentials during simulated car driving with high recognition rates.

  3. RSS Fingerprint Based Indoor Localization Using Sparse Representation with Spatio-Temporal Constraint.

    Science.gov (United States)

    Piao, Xinglin; Zhang, Yong; Li, Tingshu; Hu, Yongli; Liu, Hao; Zhang, Ke; Ge, Yun

    2016-11-03

    The Received Signal Strength (RSS) fingerprint-based indoor localization is an important research topic in wireless network communications. Most current RSS fingerprint-based indoor localization methods do not explore and utilize the spatial or temporal correlation existing in fingerprint data and measurement data, which is helpful for improving localization accuracy. In this paper, we propose an RSS fingerprint-based indoor localization method by integrating the spatio-temporal constraints into the sparse representation model. The proposed model utilizes the inherent spatial correlation of fingerprint data in the fingerprint matching and uses the temporal continuity of the RSS measurement data in the localization phase. Experiments on the simulated data and the localization tests in the real scenes show that the proposed method improves the localization accuracy and stability effectively compared with state-of-the-art indoor localization methods.

  4. A simple representation of energy matrix elements in terms of symmetry-invariant bases.

    Science.gov (United States)

    Cui, Peng; Wu, Jian; Zhang, Guiqing; Boyd, Russell J

    2010-02-01

    When a system under consideration has some symmetry, usually its Hamiltonian space can be parallel partitioned into a set of subspaces, which is invariant under symmetry operations. The bases that span these invariant subspaces are also invariant under the symmetry operations, and they are the symmetry-invariant bases. A standard methodology is available to construct a series of generator functions (GFs) and corresponding symmetry-adapted basis (SAB) functions from these symmetry-invariant bases. Elements of the factorized Hamiltonian and overlap matrix can be expressed in terms of these SAB functions, and their simple representations can be deduced in terms of GFs. The application of this method to the Heisenberg spin Hamiltonian is demonstrated.

  5. Method for 3D Image Representation with Reducing the Number of Frames based on Characteristics of Human Eyes

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2016-10-01

    Full Text Available Method for 3D image representation with reducing the number of frames based on characteristics of human eyes is proposed together with representation of 3D depth by changing the pixel transparency. Through experiments, it is found that the proposed method allows reduction of the number of frames by the factor of 1/6. Also, it can represent the 3D depth through visual perceptions. Thus, real time volume rendering can be done with the proposed method.

  6. Dictionary learning method for joint sparse representation-based image fusion

    Science.gov (United States)

    Zhang, Qiheng; Fu, Yuli; Li, Haifeng; Zou, Jian

    2013-05-01

    Recently, sparse representation (SR) and joint sparse representation (JSR) have attracted a lot of interest in image fusion. The SR models signals by sparse linear combinations of prototype signal atoms that make a dictionary. The JSR indicates that different signals from the various sensors of the same scene form an ensemble. These signals have a common sparse component and each individual signal owns an innovation sparse component. The JSR offers lower computational complexity compared with SR. First, for JSR-based image fusion, we give a new fusion rule. Then, motivated by the method of optimal directions (MOD), for JSR, we propose a novel dictionary learning method (MODJSR) whose dictionary updating procedure is derived by employing the JSR structure one time with singular value decomposition (SVD). MODJSR has lower complexity than the K-SVD algorithm which is often used in previous JSR-based fusion algorithms. To capture the image details more efficiently, we proposed the generalized JSR in which the signals ensemble depends on two dictionaries. MODJSR is extended to MODGJSR in this case. MODJSR/MODGJSR can simultaneously carry out dictionary learning, denoising, and fusion of noisy source images. Some experiments are given to demonstrate the validity of the MODJSR/MODGJSR for image fusion.

  7. Improving Low-dose Cardiac CT Images based on 3D Sparse Representation

    Science.gov (United States)

    Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis

    2016-03-01

    Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images.

  8. Weighted sparse representation for human ear recognition based on local descriptor

    Science.gov (United States)

    Mawloud, Guermoui; Djamel, Melaab

    2016-01-01

    A two-stage ear recognition framework is presented where two local descriptors and a sparse representation algorithm are combined. In a first stage, the algorithm proceeds by deducing a subset of the closest training neighbors to the test ear sample. The selection is based on the K-nearest neighbors classifier in the pattern of oriented edge magnitude feature space. In a second phase, the co-occurrence of adjacent local binary pattern features are extracted from the preselected subset and combined to form a dictionary. Afterward, sparse representation classifier is employed on the developed dictionary in order to infer the closest element to the test sample. Thus, by splitting up the ear image into a number of segments and applying the described recognition routine on each of them, the algorithm finalizes by attributing a final class label based on majority voting over the individual labels pointed out by each segment. Experimental results demonstrate the effectiveness as well as the robustness of the proposed scheme over leading state-of-the-art methods. Especially when the ear image is occluded, the proposed algorithm exhibits a great robustness and reaches the recognition performances outlined in the state of the art.

  9. Infrared moving small target detection based on saliency extraction and image sparse representation

    Science.gov (United States)

    Zhang, Xiaomin; Ren, Kan; Gao, Jin; Li, Chaowei; Gu, Guohua; Wan, Minjie

    2016-10-01

    Moving small target detection in infrared image is a crucial technique of infrared search and tracking system. This paper present a novel small target detection technique based on frequency-domain saliency extraction and image sparse representation. First, we exploit the features of Fourier spectrum image and magnitude spectrum of Fourier transform to make a rough extract of saliency regions and use a threshold segmentation system to classify the regions which look salient from the background, which gives us a binary image as result. Second, a new patch-image model and over-complete dictionary were introduced to the detection system, then the infrared small target detection was converted into a problem solving and optimization process of patch-image information reconstruction based on sparse representation. More specifically, the test image and binary image can be decomposed into some image patches follow certain rules. We select the target potential area according to the binary patch-image which contains salient region information, then exploit the over-complete infrared small target dictionary to reconstruct the test image blocks which may contain targets. The coefficients of target image patch satisfy sparse features. Finally, for image sequence, Euclidean distance was used to reduce false alarm ratio and increase the detection accuracy of moving small targets in infrared images due to the target position correlation between frames.

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

    Science.gov (United States)

    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 ℝ3. 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 ℝ3. 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.

  11. Decoding abstract and concrete concept representations based on single-trial fMRI data.

    Science.gov (United States)

    Wang, Jing; Baucom, Laura B; Shinkareva, Svetlana V

    2013-05-01

    Previously, multi-voxel pattern analysis has been used to decode words referring to concrete object categories. In this study we investigated if single-trial-based brain activity was sufficient to distinguish abstract (e.g., mercy) versus concrete (e.g., barn) concept representations. Multiple neuroimaging studies have identified differences in the processing of abstract versus concrete concepts based on the averaged activity across time by using univariate methods. In this study we used multi-voxel pattern analysis to decode functional magnetic resonance imaging (fMRI) data when participants perform a semantic similarity judgment task on triplets of either abstract or concrete words with similar meanings. Classifiers were trained to identify individual trials as concrete or abstract. Cross-validated accuracies for classifying trials as abstract or concrete were significantly above chance (P concrete was also reliably above chance (P concrete concepts differ in representations in terms of neural activity patterns during a short period of time across the whole brain.

  12. 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

  13. 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...

  14. 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...

  15. Representações sociais, ação política e cidadania Social representations, political action and citizenship

    Directory of Open Access Journals (Sweden)

    Flavio A. A. Goulart

    1993-12-01

    social movements, particularly concerning their notion of citizenship and the changes caused on their demands by the enhancing or inhibiting action of the state. It is essential to grasp the various dimensions of social movements, namely their cultural identity and pattern of interaction with the state. It is thus possible to clarify social actors' perceptions of "needs" and their notions of "citizenship", as well as their respective projects for political action. The concept and practice of "regulated" citizenship may be incorporated both by the state and social movements. The achievement of "full" citizenship is a historical process of social conquest, with particular significance in the way society organizes and represents its perceptions and notions about the issue. A deeper understanding of contradictions between social demands and institutional policy-making can solve the paradox displayed by the polymorphous character of these policies, which both compensate for and reproduce inequalities, in addition to enhancing and controlling political action by society. In conclusion, it is necessary to discover the whole variety and dynamics of social representations of citizenship, as a way to achieve new rights and new areas of political action for the disempowered members of society.

  16. New noise-based logic representations to avoid some problems with time complexity

    CERN Document Server

    Wen, H; Klappenecker, A; Peper, F

    2011-01-01

    Instantaneous noise-based logic can avoid time-averaging, which implies significant potential for low-power parallel operations in beyond-Moore-law-chips. However, the universe (uniform superposition) will be zero with high probability (non-zero with exponentially low probability) in the random-telegraph-wave representation thus the operations with the universe would require exponential time-complexity. To fix this deficiency, we modify the amplitudes of the signals of the L and H states and achieve an exponential speedup compared to the old situation. Another improvement concerns the identification of a single product (hyperspace) state. We introduce a time shifted noise-based logic, which is constructed by shifting each reference signal with a small time delay. This modification implies an exponential speedup of single hyperspace vector identification compared to the former case and it requires the same, O(N) complexity as in quantum computing.

  17. Generating Multiple Base-Resolution DNA Methylomes Using Reduced Representation Bisulfite Sequencing.

    Science.gov (United States)

    Chatterjee, Aniruddha; Rodger, Euan J; Stockwell, Peter A; Le Mée, Gwenn; Morison, Ian M

    2017-01-01

    Reduced representation bisulfite sequencing (RRBS) is an effective technique for profiling genome-wide DNA methylation patterns in eukaryotes. RRBS couples size selection, bisulfite conversion, and second-generation sequencing to enrich for CpG-dense regions of the genome. The progressive improvement of second-generation sequencing technologies and reduction in cost provided an opportunity to examine the DNA methylation patterns of multiple genomes. Here, we describe a protocol for sequencing multiple RRBS libraries in a single sequencing reaction to generate base-resolution methylomes. Furthermore, we provide a brief guideline for base-calling and data analysis of multiplexed RRBS libraries. These strategies will be useful to perform large-scale, genome-wide DNA methylation analysis.

  18. Site of metabolism prediction based on ab initio derived atom representations.

    Science.gov (United States)

    Finkelmann, Arndt R; Göller, Andreas H; Schneider, Gisbert

    2017-03-21

    Machine learning models for site of metabolism (SoM) prediction offer the ability to identify metabolic soft spots in low molecular weight drug molecules at low computational cost and enable data-based reactivity prediction. SoM prediction is an atom classification problem. Successful construction of machine learning models requires atom representations that capture the reactivity-determining features of a potential reaction site. We have developed a descriptor scheme that characterizes an atom's steric and electronic environment and its relative location in the molecular structure. The partial charge distributions were obtained from fast quantum mechanical calculations. We successfully trained machine learning classifiers on curated cytochrome p450 metabolism data. The models based on the new atom descriptors showed sustained accuracy for retrospective analyses of metabolism optimization campaigns and lead optimization projects from Bayer Pharmaceuticals. The results obtained demonstrate the practicality of quantum-chemistry-supported machine learning models for hit-to-lead optimization.

  19. 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.

  20. Symbolic representation based on trend features for knowledge discovery in long time series

    Institute of Scientific and Technical Information of China (English)

    Hong YIN; Shu-qiang YANG; Xiao-qian ZHU; Shao-dong MA; Lu-min ZHANG

    2015-01-01

    The symbolic representation of time series has attracted much research interest recently. The high dimensionality typical of the data is challenging, especially as the time series becomes longer. The wide distribution of sensors collecting more and more data exacerbates the problem. Representing a time series effectively is an essential task for decision-making activities such as classification, prediction, and knowledge discovery. In this paper, we propose a new symbolic representation method for long time series based on trend features, called trend feature symbolic approximation (TFSA). The method uses a two-step mechanism to segment long time series rapidly. Unlike some previous symbolic methods, it focuses on retaining most of the trend features and patterns of the original series. A time series is represented by trend symbols, which are also suitable for use in knowledge discovery, such as association rules mining. TFSA provides the lower bounding guarantee. Experimental results show that, compared with some previous methods, it not only has better segmentation efficiency and classification accuracy, but also is applicable for use in knowledge discovery from time series.

  1. Translating the representation of the tourist landscape: A corpus-based study

    Directory of Open Access Journals (Sweden)

    Gandin Stefania

    2015-06-01

    Full Text Available This paper will present a corpus-based study on the translated language of tourism, focusing in particular on the stylistics of tourist landscapes. Through a comparative analysis of a specifically designed corpus of travel articles originally written in English (namely the TourEC-Tourism English Corpus and a corpus of tourist texts translated from a variety of languages into English (namely the T-TourEC – Translational Tourism English Corpus, the study will investigate a selection of collocates, concordances and keywords related to the description and representation of tourist settings in both corpora. The aim will be that of identifying differences, aspects or practices to be potentially improved that characterize the translated language of tourism with respect to tourist texts originally written in English. Results will show that the discursive patterns of translated texts differ from the stylistic strategies typically employed in native English for the linguistic representation of landscape and settings due to phenomena of translation universals, and that these differences may affect the relating communicative functions, properties and persuasive effects of tourist promotional discourse.

  2. Stereo vision-based obstacle avoidance for micro air vehicles using an egocylindrical image space representation

    Science.gov (United States)

    Brockers, R.; Fragoso, A.; Matthies, L.

    2016-05-01

    Micro air vehicles which operate autonomously at low altitude in cluttered environments require a method for onboard obstacle avoidance for safe operation. Previous methods deploy either purely reactive approaches, mapping low-level visual features directly to actuator inputs to maneuver the vehicle around the obstacle, or deliberative methods that use on-board 3-D sensors to create a 3-D, voxel-based world model, which is then used to generate collision free 3-D trajectories. In this paper, we use forward-looking stereo vision with a large horizontal and vertical field of view and project range from stereo into a novel robot-centered, cylindrical, inverse range map we call an egocylinder. With this implementation we reduce the complexity of our world representation from a 3D map to a 2.5D image-space representation, which supports very efficient motion planning and collision checking, and allows to implement configuration space expansion as an image processing function directly on the egocylinder. Deploying a fast reactive motion planner directly on the configuration space expanded egocylinder image, we demonstrate the effectiveness of this new approach experimentally in an indoor environment.

  3. 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

  4. Talking about Pretending: Young Children's Explicit Understanding of Representation.

    Science.gov (United States)

    Watson, Anne C.; Guajardo, Nicole Ruther

    2000-01-01

    Investigated young children's ability to talk about representational aspects of pretense. Found that 5-year-olds, but very few 4-year-olds, can explain why certain actions should not be called pretending; young children discriminate between pictures of thinking and pretending based on a depiction of action; and preschoolers are less able than…

  5. Action-Based Digital Tools: Mathematics Learning in 6-Year-Old Children

    Science.gov (United States)

    Dejonckheere, Peter J. N.; Desoete, Annemie; Fonck, Nathalie; Roderiguez, Dave; Six, Leen; Vermeersch, Tine; Vermeulen, Lies

    2014-01-01

    Introduction: In the present study we used a metaphorical representation in order to stimulate the numerical competences of six-year-olds. It was expected that when properties of physical action are used for mathematical thinking or when abstract mathematical thinking is grounded in sensorimotor processes, learning gains should be more pronounced…

  6. Face recognition via edge-based Gabor feature representation for plastic surgery-altered images

    Science.gov (United States)

    Chude-Olisah, Chollette C.; Sulong, Ghazali; Chude-Okonkwo, Uche A. K.; Hashim, Siti Z. M.

    2014-12-01

    Plastic surgery procedures on the face introduce skin texture variations between images of the same person (intra-subject), thereby making the task of face recognition more difficult than in normal scenario. Usually, in contemporary face recognition systems, the original gray-level face image is used as input to the Gabor descriptor, which translates to encoding some texture properties of the face image. The texture-encoding process significantly degrades the performance of such systems in the case of plastic surgery due to the presence of surgically induced intra-subject variations. Based on the proposition that the shape of significant facial components such as eyes, nose, eyebrow, and mouth remains unchanged after plastic surgery, this paper employs an edge-based Gabor feature representation approach for the recognition of surgically altered face images. We use the edge information, which is dependent on the shapes of the significant facial components, to address the plastic surgery-induced texture variation problems. To ensure that the significant facial components represent useful edge information with little or no false edges, a simple illumination normalization technique is proposed for preprocessing. Gabor wavelet is applied to the edge image to accentuate on the uniqueness of the significant facial components for discriminating among different subjects. The performance of the proposed method is evaluated on the Georgia Tech (GT) and the Labeled Faces in the Wild (LFW) databases with illumination and expression problems, and the plastic surgery database with texture changes. Results show that the proposed edge-based Gabor feature representation approach is robust against plastic surgery-induced face variations amidst expression and illumination problems and outperforms the existing plastic surgery face recognition methods reported in the literature.

  7. Power transformer fault diagnosis model based on rough set theory with fuzzy representation

    Institute of Scientific and Technical Information of China (English)

    Li Minghua; Dong Ming; Yan Zhang

    2007-01-01

    Objective Due to the incompleteness and complexity of fault diagnosis for power transformers, a comprehensive rough-fuzzy scheme for solving fault diagnosis problems is presented. Fuzzy set theory is used both for representation of incipient faults' indications and producing a fuzzy granulation of the feature space. Rough set theory is used to obtain dependency rules that model indicative regions in the granulated feature space. The fuzzy membership functions corresponding to the indicative regions, modelled by rules, are stored as cases. Results Diagnostic conclusions are made using a similarity measure based on these membership functions. Each case involves only a reduced number of relevant features making this scheme suitable for fault diagnosis. Conclusion Superiority of this method in terms of classification accuracy and case generation is demonstrated.

  8. DOA estimation of wideband signals based on slice-sparse representation

    Science.gov (United States)

    Gan, Lu; Wang, Xiaoqing

    2013-12-01

    In this article, the direction-of-arrival (DOA) estimation problem of wideband signal sources is studied. We pass the incident signals through a bank of narrowband filters to split the array outputs into several narrowband components. Then, a novel slice-sparse representation model of the joint narrowband array covariance data is proposed in the frequency domain to enforce joint sparsity in the concatenated covariance matrix of all frequencies. Based on the greed matching pursuit algorithm, a multiple measurement slices orthogonal matching pursuit algorithm is proposed to exploit the joint frequency processing in the case of wideband scenarios. The DOA estimation is achieved by joint processing of the array covariance data at different frequency bins. The estimated performance is compared with the representative DOA estimation methods. Simulation experiments are conducted to validate the effectiveness of the proposed method.

  9. VLSI Floorplanning with Boundary Constraints Based on Single-Sequence Representation

    Science.gov (United States)

    Li, Kang; Yu, Juebang; Li, Jian

    In modern VLSI physical design, huge integration scale necessitates hierarchical design and IP reuse to cope with design complexity. Besides, interconnect delay becomes dominant to overall circuit performance. These critical factors require some modules to be placed along designated boundaries to effectively facilitate hierarchical design and interconnection optimization related problems. In this paper, boundary constraints of general floorplan are solved smoothly based on the novel representation Single-Sequence (SS). Necessary and sufficient conditions of rooms along specified boundaries of a floorplan are proposed and proved. By assigning constrained modules to proper boundary rooms, our proposed algorithm always guarantees a feasible SS code with appropriate boundary constraints in each perturbation. Time complexity of the proposed algorithm is O(n). Experimental results on MCNC benchmarks show effectiveness and efficiency of the proposed method.

  10. Control of a five motors web transport system based on the Energetic Macroscopic Representation

    Directory of Open Access Journals (Sweden)

    Hachemi Glaoui,

    2011-02-01

    Full Text Available The objective is to control a web transport system with winder and unwinder for elastic material. A physical mod-eling of this plant is made based on the general laws of physics. For this type of controlproblem, it is extremely important to prevent the occurrence of web break or fold by decoupling the web tension and the web velocity. Due to the wide-range variation of the radius and inertia of the rollers the system dynamics change considerably during the winding/unwinding process The system is composed of five paper rollers and a tensioning roller. A control structure is suggested for this system. This control is deduced from an Energetic Macroscopic Representation of the system. Neither robust control strategy nor mechanical emulation is required, but this control needs a large number of controllers.

  11. Parametric adaptive time-frequency representation based on time-sheared Gabor atoms

    Institute of Scientific and Technical Information of China (English)

    Ma Shiwei; Zhu Xiaojin; Chen Guanghua; Wang Jian; Cao Jialin

    2007-01-01

    A localized parametric time-sheared Gabor atom is derived by convolving a linear frequency modulated factor, modulating in frequency and translating in time to a dilated Gaussian function, which is the generalization of Gabor atom and is more delicate for matching most of the signals encountered in practice, especially for those having frequency dispersion characteristics. The time-frequency distribution of this atom concentrates in its time center and frequency center along energy curve, with the curve being oblique to a certain extent along the time axis. A novel parametric adaptive time-frequency distribution based on a set of the derived atoms is then proposed using a adaptive signal subspace decomposition method in frequency domain, which is non-negative time-frequency energy distribution and free of cross-term interference for multicomponent signals. The results of numerical simulation manifest the effectiveness of the approach in time-frequency representation and signal de-noising processing.

  12. Are word representations abstract or instance-based? Effects of spelling inconsistency in orthographic learning.

    Science.gov (United States)

    Burt, Jennifer S; Long, Julia

    2011-09-01

    In Experiment 1, 62 10-year-old children studied printed pseudowords with semantic information. The items were later represented in a different format for reading, with half of the items spelled in the same way as before and half displayed in a new phonologically equivalent spelling. In a dictation test, the exposure to an alternative spelling substantially increased the number of errors that matched the alternative spelling, especially in good spellers. Orthographic learning predicted word identification when accuracy on orthographic choice for words was controlled. In Experiment 2, the effects on dictation responses of exposure to a misspelling versus the correct spelling, and the interactive effect of spelling ability, were confirmed relative to a no-exposure control in adults. The results support a single-lexicon view of reading and spelling and have implications for abstractionist and instance-based theories of orthographic representations.

  13. A tuned mesh-generation strategy for image representation based on data-dependent triangulation.

    Science.gov (United States)

    Li, Ping; Adams, Michael D

    2013-05-01

    A mesh-generation framework for image representation based on data-dependent triangulation is proposed. The proposed framework is a modified version of the frameworks of Rippa and Garland and Heckbert that facilitates the development of more effective mesh-generation methods. As the proposed framework has several free parameters, the effects of different choices of these parameters on mesh quality are studied, leading to the recommendation of a particular set of choices for these parameters. A mesh-generation method is then introduced that employs the proposed framework with these best parameter choices. This method is demonstrated to produce meshes of higher quality (both in terms of squared error and subjectively) than those generated by several competing approaches, at a relatively modest computational and memory cost.

  14. An Ensemble 4D Seismic History Matching Framework with Sparse Representation Based on Wavelet Multiresolution Analysis

    CERN Document Server

    Luo, Xiaodong; Jakobsen, Morten; Nævdal, Geir

    2016-01-01

    In this work we propose an ensemble 4D seismic history matching framework for reservoir characterization. Compared to similar existing frameworks in reservoir engineering community, the proposed one consists of some relatively new ingredients, in terms of the type of seismic data in choice, wavelet multiresolution analysis for the chosen seismic data and related data noise estimation, and the use of recently developed iterative ensemble history matching algorithms. Typical seismic data used for history matching, such as acoustic impedance, are inverted quantities, whereas extra uncertainties may arise during the inversion processes. In the proposed framework we avoid such intermediate inversion processes. In addition, we also adopt wavelet-based sparse representation to reduce data size. Concretely, we use intercept and gradient attributes derived from amplitude versus angle (AVA) data, apply multilevel discrete wavelet transforms (DWT) to attribute data, and estimate noise level of resulting wavelet coeffici...

  15. Hierarchical QSAR technology based on the Simplex representation of molecular structure

    Science.gov (United States)

    Kuz'min, V. E.; Artemenko, A. G.; Muratov, E. N.

    2008-06-01

    This article is about the hierarchical quantitative structure-activity relationship technology (HiT QSAR) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solutions. In the SiRMS approach, every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality and symmetry). The level of simplex descriptors detailing increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach reported here are the absence of "molecular alignment" problems, consideration of different physical-chemical properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of the HiT QSAR approach is demonstrated by comparing it with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biological experiments, among others. The HiT QSAR is realized as a complex of computer programs known as HiT QSAR software that also includes a powerful statistical block and a number of useful utilities.

  16. Hierarchical QSAR technology based on the Simplex representation of molecular structure.

    Science.gov (United States)

    Kuz'min, V E; Artemenko, A G; Muratov, E N

    2008-01-01

    This article is about the hierarchical quantitative structure-activity relationship technology (HiT QSAR) based on the Simplex representation of molecular structure (SiRMS) and its application for different QSAR/QSP(property)R tasks. The essence of this technology is a sequential solution (with the use of the information obtained on the previous steps) to the QSAR problem by the series of enhanced models of molecular structure description [from one dimensional (1D) to four dimensional (4D)]. It is a system of permanently improved solutions. In the SiRMS approach, every molecule is represented as a system of different simplexes (tetratomic fragments with fixed composition, structure, chirality and symmetry). The level of simplex descriptors detailing increases consecutively from the 1D to 4D representation of the molecular structure. The advantages of the approach reported here are the absence of "molecular alignment" problems, consideration of different physical-chemical properties of atoms (e.g. charge, lipophilicity, etc.), the high adequacy and good interpretability of obtained models and clear ways for molecular design. The efficiency of the HiT QSAR approach is demonstrated by comparing it with the most popular modern QSAR approaches on two representative examination sets. The examples of successful application of the HiT QSAR for various QSAR/QSPR investigations on the different levels (1D-4D) of the molecular structure description are also highlighted. The reliability of developed QSAR models as predictive virtual screening tools and their ability to serve as the base of directed drug design was validated by subsequent synthetic and biological experiments, among others. The HiT QSAR is realized as a complex of computer programs known as HIT QSAR: software that also includes a powerful statistical block and a number of useful utilities.

  17. 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.

  18. 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.

  19. 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.

  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. Intention, emotion, and action: a neural theory based on semantic pointers.

    Science.gov (United States)

    Schröder, Tobias; Stewart, Terrence C; Thagard, Paul

    2014-06-01

    We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms is shown by a model that simulates psychologically important cases of intention.

  2. A sparse representation based method to classify pulmonary patterns of diffuse lung diseases.

    Science.gov (United States)

    Zhao, Wei; Xu, Rui; Hirano, Yasushi; Tachibana, Rie; Kido, Shoji

    2015-01-01

    We applied and optimized the sparse representation (SR) approaches in the computer-aided diagnosis (CAD) to classify normal tissues and five kinds of diffuse lung disease (DLD) patterns: consolidation, ground-glass opacity, honeycombing, emphysema, and nodule. By using the K-SVD which is based on the singular value decomposition (SVD) and orthogonal matching pursuit (OMP), it can achieve a satisfied recognition rate, but too much time was spent in the experiment. To reduce the runtime of the method, the K-Means algorithm was substituted for the K-SVD, and the OMP was simplified by searching the desired atoms at one time (OMP1). We proposed three SR based methods for evaluation: SR1 (K-SVD+OMP), SR2 (K-Means+OMP), and SR3 (K-Means+OMP1). 1161 volumes of interest (VOIs) were used to optimize the parameters and train each method, and 1049 VOIs were adopted to evaluate the performances of the methods. The SR based methods were powerful to recognize the DLD patterns (SR1: 96.1%, SR2: 95.6%, SR3: 96.4%) and significantly better than the baseline methods. Furthermore, when the K-Means and OMP1 were applied, the runtime of the SR based methods can be reduced by 98.2% and 55.2%, respectively. Therefore, we thought that the method using the K-Means and OMP1 (SR3) was efficient for the CAD of the DLDs.

  3. 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.

  4. 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…

  5. Minimalist knowledge representation of primary care diseases in the medrapid.info knowledge base

    Directory of Open Access Journals (Sweden)

    Pascal VanQuekelberghe

    2005-12-01

    Conclusions The 'knowledge entry' function allows fast formal representation of clinical knowledge (<14 minutes per disease and testing using the integrated quality management system. In the near future, new measures must be found to improve the problematic representation of disease time processes, descriptions, warnings and graphics to formally represent clinical knowledge using the medrapid 'knowledge entry' function.

  6. 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.

  7. 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.

  8. Accelerated reconstruction of electrical impedance tomography images via patch based sparse representation

    Science.gov (United States)

    Wang, Qi; Lian, Zhijie; Wang, Jianming; Chen, Qingliang; Sun, Yukuan; Li, Xiuyan; Duan, Xiaojie; Cui, Ziqiang; Wang, Huaxiang

    2016-11-01

    Electrical impedance tomography (EIT) reconstruction is a nonlinear and ill-posed problem. Exact reconstruction of an EIT image inverts a high dimensional mathematical model to calculate the conductivity field, which causes significant problems regarding that the computational complexity will reduce the achievable frame rate, which is considered as a major advantage of EIT imaging. The single-step method, state estimation method, and projection method were always used to accelerate reconstruction process. The basic principle of these methods is to reduce computational complexity. However, maintaining high resolution in space together with not much cost is still challenging, especially for complex conductivity distribution. This study proposes an idea to accelerate image reconstruction of EIT based on compressive sensing (CS) theory, namely, CSEIT method. The novel CSEIT method reduces the sampling rate through minimizing redundancy in measurements, so that detailed information of reconstruction is not lost. In order to obtain sparse solution, which is the prior condition of signal recovery required by CS theory, a novel image reconstruction algorithm based on patch-based sparse representation is proposed. By applying the new framework of CSEIT, the data acquisition time, or the sampling rate, is reduced by more than two times, while the accuracy of reconstruction is significantly improved.

  9. Formal TCA cycle description based on elementary actions

    Indian Academy of Sciences (India)

    Pierre Mazière; Nicolas Parisey; Marie Beurton-Aimar; Franck Molina

    2007-01-01

    Many databases propose their own structure and format to provide data describing biological processes. This heterogeneity contributes to the difficulty of large systematic and automatic functional comparisons. To overcome these problems, we have used the BioΨ formal description scheme which allows multi-level representations of biological process information. Applied to the description of the tricarboxylic acid cycle (TCA), we show that BioΨ allows the formal integration of functional information existing in current databases and make them available for further automated analysis. In addition such a formal TCA cycle process description leads to a more accurate biological process annotation which takes in account the biological context. This enables us to perform an automated comparison of the TCA cycles for seven different species based on processes rather than protein sequences. From current databases, BioΨ is able to unravel information that are already known by the biologists but are not available for automated analysis tools and simulation software, because of the lack of formal process descriptions. This use of the BioΨ description scheme to describe the TCA cycle was a key step of the MitoScop project that aims to describe and simulate mitochondrial metabolism in silico.

  10. Ordering actions for visibility. [distributed computing based on idea of atomic actions operating on data

    Science.gov (United States)

    Mckendry, M. S.

    1985-01-01

    The notion of 'atomic actions' has been considered in recent work on data integrity and reliability. It has been found that the standard database operations of 'read' and 'write' carry with them severe performance limitations. For this reason, systems are now being designed in which actions operate on 'objects' through operations with more-or-less arbitrary semantics. An object (i.e., an instance of an abstract data type) comprises data, a set of operations (procedures) to manipulate the data, and a set of invariants. An 'action' is a unit of work. It appears to be primitive to its surrounding environment, and 'atomic' to other actions. Attention is given to the conventional model of nested actions, ordering requirements, the maximum possible visibility (full visibility) for items which must be controlled by ordering constraints, item management paradigms, and requirements for blocking mechanisms which provide the required visibility.

  11. 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.

  12. DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation

    Science.gov (United States)

    Liu, Bin; Wang, Shanyi; Wang, Xiaolong

    2015-10-01

    DNA-binding proteins play an important role in most cellular processes. Therefore, it is necessary to develop an efficient predictor for identifying DNA-binding proteins only based on the sequence information of proteins. The bottleneck for constructing a useful predictor is to find suitable features capturing the characteristics of DNA binding proteins. We applied PseAAC to DNA binding protein identification, and PseAAC was further improved by incorporating the evolutionary information by using profile-based protein representation. Finally, Combined with Support Vector Machines (SVMs), a predictor called iDNAPro-PseAAC was proposed. Experimental results on an updated benchmark dataset showed that iDNAPro-PseAAC outperformed some state-of-the-art approaches, and it can achieve stable performance on an independent dataset. By using an ensemble learning approach to incorporate more negative samples (non-DNA binding proteins) in the training process, the performance of iDNAPro-PseAAC was further improved. The web server of iDNAPro-PseAAC is available at http://bioinformatics.hitsz.edu.cn/iDNAPro-PseAAC/.

  13. A cluster-based method for marine sensitive object extraction and representation

    Science.gov (United States)

    Xue, Cunjin; Dong, Qing; Qin, Lijuan

    2015-08-01

    Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.

  14. Contrast enhancement based on layered difference representation of 2D histograms.

    Science.gov (United States)

    Lee, Chulwoo; Lee, Chul; Kim, Chang-Su

    2013-12-01

    A novel contrast enhancement algorithm based on the layered difference representation of 2D histograms is proposed in this paper. We attempt to enhance image contrast by amplifying the gray-level differences between adjacent pixels. To this end, we obtain the 2D histogram h(k, k + l ) from an input image, which counts the pairs of adjacent pixels with gray-levels k and k + l , and represent the gray-level differences in a tree-like layered structure. Then, we formulate a constrained optimization problem based on the observation that the gray-level differences, occurring more frequently in the input image, should be more emphasized in the output image. We first solve the optimization problem to derive the transformation function at each layer. We then combine the transformation functions at all layers into the unified transformation function, which is used to map input gray-levels to output gray-levels. Experimental results demonstrate that the proposed algorithm enhances images efficiently in terms of both objective quality and subjective quality.

  15. Network-based representation of energy transfer in unsteady separated flow

    Science.gov (United States)

    Nair, Aditya; Taira, Kunihiko

    2015-11-01

    We construct a network-based representation of energy pathways in unsteady separated flows using a POD-Galerkin projection model. In this formulation, we regard the POD modes as the network nodes and the energy transfer between the modes as the network edges. Based on the energy transfer analysis performed by Noack et al. (2008), edge weights are characterized on the interaction graph. As an example, we examine the energy transfer within the two-dimensional incompressible flow over a circular cylinder. In particular, we analyze the energy pathways involved in flow transition from the unstable symmetric steady state to periodic shedding cycle. The growth of perturbation energy over the network is examined to highlight key features of flow physics and to determine how the energy transfer can be influenced. Furthermore, we implement closed-loop flow control on the POD-Galerkin model to alter the energy interaction path and modify the global behavior of the wake dynamics. The insights gained will be used to perform further network analysis on fluid flows with added complexity. Work supported by US Army Research Office (W911NF-14-1-0386) and US Air Force Office of Scientific Research (YIP: FA9550-13-1-0183).

  16. 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.

  17. Integrating Argument-Based Science Inquiry with Modal Representations: Impact on Science Achievement, Argumentation, and Writing Skills

    Science.gov (United States)

    Demirbag, Mehmet; Gunel, Murat

    2014-01-01

    This study aims to investigate the effect of integrating the Argument-Based Science Inquiry (ABSI) approach with multi-modal representations on students' achievement, and their argumentation and writing skills. The study was conducted with 62 female and 57 male college students at the Central Anatolian Turkish University. All participants…

  18. Uncertainty Representation and Interpretation in Model-based Prognostics Algorithms based on Kalman Filter Estimation

    Data.gov (United States)

    National Aeronautics and Space Administration — This article discusses several aspects of uncertainty represen- tation and management for model-based prognostics method- ologies based on our experience with Kalman...

  19. Alternating Coordinate-Momentum Representation for Quantum States Based on Bopp Operators for Modelling Long-Distance Coherence Aspects

    Directory of Open Access Journals (Sweden)

    Ezzat G. Bakhoum

    2015-01-01

    Full Text Available This study presents an alternating coordinate-momentum representation for propagation and transition of associated wave function, based on Bopp operators and on a certain symbolic determinant corresponding to a set of two linear equations with null free terms. It is shown that this alternating representation can justify in a good manner the patterns created through reflection/refraction of waves on nonperfectly smooth interfaces and phase correspondence of diffracted beams without the need of supplementary support functions. Correlations with Lorentz transformation of wave functions by interaction with a certain material medium (the space-time origin of a wave-train being adjusted are also presented, and supplementary aspects regarding the use of electromagnetic scalar and vector potentials for modelling evolution within this alternating representation are added.

  20. 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

  1. Blind 3D Model Watermarking Based on Multi-Resolution Representation and Fuzzy Logic

    CERN Document Server

    Tamane, Sharvari C

    2012-01-01

    Insertion of a text message, audio data or/and an image into another image or 3D model is called as a watermarking process. Watermarking has variety of applications like: Copyright Protection, Owner Identification, Copy Protection and Data Hiding etc., depending upon the type of watermark insertion algorithm. Watermark remains in the content after applying various attacks without any distortions. The blind watermarking method used in the system is based on a wavelet transform, a fuzzy inference system and a multi-resolution representation (MRR) of the 3d model. The watermark scrambled by Arnold Transform is embedded in the wavelet coefficients at third resolution level of the MRR. Fuzzy logic approach used in the method makes it to approximate the best possible gain with an accurate scaling factor so that the watermark remains invisible. The fuzzy input variables are computed for each wavelet coefficient in the 3D model. The output of the fuzzy system is a single value which is a perceptual value for each cor...

  2. Robust Texture Classification via Group-Collaboratively Representation-Based Strategy

    Institute of Scientific and Technical Information of China (English)

    Xiao-Ling Xia; Hang-Hui Huang

    2013-01-01

    In this paper, we present a simple but powerful ensemble for robust texture classification. The proposed method uses a single type of feature descriptor, i.e. scale-invariant feature transform (SIFT), and inherits the spirit of the spatial pyramid matching model (SPM). In a flexible way of partitioning the original texture images, our approach can produce sufficient informative local features and thereby form a reliable feature pond or train a new class-specific dictionary. To take full advantage of this feature pond, we develop a group-collaboratively representation-based strategy (GCRS) for the final classification. It is solved by the well-known group lasso. But we go beyond of this and propose a locality-constraint method to speed up this, named local constraint-GCRS (LC-GCRS). Experimental results on three public texture datasets demonstrate the proposed approach achieves competitive outcomes and even outperforms the state-of-the-art methods. Particularly, most of methods cannot work well when only a few samples of each category are available for training, but our approach still achieves very high classification accuracy, e.g. an average accuracy of 92.1%for the Brodatz dataset when only one image is used for training, significantly higher than any other methods.

  3. 3D face recognition based on multiple keypoint descriptors and sparse representation.

    Directory of Open Access Journals (Sweden)

    Lin Zhang

    Full Text Available Recent years have witnessed a growing interest in developing methods for 3D face recognition. However, 3D scans often suffer from the problems of missing parts, large facial expressions, and occlusions. To be useful in real-world applications, a 3D face recognition approach should be able to handle these challenges. In this paper, we propose a novel general approach to deal with the 3D face recognition problem by making use of multiple keypoint descriptors (MKD and the sparse representation-based classification (SRC. We call the proposed method 3DMKDSRC for short. Specifically, with 3DMKDSRC, each 3D face scan is represented as a set of descriptor vectors extracted from keypoints by meshSIFT. Descriptor vectors of gallery samples form the gallery dictionary. Given a probe 3D face scan, its descriptors are extracted at first and then its identity can be determined by using a multitask SRC. The proposed 3DMKDSRC approach does not require the pre-alignment between two face scans and is quite robust to the problems of missing data, occlusions and expressions. Its superiority over the other leading 3D face recognition schemes has been corroborated by extensive experiments conducted on three benchmark databases, Bosphorus, GavabDB, and FRGC2.0. The Matlab source code for 3DMKDSRC and the related evaluation results are publicly available at http://sse.tongji.edu.cn/linzhang/3dmkdsrcface/3dmkdsrc.htm.

  4. Whose place is it anyway? Representational politics in a place-based health initiative.

    Science.gov (United States)

    Rushton, Carole

    2014-03-01

    The association between place and poor health, such as chronic disease, is well documented and in recent years has given rise to public health strategies such as place-based initiatives (PBIs). This article reports on the emergence of one such initiative in Australia, in regions identified as culturally diverse and socially disadvantaged. The study draws on the intellectual resources provided by governmentality and actor-network theory to provide insights into the reasons why community actors were excluded from a new governance body established to represent their interests. Risk-thinking and representational politics determined who represented whom in the PBI partnership. Paradoxically, actors representing 'community', identified as being 'at risk', were excluded from the partnership during its translation because they were also identified as being 'a risk'. As a consequence, contrary to federal government health and social policy in Australia, it was state government interests rather than the interests of community actors that influenced decisions made in relation to local health planning and the allocation of resources.

  5. Detecting aircrafts from satellite images using saliency and conical pyramid based template representation

    Indian Academy of Sciences (India)

    SAMIK BANERJEE; NITIN GUPTA; SUKHENDU DAS; PINAKI ROY CHOWDHURY; L K SINHA

    2016-10-01

    Automatic target localization in satellite images still remains as a challenging problem in the field of computer vision. The issues involved in locating targets in satellite images are viewpoint, spectral (intensity) and scale variations. Diversity in background texture and target clutter also adds up to the complexity of the problem of localizing aircrafts in satellite images. Failure of modern feature extraction and object detection methods highlight the complexity of the problem. In the proposed work, pre-processing techniques, viz.denoising and contrast enhancement, are first used to improve the quality of the images. Then, the concept of unsupervised saliency is used to detect the potential regions of interest, which reduces the search space. Parts from the salient regions are further processed using clustering and morphological processing to get the probable regions of isolated aircraft targets. Finally, a novel conical pyramid based framework for template representation of the target samples is proposed for matching. Experimental results shown on a few satellite images exhibit the superior performance of the proposed methods.

  6. Power distribution control of CANDU reactors based on modal representation of reactor kinetics

    Energy Technology Data Exchange (ETDEWEB)

    Xia, Lingzhi, E-mail: lxia4@uwo.ca [Department of Electrical and Computer Engineering, The University of Western Ontario, London, Ontario N6A 5B9 (Canada); Jiang, Jin, E-mail: jjiang@eng.uwo.ca [Department of Electrical and Computer Engineering, The University of Western Ontario, London, Ontario N6A 5B9 (Canada); Luxat, John C., E-mail: luxatj@mcmaster.ca [Department of Engineering Physics, McMaster University, Hamilton, Ontario L8S 4L7 (Canada)

    2014-10-15

    Highlights: • Linearization of the modal synthesis model of neutronic kinetic equations for CANDU reactors. • Validation of the linearized dynamic model through closed-loop simulations by using the reactor regulating system. • Design of a LQR state feedback controller for CANDU core power distribution control. • Comparison of the results of this new controller against those of the conventional reactor regulation system. - Abstract: Modal synthesis representation of a neutronic kinetic model for a CANDU reactor core has been utilized in the analysis and synthesis for reactor control systems. Among all the mode shapes, the fundamental mode of the power distribution, which also coincides with the desired reactor power distribution during operation, is used in the control system design. The nonlinear modal models are linearized around desired operating points. Based on the linearized model, linear quadratic regulator (LQR) control approach is used to synthesize a state feedback controller. The performance of this controller has been evaluated by using the original nonlinear models under load-following conditions. It has been demonstrated that the proposed reactor control system can produce more uniform power distribution than the traditional reactor regulation systems (RRS); in particular, it is more effective in compensating the Xenon induced transients.

  7. Pulling out the Intentional Structure of Action: The Relation between Action Processing and Action Production in Infancy

    Science.gov (United States)

    Sommerville, Jessica A.; Woodward, Amanda L.

    2005-01-01

    Adults and children readily construct action representations organized with respect to an ultimate goal. These representations allow one to predict the consequences of action, interpret and describe actions, and categorize action sequences. In this paper, we explore the ontogeny of hierarchically organized action representations, and its relation…

  8. The Measure Theory of Knowledge Representation Based on Agent%基于Agent的知识表达度量理论

    Institute of Scientific and Technical Information of China (English)

    李凡长

    2001-01-01

    Agent is like human or intelligence object, which has ability to autonomy, guess, repercussion,cooperate,self-techer,mutual learning,and so on. Based on Agent, we have tried various ways to quantitative analysis for knoledge representation. From measure theory of knowledge, using measure principle of information theory,we study knowledge representation thoroughly,and regard Agent as carrier of knowledge,and give the measure theory of knowledge representation.

  9. Modality-independent representations of small quantities based on brain activation patterns.

    Science.gov (United States)

    Damarla, Saudamini Roy; Cherkassky, Vladimir L; Just, Marcel Adam

    2016-04-01

    Machine learning or MVPA (Multi Voxel Pattern Analysis) studies have shown that the neural representation of quantities of objects can be decoded from fMRI patterns, in cases where the quantities were visually displayed. Here we apply these techniques to investigate whether neural representations of quantities depicted in one modality (say, visual) can be decoded from brain activation patterns evoked by quantities depicted in the other modality (say, auditory). The main finding demonstrated, for the first time, that quantities of dots were decodable by a classifier that was trained on the neural patterns evoked by quantities of auditory tones, and vice-versa. The representations that were common across modalities were mainly right-lateralized in frontal and parietal regions. A second finding was that the neural patterns in parietal cortex that represent quantities were common across participants. These findings demonstrate a common neuronal foundation for the representation of quantities across sensory modalities and participants and provide insight into the role of parietal cortex in the representation of quantity information.

  10. 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)

  11. View-Invariant Action Recognition Based on Action Graphs%基于动作图的视角无关动作识别

    Institute of Scientific and Technical Information of China (English)

    杨跃东; 郝爱民; 褚庆军; 赵沁平; 王莉莉

    2009-01-01

    针对视角无关的动作识别,提出加权字典向量描述方法和动作图识别模型.将视频中的局部兴趣点特征和全局形状描述有机结合,形成加权字典向量的描述方法,该方法既具有兴趣点抗噪声强的优点,又可克服兴趣点无法识别静态动作的缺点.根据运动捕获、点云等三维运动数据构建能量曲线,提取关键姿势,生成基本运动单元,并通过自连接、向前连接和向后连接3种连接方式构成有向图,称为本质图.本质图向各个方向投影,根据节点近邻规则建立的有向图称为动作图.通过Na-ve Bayes训练动作图模型,采用Viterbi算法计算视频与动作图的匹配度,根据最大匹配度标定视频序列.动作图具有多角度投影和投影平滑过渡等特点,因此可识别任意角度、任意运动方向的视频序列.实验结果表明,该算法具有较好的识别效果,可识别单目视频、多目视频和多动作视频.%This paper proposes a weighted codebook vector representation and an action graph model for view-invariant human action recognition. A video is represented as a weighted codebook vector combining dynamic interest points and static shapes. This combined representation has strong noise robusticity and high classification performance on static actions. Several 3D key poses are extracted from the motion capture data or points cloud data, and a set of primitive motion segments are generated. A directed graph called Essential Graph is built of these segments according to self-link, forward-link and back-link. Action Graph is generated from the essential graph projected from a wide range of viewpoints. This paper uses Naive Bayes to train a statistical model for each node. Given an unlabeled video, Viterbi algorithm is used for computing the match score between the video and the action graph. The video is then labeled based on the maximum score. Finally, the algorithm is tested on the IXMAS dataset, and the CMU

  12. Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

    Science.gov (United States)

    He, Fei; Han, Ye; Gong, Jianting; Song, Jiazhi; Wang, Han; Li, Yanwen

    2017-03-01

    Small interfering RNAs (siRNAs) may induce to targeted gene knockdown, and the gene silencing effectiveness relies on the efficacy of the siRNA. Therefore, the task of this paper is to construct an effective siRNA prediction method. In our work, we try to describe siRNA from both quantitative and qualitative aspects. For quantitative analyses, we form four groups of effective features, including nucleotide frequencies, thermodynamic stability profile, thermodynamic of siRNA-mRNA interaction, and mRNA related features, as a new mixed representation, in which thermodynamic of siRNA-mRNA interaction is introduced to siRNA efficacy prediction for the first time to our best knowledge. And then an F-score based feature selection is employed to investigate the contribution of each feature and remove the weak relevant features. Meanwhile, we encode the siRNA sequence and existed empirical design rules as a qualitative siRNA representation. These two kinds of siRNA representations are combined to predict siRNA efficacy by supported Vector Regression (SVR) at score level. The experimental results indicate that our method may select the features with powerful discriminative ability and make the two kinds of siRNA representations work at full capacity. The prediction results also demonstrate that our method can outperform other popular siRNA efficacy prediction algorithms.

  13. Temporal Super Resolution Enhancement of Echocardiographic Images Based on Sparse Representation.

    Science.gov (United States)

    Gifani, Parisa; Behnam, Hamid; Haddadi, Farzan; Sani, Zahra Alizadeh; Shojaeifard, Maryam

    2016-01-01

    A challenging issue for echocardiographic image interpretation is the accurate analysis of small transient motions of myocardium and valves during real-time visualization. A higher frame rate video may reduce this difficulty, and temporal super resolution (TSR) is useful for illustrating the fast-moving structures. In this paper, we introduce a novel framework that optimizes TSR enhancement of echocardiographic images by utilizing temporal information and sparse representation. The goal of this method is to increase the frame rate of echocardiographic videos, and therefore enable more accurate analyses of moving structures. For the proposed method, we first derived temporal information by extracting intensity variation time curves (IVTCs) assessed for each pixel. We then designed both low-resolution and high-resolution overcomplete dictionaries based on prior knowledge of the temporal signals and a set of prespecified known functions. The IVTCs can then be described as linear combinations of a few prototype atoms in the low-resolution dictionary. We used the Bayesian compressive sensing (BCS) sparse recovery algorithm to find the sparse coefficients of the signals. We extracted the sparse coefficients and the corresponding active atoms in the low-resolution dictionary to construct new sparse coefficients corresponding to the high-resolution dictionary. Using the estimated atoms and the high-resolution dictionary, a new IVTC with more samples was constructed. Finally, by placing the new IVTC signals in the original IVTC positions, we were able to reconstruct the original echocardiography video with more frames. The proposed method does not require training of low-resolution and high-resolution dictionaries, nor does it require motion estimation; it does not blur fast-moving objects, and does not have blocking artifacts.

  14. Students and tutors' social representations of assessment in problem-based learning tutorials supporting change

    Directory of Open Access Journals (Sweden)

    Bollela Valdes R

    2009-06-01

    Full Text Available Abstract Background Medical programmes that implement problem-based learning (PBL face several challenges when introducing this innovative learning method. PBL relies on small group as the foundation of study, and tutors facilitate learning by guiding the process rather than teaching the group. One of the major challenges is the use of strategies to assess students working in small groups. Self-, peer- and tutor-assessment are integral part of PBL tutorials and they're not easy to perform, especially for non experienced students and tutors. The undergraduate PBL medical programme was introduced in 2003, and after two years the curriculum committee decided to evaluate the tutorial assessment in the new program. Methods A random group of ten students, out of a cohort of sixty, and ten tutors (out of eighteen were selected for semi-structured interviews. The social representations' theory was used to explore how the students and tutors made sense of "assessment in tutorials". The data were content analyzed using software for qualitative and quantitative processing of text according to lexicological distribution patterns. Results Even though students and tutors are aware of the broader purpose of assessment, they felt that they were not enough trained and confident to the tutorial assessment. Assigning numbers to complex behaviors on a regular basis, as in tutorials, is counter productive to cooperative group learning and self assessment. Tutors believe that students are immature and not able to assess themselves and tutors. Students believe that good grades are closely related to good oral presentation skills and also showed a corporative attitude among themselves (protecting each other from poor grades. Conclusion Faculty training on PBL tutorials' assessment process and a systematic strategy to evaluate new programs is absolutely necessary to review and correct directions. It is envisaged that planners can make better-informed decisions about

  15. 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.

  16. Multimodal sparse representation-based classification for lung needle biopsy images.

    Science.gov (United States)

    Shi, Yinghuan; Gao, Yang; Yang, Yubin; Zhang, Ying; Wang, Dong

    2013-10-01

    Lung needle biopsy image classification is a critical task for computer-aided lung cancer diagnosis. In this study, a novel method, multimodal sparse representation-based classification (mSRC), is proposed for classifying lung needle biopsy images. In the data acquisition procedure of our method, the cell nuclei are automatically segmented from the images captured by needle biopsy specimens. Then, features of three modalities (shape, color, and texture) are extracted from the segmented cell nuclei. After this procedure, mSRC goes through a training phase and a testing phase. In the training phase, three discriminative subdictionaries corresponding to the shape, color, and texture information are jointly learned by a genetic algorithm guided multimodal dictionary learning approach. The dictionary learning aims to select the topmost discriminative samples and encourage large disagreement among different subdictionaries. In the testing phase, when a new image comes, a hierarchical fusion strategy is applied, which first predicts the labels of the cell nuclei by fusing three modalities, then predicts the label of the image by majority voting. Our method is evaluated on a real image set of 4372 cell nuclei regions segmented from 271 images. These cell nuclei regions can be divided into five classes: four cancerous classes (corresponding to four types of lung cancer) plus one normal class (no cancer). The results demonstrate that the multimodal information is important for lung needle biopsy image classification. Moreover, compared to several state-of-the-art methods (LapRLS, MCMI-AB, mcSVM, ESRC, KSRC), the proposed mSRC can achieve significant improvement (mean accuracy of 88.1%, precision of 85.2%, recall of 92.8%, etc.), especially for classifying different cancerous types.

  17. Block-diagonal representations for covariance-based anomalous change detectors

    Energy Technology Data Exchange (ETDEWEB)

    Matsekh, Anna M [Los Alamos National Laboratory; Theiler, James P [Los Alamos National Laboratory

    2010-01-01

    We use singular vectors of the whitened cross-covariance matrix of two hyper-spectral images and the Golub-Kahan permutations in order to obtain equivalent tridiagonal representations of the coefficient matrices for a family of covariance-based quadratic Anomalous Change Detection (ACD) algorithms. Due to the nature of the problem these tridiagonal matrices have block-diagonal structure, which we exploit to derive analytical expressions for the eigenvalues of the coefficient matrices in terms of the singular values of the whitened cross-covariance matrix. The block-diagonal structure of the matrices of the RX, Chronochrome, symmetrized Chronochrome, Whitened Total Least Squares, Hyperbolic and Subpixel Hyperbolic Anomalous Change Detectors are revealed by the white singular value decomposition and Golub-Kahan transformations. Similarities and differences in the properties of these change detectors are illuminated by their eigenvalue spectra. We presented a methodology that provides the eigenvalue spectrum for a wide range of quadratic anomalous change detectors. Table I summarizes these results, and Fig. I illustrates them. Although their eigenvalues differ, we find that RX, HACD, Subpixel HACD, symmetrized Chronochrome, and WTLSQ share the same eigenvectors. The eigen vectors for the two variants of Chronochrome defined in (18) are different, and are different from each other, even though they share many (but not all, unless d{sub x} = d{sub y}) eigenvalues. We demonstrated that it is sufficient to compute SVD of the whitened cross covariance matrix of the data in order to almost immediately obtain highly structured sparse matrices (and their eigenvalue spectra) of the coefficient matrices of these ACD algorithms in the white SVD-transformed coordinates. Converting to the original non-white coordinates, these eigenvalues will be modified in magnitude but not in sign. That is, the number of positive, zero-valued, and negative eigenvalues will be conserved.

  18. Micro-Expression Recognition based on 2D Gabor Filter and Sparse Representation

    Science.gov (United States)

    Zheng, Hao

    2017-01-01

    Micro-expression recognition is always a challenging problem for its quick facial expression. This paper proposed a novel method named 2D Gabor filter and Sparse Representation (2DGSR) to deal with the recognition of micro-expression. In our method, 2D Gabor filter is used for enhancing the robustness of the variations due to increasing the discrimination power. While the sparse representation is applied to deal with the subtlety, and cast recognition as a sparse approximation problem. We compare our method to other popular methods in three spontaneous micro-expression recognition databases. The results show that our method has more excellent performance than other methods.

  19. Representational Thickness

    DEFF Research Database (Denmark)

    Mullins, Michael

    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......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...... by ‘professionals’ to ‘laypeople’. The thesis articulates problems in VR’s current application, specifically the CAVE and Panorama theatres, and seeks an understanding of how these problems may be addressed. The central questions that have motivated this research project are thus: What is architectural VR...

  20. Dialectical Thinking and Fairness-Based Perspectives of Affirmative Action.

    Science.gov (United States)

    Hideg, Ivona; Ferris, D Lance

    2017-02-02

    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

  1. 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.

  2. 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.

  3. Representational similarity encoding for fMRI: Pattern-based synthesis to predict brain activity using stimulus-model-similarities.

    Science.gov (United States)

    Anderson, Andrew James; Zinszer, Benjamin D; Raizada, Rajeev D S

    2016-03-01

    Patterns of neural activity are systematically elicited as the brain experiences categorical stimuli and a major challenge is to understand what these patterns represent. Two influential approaches, hitherto treated as separate analyses, have targeted this problem by using model-representations of stimuli to interpret the corresponding neural activity patterns. Stimulus-model-based-encoding synthesizes neural activity patterns by first training weights to map between stimulus-model features and voxels. This allows novel model-stimuli to be mapped into voxel space, and hence the strength of the model to be assessed by comparing predicted against observed neural activity. Representational Similarity Analysis (RSA) assesses models by testing how well the grand structure of pattern-similarities measured between all pairs of model-stimuli aligns with the same structure computed from neural activity patterns. RSA does not require model fitting, but also does not allow synthesis of neural activity patterns, thereby limiting its applicability. We introduce a new approach, representational similarity-encoding, that builds on the strengths of RSA and robustly enables stimulus-model-based neural encoding without model fitting. The approach therefore sidesteps problems associated with overfitting that notoriously confront any approach requiring parameter estimation (and is consequently low cost computationally), and importantly enables encoding analyses to be incorporated within the wider Representational Similarity Analysis framework. We illustrate this new approach by using it to synthesize and decode fMRI patterns representing the meanings of words, and discuss its potential biological relevance to encoding in semantic memory. Our new similarity-based encoding approach unites the two previously disparate methods of encoding models and RSA, capturing the strengths of both, and enabling similarity-based synthesis of predicted fMRI patterns.

  4. Sharing Control: Developing Research Literacy through Community-Based Action Research

    Science.gov (United States)

    Juergensmeyer, Erik

    2011-01-01

    This article suggests that the methodology of community-based action research provides concrete strategies for fostering effective community problem solving. To argue for a community research pedagogy, the author draws upon past and present scholarship in action research and participatory action research, experiences teaching an undergraduate…

  5. THE DEVELOPMENT OF COURSEWARE BASED ON MATHEMATICAL REPRESENTATIONS AND ARGUMENTS IN NUMBER THEORY COURSES

    Directory of Open Access Journals (Sweden)

    Cita Dwi Rosita

    2016-10-01

    Full Text Available Courseware have an important role in the achievement of the objectives of education. Nevertheless, it does not mean any learning resources can be used for a type of learning. The teacher should provide and develop materials appropriate to the characteristics and the social environment of  its student. Number Theory courses is one of the basic subjects that would be a prerequisite for courses at the next level, such as Linear Algebra, Complex Analysis, Real Analysis, Transformation Geometry, and Algebra Structure. Thus, the student’s understanding about the essential concepts that exist in this course will determine their success in studying subjects that mentioned above. In trying to understand most of the topics in Number Theory required  the abilities of mathematical argumentation and representation. The ability of argumentation is required in studying the topic of complex number system, special operations, mathematical induction, congruence and divisibility. Ability representation especially verbal representations and symbols required by almost all the topics in this course. The purpose of this paper is to describe the development of teaching and learning Number Theory materials which facilitate students to develop the ability of mathematical argumentation and representation. The model used is a Thiagarajan development model consisting phases of defining, planning, development, and deployment. This paper is restricted to the analysis of the results of the materials validation from number theory experts.

  6. 2D vario-scale representations based on real 3D structure

    NARCIS (Netherlands)

    Suba, R.; Meijers, B.M.; Van Oosterom, P.J.M.

    2013-01-01

    This paper focuses on 3D data structures supporting an alternative approach for creating 2D vario-scale maps. The smooth animated zooming functionality have lead us to investigate a volumetric representation of gradually changing vario-scale objects. In this paper, the principle of vario-scale maps

  7. 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.

  8. 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 da

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

    NARCIS (Netherlands)

    Kollöffel, 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 ex

  10. Different brains process numbers differently: structural bases of individual differences in spatial and nonspatial number representations.

    Science.gov (United States)

    Krause, Florian; Lindemann, Oliver; Toni, Ivan; Bekkering, Harold

    2014-04-01

    A dominant hypothesis on how the brain processes numerical size proposes a spatial representation of numbers as positions on a "mental number line." An alternative hypothesis considers numbers as elements of a generalized representation of sensorimotor-related magnitude, which is not obligatorily spatial. Here we show that individuals' relative use of spatial and nonspatial representations has a cerebral counterpart in the structural organization of the posterior parietal cortex. Interindividual variability in the linkage between numbers and spatial responses (faster left responses to small numbers and right responses to large numbers; spatial-numerical association of response codes effect) correlated with variations in gray matter volume around the right precuneus. Conversely, differences in the disposition to link numbers to force production (faster soft responses to small numbers and hard responses to large numbers) were related to gray matter volume in the left angular gyrus. This finding suggests that numerical cognition relies on multiple mental representations of analogue magnitude using different neural implementations that are linked to individual traits.

  11. 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…

  12. 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.

  13. The Apportionment of Liability for Damages between Employer and Union in Section 301 Actions Involving a Union's Breach of Its Duty of Fair Representation.

    Science.gov (United States)

    Linsey, James L.

    1979-01-01

    Examines the meaning and application of the Supreme Court's ruling in "Vaca v Sipes" concerning the apportionment of liability between union and employers in duty of fair representation cases. Available from the Managing Editor, Mercer Law Review, Mercer University, 1400 Coleman Avenue, Macon, Georgia 31207; single lead article issue $3.50.…

  14. Towards knowledge-based retrieval of medical images. The role of semantic indexing, image content representation and knowledge-based retrieval.

    Science.gov (United States)

    Lowe, H J; Antipov, I; Hersh, W; Smith, C A

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis.

  15. 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? Ho...... does the educational purpose affect the specific form of the constituting elements of the method?...

  16. A Joint Doppler Frequency Shift and DOA Estimation Algorithm Based on Sparse Representations for Colocated TDM-MIMO Radar

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2014-01-01

    Full Text Available We address the problem of a new joint Doppler frequency shift (DFS and direction of arrival (DOA estimation for colocated TDM-MIMO radar that is a novel technology applied to autocruise and safety driving system in recent years. The signal model of colocated TDM-MIMO radar with few transmitter or receiver channels is depicted and “time varying steering vector” model is proved. Inspired by sparse representations theory, we present a new processing scheme for joint DFS and DOA estimation based on the new input signal model of colocated TDM-MIMO radar. An ultracomplete redundancy dictionary for angle-frequency space is founded in order to complete sparse representations of the input signal. The SVD-SR algorithm which stands for joint estimation based on sparse representations using SVD decomposition with OMP algorithm and the improved M-FOCUSS algorithm which combines the classical M-FOCUSS with joint sparse recovery spectrum are applied to the new signal model’s calculation to solve the multiple measurement vectors (MMV problem. The improved M-FOCUSS algorithm can work more robust than SVD-SR and JS-SR algorithms in the aspects of coherent signals resolution and estimation accuracy. Finally, simulation experiments have shown that the proposed algorithms and schemes are feasible and can be further applied to practical application.

  17. Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

    Science.gov (United States)

    An, Gary C

    2010-01-01

    The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

  18. Noncircular Sources-Based Sparse Representation Algorithm for Direction of Arrival Estimation in MIMO Radar with Mutual Coupling

    Directory of Open Access Journals (Sweden)

    Weidong Zhou

    2016-09-01

    Full Text Available In this paper, a reweighted sparse representation algorithm based on noncircular sources is proposed, and the problem of the direction of arrival (DOA estimation for multiple-input multiple-output (MIMO radar with mutual coupling is addressed. Making full use of the special structure of banded symmetric Toeplitz mutual coupling matrices (MCM, the proposed algorithm firstly eliminates the effect of mutual coupling by linear transformation. Then, a reduced dimensional transformation is exploited to reduce the computational complexity of the proposed algorithm. Furthermore, by utilizing the noncircular feature of signals, the new extended received data matrix is formulated to enlarge the array aperture. Finally, based on the new received data, a reweighted matrix is constructed, and the proposed method further designs the joint reweighted sparse representation scheme to achieve the DOA estimation by solving the l 1 -norm constraint minimization problem. The proposed method enlarges the array aperture due to the application of signal noncircularity, and in the presence of mutual coupling, the proposed algorithm provides higher resolution and better angle estimation performance than ESPRIT-like, l 1 -SVD and l 1 -SRDML (sparse representation deterministic maximum likelihood algorithms. Numerical experiment results verify the effectiveness and advantages of the proposed method.

  19. Evaluation of the vector space representation in text-based gene clustering.

    Science.gov (United States)

    Glenisson, P; Antal, P; Mathys, J; Moreau, Y; De Moor, B

    2003-01-01

    Thanks to its increasing availability, electronic literature can now be a major source of information when developing complex statistical models where data is scarce or contains much noise. This raises the question of how to deeply integrate information from domain literature with experimental data. Evaluating what kind of statistical text representations can integrate literature knowledge in clustering still remains an unsufficiently explored topic. In this work we discuss how the bag-of-words representation can be used successfully to represent genetic annotation and free-text information coming from different databases. We demonstrate the effect of various weighting schemes and information sources in a functional clustering setup. As a quantitative evaluation, we contrast for different parameter settings the functional groupings obtained from text with those obtained from expert assessments and link each of the results to a biological discussion.

  20. Consistent sparse representations of EEG ERP and ICA components based on wavelet and chirplet dictionaries.

    Science.gov (United States)

    Qiu, Jun-Wei; Zao, John K; Wang, Peng-Hua; Chou, Yu-Hsiang

    2010-01-01

    A randomized search algorithm for sparse representations of EEG event-related potentials (ERPs) and their statistically independent components is presented. This algorithm combines greedy matching pursuit (MP) technique with covariance matrix adaptation evolution strategy (CMA-ES) to select small number of signal atoms from over-complete wavelet and chirplet dictionaries that offer best approximations of quasi-sparse ERP signals. During the search process, adaptive pruning of signal parameters was used to eliminate redundant or degenerative atoms. As a result, the CMA-ES/MP algorithm is capable of producing accurate efficient and consistent sparse representations of ERP signals and their ICA components. This paper explains the working principles of the algorithm and presents the preliminary results of its use.

  1. 面向敌方作战行动过程的本体构建%Formalized Representation and Ontology Building for Course of Enemy Campaign Action

    Institute of Scientific and Technical Information of China (English)

    崇元; 李加祥; 艾葳

    2016-01-01

    In order to make commanders at all levels consistently understand the enemy campaign at some stage and its execution, in-depth study on formal description method of enemy campaign operation action (ECOA). Based on understanding the process and essential of situation assessment, the frame of ECOA based on knowledge discovery is presented, and formal definition is put forward by using six-tuple array. Then detailed describe the concept attribute set and its hierarchical relationships of ECOA, and the ontology model of ECOA based on UML is carried out. The result shows that the research can express the whole characteristic of one EOCA, and realize share battlefield situation.%为使各级指挥员系统一致地理解敌方在某阶段作战的内涵及执行过程,对敌方作战行动过程的形式化描述方法进行深入研究.在理解态势分析过程和实质的基础上,提出基于知识发现的敌方作战行动过程构建框架,利用六元组结构给出其形式化定义.对作战行动过程中所涉及到的概念属性集及其层次关系进行详细描述,通过UML建模语言构建作战行动过程本体模型.结果表明:该研究可表达敌方在执行某一作战行动过程中的整体特征规律,并实现战场态势内容共享.

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

    OpenAIRE

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Background 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 stu...

  3. Multiple domains of parental secure base support during childhood and adolescence contribute to adolescents' representations of attachment as a secure base script.

    Science.gov (United States)

    Vaughn, Brian E; Waters, Theodore E A; Steele, Ryan D; Roisman, Glenn I; Bost, Kelly K; Truitt, Warren; Waters, Harriet S; Booth-Laforce, Cathryn

    2016-08-01

    Although attachment theory claims that early attachment representations reflecting the quality of the child's "lived experiences" are maintained across developmental transitions, evidence that has emerged over the last decade suggests that the association between early relationship quality and adolescents' attachment representations is fairly modest in magnitude. We used aspects of parenting beyond sensitivity over childhood and adolescence and early security to predict adolescents' scripted attachment representations. At age 18 years, 673 participants from the NICHD Study of Early Child Care and Youth Development completed the Attachment Script Assessment from which we derived an assessment of secure base script knowledge. Measures of secure base support from childhood through age 15 years (e.g., parental monitoring of child activity, father presence in the home) were selected as predictors and accounted for an additional 8% of the variance in secure base script knowledge scores above and beyond direct observations of sensitivity and early attachment status alone, suggesting that adolescents' scripted attachment representations reflect multiple domains of parenting. Cognitive and demographic variables also significantly increased predicted variance in secure base script knowledge by 2% each.

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

    Science.gov (United States)

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

    2015-10-01

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

  5. 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.

  6. Incoherent Dictionary Learning Method Based on Unit Norm Tight Frame and Manifold Optimization for Sparse Representation

    Directory of Open Access Journals (Sweden)

    HongZhong Tang

    2016-01-01

    Full Text Available Optimizing the mutual coherence of a learned dictionary plays an important role in sparse representation and compressed sensing. In this paper, a efficient framework is developed to learn an incoherent dictionary for sparse representation. In particular, the coherence of a previous dictionary (or Gram matrix is reduced sequentially by finding a new dictionary (or Gram matrix, which is closest to the reference unit norm tight frame of the previous dictionary (or Gram matrix. The optimization problem can be solved by restricting the tightness and coherence alternately at each iteration of the algorithm. The significant and different aspect of our proposed framework is that the learned dictionary can approximate an equiangular tight frame. Furthermore, manifold optimization is used to avoid the degeneracy of sparse representation while only reducing the coherence of the learned dictionary. This can be performed after the dictionary update process rather than during the dictionary update process. Experiments on synthetic and real audio data show that our proposed methods give notable improvements in lower coherence, have faster running times, and are extremely robust compared to several existing methods.

  7. Karhunen-Loeve Transform and Sparse Representation Based Plant Leaf Disease Recognition

    Directory of Open Access Journals (Sweden)

    Tian Jie

    2013-09-01

    Full Text Available To improve the classification accuracy rate of apple leaf disease images and solve the problem of dimension redundancy in feature extraction, Karhunen-Loeve (K-L transform and sparse representation are applied to apple leaf disease recognition. Firstly 9 color features and 8 texture features of disease leaf images are extracted and taken as feature vectors after dimensionality reduction by the K-L transform. Then, for each of apple mosaic virus, apple rust and apple alternaria leaf spot, 40 apple leaf images are selected as the training samples, whose feature vectors are made up of the dictionary of the sparse representation, respectively. Each testing sample is classified into the class with the minimal residual. The identifying results using the proposed method are analyzed and compared with those of the Support Vector Machine (SVM and original sparse representation method. The average classification accuracy rate of the proposed method is 94.18 %, which confirms its good robustness. In addition, the proposed method not only improves the plant leaf disease classification accuracy but also solves the redundancy problem of the extracted features.

  8. Uncertainty Representation of Ocean Fronts Based on Fuzzy-Rough Set Theory

    Institute of Scientific and Technical Information of China (English)

    XUE Cunjin; ZHOU Chenghu; SU Fenzhen; ZHANG Dandan

    2008-01-01

    Analysis of ocean fronts' uncertainties indicates that they result from indiseemibility of their spatial position and fuzzi-ness of their intensity. In view of this, a flow hierarchy for uncertainty representation of ocean fronts is proposed on the basis of fuzzy-rough set theory. Firstly, raster scanning and blurring are carried out on an ocean front, and the upper and lower approximate sets, the indiscernible relation in fuzzy-rough theories and related operators in fuzzy set theories are adopted to represent its uncer-tainties, then they are classified into three sets: with members one hundred pereent belonging to the ocean front, belonging to the ocean front's edge and definitely not belonging to the ocean front. Finally, the approximate precision and roughness degree are util-ized to evaluate the ocean front's degree of uncertainties and the precision of the representation. It has been proven that the method is not only capable of representing ocean fronts' uncertainties, but also provides a new theory and method for uncertainty representation of other oceanic phenomena.

  9. Comprehension and Representation in Translation

    Institute of Scientific and Technical Information of China (English)

    徐玉萍

    2010-01-01

    Transhfion is the faithful rcpresentation in one language of the thought, content, feeling and style written in another language. It involves two processes: comprehension and representation. Correct comprehension is the base for adequate representation. Criteria for good representation lies in two points: the version should be faithful to the original, and the version should be as intelligible as possible.

  10. Embedded Data Representations.

    Science.gov (United States)

    Willett, Wesley; Jansen, Yvonne; Dragicevic, Pierre

    2017-01-01

    We introduce embedded data representations, the use of visual and physical representations of data that are deeply integrated with the physical spaces, objects, and entities to which the data refers. Technologies like lightweight wireless displays, mixed reality hardware, and autonomous vehicles are making it increasingly easier to display data in-context. While researchers and artists have already begun to create embedded data representations, the benefits, trade-offs, and even the language necessary to describe and compare these approaches remain unexplored. In this paper, we formalize the notion of physical data referents - the real-world entities and spaces to which data corresponds - and examine the relationship between referents and the visual and physical representations of their data. We differentiate situated representations, which display data in proximity to data referents, and embedded representations, which display data so that it spatially coincides with data referents. Drawing on examples from visualization, ubiquitous computing, and art, we explore the role of spatial indirection, scale, and interaction for embedded representations. We also examine the tradeoffs between non-situated, situated, and embedded data displays, including both visualizations and physicalizations. Based on our observations, we identify a variety of design challenges for embedded data representation, and suggest opportunities for future research and applications.

  11. A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text

    Directory of Open Access Journals (Sweden)

    Mujiono Sadikin

    2016-01-01

    Full Text Available One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug, the lack of labeled dataset sources and external knowledge, and the multiple token representations for a single drug name. Although many approaches have been proposed to overwhelm the task, some problems remained with poor F-score performance (less than 0.75. This paper presents a new treatment in data representation techniques to overcome some of those challenges. We propose three data representation techniques based on the characteristics of word distribution and word similarities as a result of word embedding training. The first technique is evaluated with the standard NN model, that is, MLP. The second technique involves two deep network classifiers, that is, DBN and SAE. The third technique represents the sentence as a sequence that is evaluated with a recurrent NN model, that is, LSTM. In extracting the drug name entities, the third technique gives the best F-score performance compared to the state of the art, with its average F-score being 0.8645.

  12. Prediction of S-Nitrosylation Modification Sites Based on Kernel Sparse Representation Classification and mRMR Algorithm

    Directory of Open Access Journals (Sweden)

    Guohua Huang

    2014-01-01

    Full Text Available Protein S-nitrosylation plays a very important role in a wide variety of cellular biological activities. Hitherto, accurate prediction of S-nitrosylation sites is still of great challenge. In this paper, we presented a framework to computationally predict S-nitrosylation sites based on kernel sparse representation classification and minimum Redundancy Maximum Relevance algorithm. As much as 666 features derived from five categories of amino acid properties and one protein structure feature are used for numerical representation of proteins. A total of 529 protein sequences collected from the open-access databases and published literatures are used to train and test our predictor. Computational results show that our predictor achieves Matthews’ correlation coefficients of 0.1634 and 0.2919 for the training set and the testing set, respectively, which are better than those of k-nearest neighbor algorithm, random forest algorithm, and sparse representation classification algorithm. The experimental results also indicate that 134 optimal features can better represent the peptides of protein S-nitrosylation than the original 666 redundant features. Furthermore, we constructed an independent testing set of 113 protein sequences to evaluate the robustness of our predictor. Experimental result showed that our predictor also yielded good performance on the independent testing set with Matthews’ correlation coefficients of 0.2239.

  13. A Robust Approach for Action Recognition Based on Spatio-Temporal Features in RGB-D Sequences

    Directory of Open Access Journals (Sweden)

    Ly Quoc Ngoc

    2016-05-01

    Full Text Available Recognizing human action is attractive research topic in computer vision since it plays an important role on the applications such as human-computer interaction, intelligent surveillance, human actions retrieval system, health care, smart home, robotics and so on. The availability the low-cost Microsoft Kinect sensor, which can capture real-time high-resolution RGB and visual depth information, has opened an opportunity to significantly increase the capabilities of many automated vision based recognition tasks. In this paper, we propose new framework for action recognition in RGB-D video. We extract spatiotemporal features from RGB-D data that capture both visual, shape and motion information. Moreover, the segmentation technique is applied to present the temporal structure of action. Firstly, we use STIP to detect interest points both of RGB and depth channels. Secondly, we apply HOG3D descriptor for RGB channel and 3DS-HONV descriptor for depth channel. In addition, we also extract HOF2.5D from fusing RGB and Depth to capture human’s motion. Thirdly, we divide the video into segments and apply GMM to create feature vectors for each segment. So, we have three feature vectors (HOG3D, 3DS-HONV, and HOF2.5D that represent for each segment. Next, the max pooling technique is applied to create a final vector for each descriptor. Then, we concatenate the feature vectors from the previous step into the final vector for action representation. Lastly, we use SVM method for classification step. We evaluated our proposed method on three benchmark datasets to demonstrate generalizability. And, the experimental results shown to be more accurate for action recognition compared to the previous works. We obtain overall accuracies of 93.5%, 99.16% and 89.38% with our proposed method on the UTKinect-Action, 3D Action Pairs and MSR-Daily Activity 3D dataset, respectively. These results show that our method is feasible and superior performance over the

  14. Community-based knowledge transfer and exchange: Helping community-based organizations link research to action

    Directory of Open Access Journals (Sweden)

    Lavis John N

    2010-04-01

    Full Text Available Abstract Background Community-based organizations (CBOs are important stakeholders in health systems and are increasingly called upon to use research evidence to inform their advocacy, program planning, and service delivery efforts. CBOs increasingly turn to community-based research (CBR given its participatory focus and emphasis on linking research to action. In order to further facilitate the use of research evidence by CBOs, we have developed a strategy for community-based knowledge transfer and exchange (KTE that helps CBOs more effectively link research evidence to action. We developed the strategy by: outlining the primary characteristics of CBOs and why they are important stakeholders in health systems; describing the concepts and methods for CBR and for KTE; comparing the efforts of CBR to link research evidence to action to those discussed in the KTE literature; and using the comparison to develop a framework for community-based KTE that builds on both the strengths of CBR and existing KTE frameworks. Discussion We find that CBR is particularly effective at fostering a climate for using research evidence and producing research evidence relevant to CBOs through community participation. However, CBOs are not always as engaged in activities to link research evidence to action on a larger scale or to evaluate these efforts. Therefore, our strategy for community-based KTE focuses on: an expanded model of 'linkage and exchange' (i.e., producers and users of researchers engaging in a process of asking and answering questions together; a greater emphasis on both producing and disseminating systematic reviews that address topics of interest to CBOs; developing a large-scale evidence service consisting of both 'push' efforts and efforts to facilitate 'pull' that highlight actionable messages from community relevant systematic reviews in a user-friendly way; and rigorous evaluations of efforts for linking research evidence to action. Summary

  15. 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,…

  16. 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.

  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. Unsupervised learning of reflexive and action-based affordances to model adaptive navigational behavior

    Directory of Open Access Journals (Sweden)

    Daniel Weiller

    2010-05-01

    Full Text Available Here we introduce a cognitive model capable to model a variety of behavioral domains and apply it to a navigational task. We used place cells as sensory representation, such that the cells’ place fields divided the environment into discrete states. The robot learns knowledge of the environment by memorizing the sensory outcome of its motor actions. This is composed of a central process, learning the probability of state-to-state transitions by motor actions and a distal processing routine, learning the extent to which these state-to-state transitions are caused by sensory-driven reflex behavior (obstacle avoidance. Navigational decision making integrates central and distal learned environmental knowledge to select an action that leads to a goal state. Differentiating distal and central processing increases the behavioral accuracy of the selected actions and the ability of behavioral adaptation to a changed environment. We propose that the system can canonically be expanded to model other behaviors, using alternative definitions of states and actions. The emphasis of this paper is to test this general cognitive model on a robot in a real world environment

  19. 基于多重核的稀疏表示分类%Multiple Kernel Sparse Representation-Based Classification

    Institute of Scientific and Technical Information of China (English)

    陈思宝; 许立仙; 罗斌

    2014-01-01

    稀疏表示分类(SRC )及核方法在模式识别的很多问题中都得到了成功的运用。为了提高其分类精度,提出多重核稀疏表示及其分类(MKSRC )方法。提出一种快速求解稀疏系数的优化迭代方法并给出了其收敛到全局最优解的证明。对于多重核的权重给出了两种自动更新方式并进行了分析与比较。在不同的人脸图像库上的分类实验显示了所提出的多重核稀疏表示分类的优越性。%Sparse representation based classification (SRC) and kernel methods are applied in many pattern recognition prob-lems .In order to improve the classification accuracy ,we propose multiple kernel sparse representation based classification (MK-SRC) .A fast optimization iteration method to solve sparse coefficients and the associated convergence proof to global optimal solu-tion are given .In order to update the kernel weights of MKSRC ,two different updating methods and the associated comparison are given .The experimental results on three face image databases show the superiority of the proposed multiple kernel sparse representa-tion based classification .

  20. 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.

  1. 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.

  2. The fusiform face area is engaged in holistic, not parts-based, representation of faces.

    Directory of Open Access Journals (Sweden)

    Jiedong Zhang

    Full Text Available Numerous studies with functional magnetic resonance imaging have shown that the fusiform face area (FFA in the human brain plays a key role in face perception. Recent studies have found that both the featural information of faces (e.g., eyes, nose, and mouth and the configural information of faces (i.e., spatial relation among features are encoded in the FFA. However, little is known about whether the featural information is encoded independent of or combined with the configural information in the FFA. Here we used multi-voxel pattern analysis to examine holistic representation of faces in the FFA by correlating spatial patterns of activation with behavioral performance in discriminating face parts with face configurations either present or absent. Behaviorally, the absence of face configurations (versus presence impaired discrimination of face parts, suggesting a holistic representation in the brain. Neurally, spatial patterns of activation in the FFA were more similar among correct than incorrect trials only when face parts were presented in a veridical face configuration. In contrast, spatial patterns of activation in the occipital face area, as well as the object-selective lateral occipital complex, were more similar among correct than incorrect trials regardless of the presence of veridical face configurations. This finding suggests that in the FFA faces are represented not on the basis of individual parts but in terms of the whole that emerges from the parts.

  3. 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.

  4. The Statistical Coherence-based Theory of Robust Recovery of Sparsest Overcomplete Representation

    CERN Document Server

    Li, Lianlin

    2011-01-01

    The recovery of sparsest overcomplete representation has recently attracted intensive research activities owe to its important potential in the many applied fields such as signal processing, medical imaging, communication, and so on. This problem can be stated in the following, i.e., to seek for the sparse coefficient vector of the given noisy observation over a redundant dictionary such that, where is the corrupted error. Elad et al. made the worst-case result, which shows the condition of stable recovery of sparest overcomplete representation over is where . Although it's of easy operation for any given matrix, this result can't provide us realistic guide in many cases. On the other hand, most of popular analysis on the sparse reconstruction relies heavily on the so-called RIP (Restricted Isometric Property) for matrices developed by Candes et al., which is usually very difficult or impossible to be justified for a given measurement matrix. In this article, we introduced a simple and efficient way of determ...

  5. 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.

  6. Theoretical base of the approach to the representation of aggregate information on the cross sections of the scattering processes

    Directory of Open Access Journals (Sweden)

    Alla A. Mityureva

    2015-12-01

    Full Text Available In the present paper, the approach to the representation of aggregate information on the cross sections of elementary processes is described and its justification within mathematical statistics is given. It is caused by necessity of integrated account of the results obtained by different works at different times, in different groups, based on experimental and theoretical studies in various energy ranges. The main attention is paid to the process of electron-atom scattering. As an example of the proposed approach application, the aggregate result on thus obtained integral cross sections of electron impact excitation of the transitions in the hydrogen atom is presented.

  7. 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.

  8. Application and Methodology of Knowledge Representation Based on Semantic Web%语义Web 知识表示方法及应用

    Institute of Scientific and Technical Information of China (English)

    杜来红

    2011-01-01

    To meet the requirement of knowledge representation, discovery and management for networked environment, methodology of knowledge representation based on semantic Web is put forward.Then as an example,enterprise resource semantic Web knowledge representation is realized by Protégé platform.%为满足网络环境下知识表示、发现和管理的需求,提出了基于语义Web的知识表示方案.以企业资源知识表示为例,利用Protege工具实现了企业资源知识的语义Web表示.

  9. Curve/surface representation and evolution using vector level sets with application to the shape-based segmentation problem.

    Science.gov (United States)

    Abd El Munim, Hossam E; Farag, Aly A

    2007-06-01

    In this paper, we revisit the implicit front representation and evolution using the vector level set function (VLSF) proposed in [1]. Unlike conventional scalar level sets, this function is designed to have a vector form. The distance from any point to the nearest point on the front has components (projections) in the coordinate directions included in the vector function. This kind of representation is used to evolve closed planar curves and 3D surfaces as well. Maintaining the VLSF property as the distance projections through evolution will be considered together with a detailed derivation of the vector partial differential equation (PDE) for such evolution. A shape-based segmentation framework will be demonstrated as an application of the given implicit representation. The proposed level set function system will be used to represent shapes to give a dissimilarity measure in a variational object registration process. This kind of formulation permits us to better control the process of shape registration, which is an important part in the shape-based segmentation framework. The method depends on a set of training shapes used to build a parametric shape model. The color is taken into consideration besides the shape prior information. The shape model is fitted to the image volume by registration through an energy minimization problem. The approach overcomes the conventional methods problems like point correspondences and weighing coefficients tuning of the evolution (PDEs). It is also suitable for multidimensional data and computationally efficient. Results in 2D and 3D of real and synthetic data will demonstrate the efficiency of the framework.

  10. Nonsymmorphic Weyl superconductivity in UPt3 based on E2 u representation

    Science.gov (United States)

    Yanase, Youichi

    2016-11-01

    We show that a heavy fermion superconductor UPt3 is a topological Weyl superconductor with tunable Weyl nodes. Adopting a generic order parameter in the E2 u representation allowed by nonsymmorphic crystal symmetry, we clarify unusual gap structure and associated topological properties. The pair creation, pair annihilation, and coalescence of Weyl nodes are demonstrated in the time-reversal symmetry broken B-phase. At most 98 point nodes compatible with Blount's theorem give rise to line-node-like behaviors in low-energy excitations, consistent with experimental results. We also show an arc node protected by the nonsymmorphic crystal symmetry on the Brillouin zone face, which is a counterexample of Blount's theorem.

  11. Multi-objective analysis of a component-based representation within an interactive evolutionary design system

    Science.gov (United States)

    Machwe, A. T.; Parmee, I. C.

    2007-07-01

    This article describes research relating to a user-centered evolutionary design system that evaluates both engineering and aesthetic aspects of design solutions during early-stage conceptual design. The experimental system comprises several components relating to user interaction, problem representation, evolutionary search and exploration and online learning. The main focus of the article is the evolutionary aspect of the system when using a single quantitative objective function plus subjective judgment of the user. Additionally, the manner in which the user-interaction aspect affects system output is assessed by comparing Pareto frontiers generated with and without user interaction via a multi-objective evolutionary algorithm (MOEA). A solution clustering component is also introduced and it is shown how this can improve the level of support to the designer when dealing with a complex design problem involving multiple objectives. Supporting results are from the application of the system to the design of urban furniture which, in this case, largely relates to seating design.

  12. Dynamics of Random Boolean Networks under Fully Asynchronous Stochastic Update Based on Linear Representation

    Science.gov (United States)

    Luo, Chao; Wang, Xingyuan

    2013-01-01

    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 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. PMID:23785502

  13. Change Energy Image for Gait Recognition: An Approach Based on Symbolic Representation

    Directory of Open Access Journals (Sweden)

    Mohan Kumar H P

    2014-03-01

    Full Text Available Gait can be identified by observing static and dynamic parts of human body. In this paper a variant of gait energy image called change energy images (CEI are generated to capture detailed static and dynamic information of human gait. Radon transform is applied to CEI in four different directions (vertical, horizontal and two opposite cross sections considering four different angles to compute discriminative feature values. The extracted features are represented in the form of interval –valued type symbolic data. The proposed method is capable of recognizing an individual when he/she have variations in their gait due to different clothes they wear, in different normal conditions and carrying a bag. A similarity measure suitable for the proposed gait representation is explored for the purpose of establishing similarity match for gait recognition. Experiments are conducted on CASIA database B and the results have shown better recognition performance compared to some of the existing methods.

  14. Topology optimization of support structure of telescope skin based on bit-matrix representation NSGA-II

    Institute of Scientific and Technical Information of China (English)

    Liu Weidong; Zhu Hua; Wang Yiping; Zhou Shengqiang; Bai Yalei; Zhao Chunsheng

    2013-01-01

    Non-dominated sorting genetic algorithm II (NSGA-II) with multiple constraints han-dling is employed for multi-objective optimization of the topological structure of telescope skin, in which a bit-matrix is used as the representation of a chromosome, and genetic algorithm (GA) operators are introduced based on the matrix. Objectives including mass, in-plane performance, and out-of-plane load-bearing ability of the individuals are obtained by finite element analysis (FEA) using ANSYS, and the matrix-based optimization algorithm is realized in MATLAB by han-dling multiple constraints such as structural connectivity and in-plane strain requirements. Feasible configurations of the support structure are achieved. The results confirm that the matrix-based NSGA-II with multiple constraints handling provides an effective method for two-dimensional multi-objective topology optimization.

  15. When Simple Harmonic Motion is not That Simple: Managing Epistemological Complexity by Using Computer-based Representations

    Science.gov (United States)

    Parnafes, Orit

    2010-12-01

    Many real-world phenomena, even "simple" physical phenomena such as natural harmonic motion, are complex in the sense that they require coordinating multiple subtle foci of attention to get the required information when experiencing them. Moreover, for students to develop sound understanding of a concept or a phenomenon, they need to learn to get the same type of information across different contexts and situations (diSessa and Sherin 1998; diSessa and Wagner 2005). Rather than simplifying complex situations, or creating a linear instructional sequence in which students move from one context to another, this paper demonstrates the use of computer-based representations to facilitate developing understanding of complex physical phenomena. The data is collected from 8 studies in which pairs of students are engaged in an exploratory activity, trying to understand the dynamic behavior of a simulation and, at the same time, to attribute meaning to it in terms of the physical phenomenon it represents. The analysis focuses on three episodes. The first two episodes demonstrate the epistemological complexity involved in attempting to make sense of natural harmonic oscillation. A third episode demonstrates the process by which students develop understanding in this complex perceptual and conceptual territory, through the mediation (Vygotsky 1978) of computer-based representations designed to facilitate understanding in this topic.

  16. 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.

  17. Developing Results-Based Leadership Attributes and Team Cohesiveness through Action Learning

    Science.gov (United States)

    Troupe, David

    2010-01-01

    Those who develop leaders in manufacturing settings have little data that describe the usefulness of action learning as a method of developing leaders' abilities to improve results-based leadership attributes or perceptions about their team's cohesiveness. The two purposes of this study were to evaluate an action learning program with regards to…

  18. 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.

  19. 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” w...

  20. Spatial choices of macaque monkeys based on the visual representation of the response space: rotation of the stimuli.

    Science.gov (United States)

    Nedvidek, Jan; Nekovarova, Tereza; Bures, Jan

    2008-11-21

    In earlier experiments we have demonstrated that macaque monkeys (Macaca mulatta) are able to use abstract visual stimuli presented on a computer screen to make spatial choices in the real environment. In those experiments a touch board ("response space") was directly connected to the computer screen ("virtual space"). The goal of the present experiment was to find out whether macaque monkeys are able: (1) To make spatial choices in a response space which is completely separated from the screen where the stimuli (designed as representation of the response space) are presented. (2) To make spatial choices based on visual stimuli representing the configuration of the response space which are rotated with respect to this response space. The monkeys were trained to choose one of the nine "touch holes" on a transparent touch panel situated beside a computer monitor on which the visual stimuli were presented. The visual stimuli were designed as an abstract representation of the response space: the rewarded position was shown as a bright circle situated at a certain position in the rectangle representing the contours of the touch panel. At first, the monkeys were trained with non-rotated spatial stimuli. After this initial training, the visual stimuli were gradually rotated by 20 degrees in each step. In the last phase, the stimulus was suddenly rotated in the opposite direction by 60 degrees in one step. The results of the experiment suggest that the monkeys are able to use successfully abstract stimuli from one spatial frame for spatial choices in another frame. Effective use of the stimuli after their rotation suggested that the monkeys perceived the stimuli as a representation of the configuration of the touch holes in the real space, not only as different geometrical patterns without configuration information.

  1. 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...

  2. Representational Machines

    DEFF Research Database (Denmark)

    Petersson, Dag; Dahlgren, Anna; Vestberg, Nina Lager

    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....

  3. Action-based distribution functions for spheroidal galaxy components

    Science.gov (United States)

    Posti, Lorenzo; Binney, James; Nipoti, Carlo; Ciotti, Luca

    2015-03-01

    We present an approach to the design of distribution functions that depend on the phase-space coordinates through the action integrals. The approach makes it easy to construct a dynamical model of a given stellar component. We illustrate the approach by deriving distribution functions that self-consistently generate several popular stellar systems, including the Hernquist, Jaffe, and Navarro, Frenk and White models. We focus on non-rotating spherical systems, but extension to flattened and rotating systems is trivial. Our distribution functions are easily added to each other and to previously published distribution functions for discs to create self-consistent multicomponent galaxies. The models this approach makes possible should prove valuable both for the interpretation of observational data and for exploring the non-equilibrium dynamics of galaxies via N-body simulations.

  4. Action-based distribution functions for spheroidal galaxy components

    CERN Document Server

    Posti, Lorenzo; Nipoti, Carlo; Ciotti, Luca

    2014-01-01

    We present an approach to the design of distribution functions that depend on the phase-space coordinates through the action integrals. The approach makes it easy to construct a dynamical model of a given stellar component. We illustrate the approach by deriving distribution functions that self-consistently generate several popular stellar systems, including the Hernquist, Jaffe, Navarro, Frenk and White models. We focus on non-rotating spherical systems, but extension to flattened and rotating systems is trivial. Our distribution functions are easily added to each other and to previously published distribution functions for discs to create self-consistent multi-component galaxies. The models this approach makes possible should prove valuable both for the interpretation of observational data and for exploring the non-equilibrium dynamics of galaxies via N-body simulation.

  5. Grid-based methods for diatomic quantum scattering problems: a finite-element, discrete variable representation in prolate spheroidal coordinates

    Energy Technology Data Exchange (ETDEWEB)

    Tao, Liang; McCurdy, C.W.; Rescigno, T.N.

    2008-11-25

    We show how to combine finite elements and the discrete variable representation in prolate spheroidal coordinates to develop a grid-based approach for quantum mechanical studies involving diatomic molecular targets. Prolate spheroidal coordinates are a natural choice for diatomic systems and have been used previously in a variety of bound-state applications. The use of exterior complex scaling in the present implementation allows for a transparently simple way of enforcing Coulomb boundary conditions and therefore straightforward application to electronic continuum problems. Illustrative examples involving the bound and continuum states of H2+, as well as the calculation of photoionization cross sections, show that the speed and accuracy of the present approach offer distinct advantages over methods based on single-center expansions.

  6. Time-frequency representation based on time-varying autoregressive model with applications to non-stationary rotor vibration analysis

    Indian Academy of Sciences (India)

    Long Zhang; Guoliang Xiong; Hesheng Liu; Huijun Zou; Weizhong Guo

    2010-04-01

    A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identification of time-varying model coefficients and the determination of model order, are addressed by means of neural networks and genetic algorithms, respectively. Firstly, a simulated signal which mimic the rotor vibration during run-up stages was processed for a comparative study on TVAR and other non-parametric time-frequency representations such as Short Time Fourier Transform, Continuous Wavelet Transform, Empirical Mode Decomposition, Wigner–Ville Distribution and Choi–Williams Distribution, in terms of their resolutions, accuracy, cross term suppression as well as noise resistance. Secondly, TVAR was applied to analyse non-stationary vibration signals collected from a rotor test rig during run-up stages, with an aim to extract fault symptoms under non-stationary operating conditions. Simulation and experimental results demonstrate that TVAR is an effective solution to non-stationary signal analysis and has strong capability in signal time-frequency feature extraction.

  7. Attachment and God representations among lay Catholics, priests, and religious: a matched comparison study based on the Adult Attachment Interview.

    Science.gov (United States)

    Cassibba, Rosalinda; Granqvist, Pehr; Costantini, Alessandro; Gatto, Sergio

    2008-11-01

    Based on the idea that believers' perceived relationships with God develop from their attachment-related experiences with primary caregivers, the authors explored the quality of such experiences and their representations among individuals who differed in likelihood of experiencing a principal attachment to God. Using the Adult Attachment Interview (AAI), they compared attachment-related experiences and representations in a group of 30 Catholic priests and religious with a matched group of lay Catholics and with the worldwide normal distribution of AAI classifications. They found an overrepresentation of secure-autonomous states regarding attachment among those more likely to experience a principal attachment to God (i.e., the priests and religious) compared with the other groups and an underrepresentation of unresolved-disorganized states in the two groups of Catholics compared with the worldwide normal distribution. Key findings also included links between secure-autonomous states regarding attachment and estimated experiences with loving or nonrejecting parents on the one hand and loving God imagery on the other. These results extend the literature on religion from an attachment perspective and support the idea that generalized working models derived from attachment experiences with parents are reflected in believers' perceptions of God.

  8. Representation of multi-target activity landscapes through target pair-based compound encoding in self-organizing maps.

    Science.gov (United States)

    Iyer, Preeti; Bajorath, Jürgen

    2011-11-01

    Activity landscape representations provide access to structure-activity relationships information in compound data sets. In general, activity landscape models integrate molecular similarity relationships with biological activity data. Typically, activity against a single target is monitored. However, for steadily increasing numbers of compounds, activity against multiple targets is reported, resulting in an opportunity, and often a need, to explore multi-target structure-activity relationships. It would be attractive to utilize activity landscape representations to aid in this process, but the design of activity landscapes for multiple targets is a complicated task. Only recently has a first multi-target landscape model been introduced, consisting of an annotated compound network focused on the systematic detection of activity cliffs. Herein, we report a conceptually different multi-target activity landscape design that is based on a 2D projection of chemical reference space using self-organizing maps and encodes compounds as arrays of pair-wise target activity relationships. In this context, we introduce the concept of discontinuity in multi-target activity space. The well-ordered activity landscape model highlights centers of discontinuity in activity space and is straightforward to interpret. It has been applied to analyze compound data sets with three, four, and five target annotations and identify multi-target structure-activity relationships determinants in analog series.

  9. A Symmetric Sparse Representation Based Band Selection Method for Hyperspectral Imagery Classification

    Directory of Open Access Journals (Sweden)

    Weiwei Sun

    2016-03-01

    Full Text Available A novel Symmetric Sparse Representation (SSR method has been presented to solve the band selection problem in hyperspectral imagery (HSI classification. The method assumes that the selected bands and the original HSI bands are sparsely represented by each other, i.e., symmetrically represented. The method formulates band selection into a famous problem of archetypal analysis and selects the representative bands by finding the archetypes in the minimal convex hull containing the HSI band points (i.e., one band corresponds to a band point in the high-dimensional feature space. Without any other parameter tuning work except the size of band subset, the SSR optimizes the band selection program using the block-coordinate descent scheme. Four state-of-the-art methods are utilized to make comparisons with the SSR on the Indian Pines and PaviaU HSI datasets. Experimental results illustrate that SSR outperforms all four methods in classification accuracies (i.e., Average Classification Accuracy (ACA and Overall Classification Accuracy (OCA and three quantitative evaluation results (i.e., Average Information Entropy (AIE, Average Correlation Coefficient (ACC and Average Relative Entropy (ARE, whereas it takes the second shortest computational time. Therefore, the proposed SSR is a good alternative method for band selection of HSI classification in realistic applications.

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

    OpenAIRE

    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.

  11. Multi-Agent Reinforcement Learning Algorithm Based on Action Prediction

    Institute of Scientific and Technical Information of China (English)

    TONG Liang; LU Ji-lian

    2006-01-01

    Multi-agent reinforcement learning algorithms are studied. A prediction-based multi-agent reinforcement learning algorithm is presented for multi-robot cooperation task. The multi-robot cooperation experiment based on multi-agent inverted pendulum is made to test the efficency of the new algorithm, and the experiment results show that the new algorithm can achieve the cooperation strategy much faster than the primitive multiagent reinforcement learning algorithm.

  12. Sensitivity analysis and probabilistic re-entry modeling for debris using high dimensional model representation based uncertainty treatment

    Science.gov (United States)

    Mehta, Piyush M.; Kubicek, Martin; Minisci, Edmondo; Vasile, Massimiliano

    2017-01-01

    Well-known tools developed for satellite and debris re-entry perform break-up and trajectory simulations in a deterministic sense and do not perform any uncertainty treatment. The treatment of uncertainties associated with the re-entry of a space object requires a probabilistic approach. A Monte Carlo campaign is the intuitive approach to performing a probabilistic analysis, however, it is computationally very expensive. In this work, we use a recently developed approach based on a new derivation of the high dimensional model representation method for implementing a computationally efficient probabilistic analysis approach for re-entry. Both aleatoric and epistemic uncertainties that affect aerodynamic trajectory and ground impact location are considered. The method is applicable to both controlled and un-controlled re-entry scenarios. The resulting ground impact distributions are far from the typically used Gaussian or ellipsoid distributions.

  13. 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.

  14. 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.

  15. 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...

  16. 基于wedgelets的快速图像表示方法%Fast image representation method based on wedgelets

    Institute of Scientific and Technical Information of China (English)

    束建华; 殷志祥

    2014-01-01

    针对用wedgelets表示图像存在计算冗余和存储空间大的问题,提出一种快速的基于wedgelets的图像表示方法。采用与传统的自下而上的剪枝策略不同的四叉树剪枝算法,通过基于快速多叉数树搜索及仅用wedgelets表示树叶来实现快速运算和减少存储空间,并且提出了一些提高计算效率的搜索和编码技巧。复杂度分析及实验结果表明,该方法能降低计算复杂度且有理想的率失真性能,并有效地捕获图像的几何结构。%A fast image representation method based on wedgelets is proposed in order to solve the problem that the image representation method by wedgelets has high computational complexity and storage space. The proposed method uses a recursive top-down quad-tree pruning algorithm compared to traditional bottom-up pruning strategy, based on fast multi-tree search and decorating leaves by wedgelets to achieve fast operation and reduce the storage space. Meanwhile, simple coding strategy and some search tips to improve the computational efficiency are presented and analyzed in this paper. Complexity analysis and Experimental results show that the method reduces computation complexity for searching different dyadic squares with desirable rate-distortion behaviour and captures natural geometric structure of image effectively.

  17. 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.

  18. Case-Based Plan Recognition Using Action Sequence Graphs

    Science.gov (United States)

    2014-10-01

    while probabilistic algorithms include those that use stochastic grammars and probabilistic relational models. Both these approaches are sensitive to...Proceedings of the Fifth Game-On International Conference (pp. 36-40). Reading, UK: University of Wolverhampton Press. Cox, M. T., & Kerkez, B...algorithm based on plan tree grammars . Artificial Intelligence, 173(11), 1101-1132. Ghallab,M., Nau, D., & Traverso, P. (2004). Automated planning: Theory

  19. 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

  20. 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…

  1. Caregiving Antecedents of Secure Base Script Knowledge: A Comparative Analysis of Young Adult Attachment Representations

    Science.gov (United States)

    Steele, Ryan D.; Waters, Theodore E. A.; Bost, Kelly K.; Vaughn, Brian E.; Truitt, Warren; Waters, Harriet S.; Booth-LaForce, Cathryn; Roisman, Glenn I.

    2014-01-01

    Based on a subsample (N = 673) of the NICHD Study of Early Child Care and Youth Development (SECCYD) cohort, this article reports data from a follow-up assessment at age 18 years on the antecedents of "secure base script knowledge", as reflected in the ability to generate narratives in which attachment-related difficulties are…

  2. 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.

  3. Product Knowledge Representation and Integration Technology in Web-based Collaborative Design

    Institute of Scientific and Technical Information of China (English)

    HAO Wentao; TIAN Ling; LUO Wei; TONG Bingshu

    2006-01-01

    Because of the complexity of modern product design, the web-based collaborative product design aroused considerable attention of manufacturers in the last few years with the development of Internet technology. But it is still hardly achievable due to the difficulty to share product knowledge from different designers and systems. In this paper, we firstly create an ontology-based product model, which consists of PPR (Product, Process and Resource) concept models and PPR characteristic models, to describe product knowledge. Afterwards, how to represent the model in XML is discussed in detail. Then the mechanism of product knowledge collection and integration from different application systems based on interface agents is introduced. At last, a web-based open-architecture product knowledge integrating and sharing prototype system AD-HUB is developed. An example is also given and it shows that the theory discussed in this paper is efficient to represent and integrate product knowledge in web-based collaborative design processes.

  4. Institutional actions based on nursing diagnoses for preventing falls in the elderly

    OpenAIRE

    Rafaela Vivian Valcarenghi; Silvana Sidney Costa Santos; Karina Silveira de Almeida Hammerschmidt; Edison Luiz Devos Barlem; iovana Calcagno Gomes; Bárbara Tarouco da Silva

    2014-01-01

    This study aimed to propose institutional actions based on nursing diagnoses for the prevention of falls in the elderly. Qualitative, exploratory and descriptive research, with 30 institutionalized senior citizens from Rio Grande, RS, Brazil. During data collection five instruments were applied from March to July 2009. One presents the elderly’s profile; aspects that favored the falls; nursing diagnoses; proposals for institutional actions to prevent falls. The nursing diagnoses were identifi...

  5. Cardiovascular actions of GLP-1 and incretin-based pharmacotherapy.

    Science.gov (United States)

    Avogaro, Angelo; Vigili de Kreutzenberg, Saula; Fadini, Gian Paolo

    2014-01-01

    Incretin-based therapy became recently available as antihyperglycemic treatment for patients with type 2 diabetes (T2DM). Incretin therapy comprises glucagon-like peptide receptor agonists (GLP-1RA) and dipeptidyl-peptidase 4 inhibitors (DPP4-I): these classes of drugs not only have the ability to reduce blood glucose, but also can exert several cardioprotective effects. They have been shown to positively influence some risk factors for cardiovascular disease (CVD), to improve endothelial function, and to directly affect cardiac function. For these reasons incretins are considered not only antidiabetic drugs, but also cardiovascular effective. The first clinical trials aimed to demonstrate the safety of DPP4 inhibitors have been recently published: their clinical significance will be discussed in light of the prior experimental findings.

  6. Multi-objective robust airfoil optimization based on non-uniform rational B-spline (NURBS) representation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In order to improve airfoil performance under different flight conditions and to make the performance insensitive to off-design condition at the same time,a multi-objective optimization approach considering robust design has been developed and applied to airfoil design. Non-uniform rational B-spline (NURBS) representation is adopted in airfoil design process,control points and related weights around airfoil are used as design variables. Two airfoil representation cases show that the NURBS method can get airfoil geometry with max geometry error less than 0.0019. By using six-sigma robust approach in multi-objective airfoil design,each sub-objective function of the problem has robustness property. By adopting multi-objective genetic algorithm that is based on non-dominated sorting,a set of non-dominated airfoil solutions with robustness can be obtained in the design. The optimum robust airfoil can be traded off and selected in these non-dominated solutions by design tendency. By using the above methods,a multi-objective robust optimization was conducted for NASA SC0712 airfoil. After performing robust airfoil optimization,the mean value of drag coefficient at Ma0.7-0.8 and the mean value of lift coefficient at post stall regime (Ma0.3) have been improved by 12.2% and 25.4%. By comparing the aerodynamic force coefficients of optimization result,it shows that: different from single robust airfoil design which just improves the property of drag divergence at Ma0.7-0.8,multi-objective robust design can improve both the drag divergence property at Ma0.7-0.8 and stall property at low speed. The design cases show that the multi-objective robust design method makes the airfoil performance robust under different off-design conditions.

  7. FPGA implementation of a modified FitzHugh-Nagumo neuron based causal neural network for compact internal representation of dynamic environments

    Science.gov (United States)

    Salas-Paracuellos, L.; Alba, Luis; Villacorta-Atienza, Jose A.; Makarov, Valeri A.

    2011-05-01

    Animals for surviving have developed cognitive abilities allowing them an abstract representation of the environment. This internal representation (IR) may contain a huge amount of information concerning the evolution and interactions of the animal and its surroundings. The temporal information is needed for IRs of dynamic environments and is one of the most subtle points in its implementation as the information needed to generate the IR may eventually increase dramatically. Some recent studies have proposed the compaction of the spatiotemporal information into only space, leading to a stable structure suitable to be the base for complex cognitive processes in what has been called Compact Internal Representation (CIR). The Compact Internal Representation is especially suited to be implemented in autonomous robots as it provides global strategies for the interaction with real environments. This paper describes an FPGA implementation of a Causal Neural Network based on a modified FitzHugh-Nagumo neuron to generate a Compact Internal Representation of dynamic environments for roving robots, developed under the framework of SPARK and SPARK II European project, to avoid dynamic and static obstacles.

  8. 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.

  9. 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 fo...... 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....

  10. THEORY OF REGENERATION BASED ON MASS ACTION. II.

    Science.gov (United States)

    Loeb, J

    1923-11-20

    1. Quantitative proof is furnished that all the material available for shoot and root formation in an isolated leaf of Bryophyllum calycinum flows to those notches where through the influence of gravity or by a more abundant supply of water growth is accelerated. As soon as the acceleration of growth in these notches commences, the growth of shoots and roots in the other notches which may already have started ceases. 2. It had been shown in a preceding paper that the regeneration of an isolated piece of stem may be and frequently is in the beginning not markedly polar, but that after some time the growth of all the roots except those at the base and of all the shoots except those at the apex is suppressed. This analogy with the behavior of regeneration in a leaf in which the growth in one set of notches is accelerated, suggests that in an isolated stem a more rapid growth is favored at the extreme ends (probably by a block of the sap flow at the extreme ends) and that when this happens the total flow of ascending sap goes to the most apical buds and the total flow of the descending sap goes to the most basal roots. As soon as this occurs, the growth of the other roots and shoots is suppressed.

  11. Bridging Real World Semantics to Model World Semantics for Taxonomy Based Knowledge Representation System

    Institute of Scientific and Technical Information of China (English)

    Ju-Hum Kwon; Chee-Yang Song; Chang-Joo Moon; Doo-Kwon Baik

    2005-01-01

    As a mean to map ontology concepts, a similarity technique is employed. Especially a context dependent concept mapping is tackled, which needs contextual information from knowledge taxonomy. Context-based semantic similarity differs from the real world similarity in that it requires contextual information to calculate similarity. The notion of semantic coupling is introduced to derive similarity for a taxonomy-based system. The semantic coupling shows the degree of semantic cohesiveness for a group of concepts toward a given context. In order to calculate the semantic coupling effectively, the edge counting method is revisited for measuring basic semantic similarity by considering the weighting attributes from where they affect an edge's strength. The attributes of scaling depth effect, semantic relation type, and virtual connection for the edge counting are considered. Furthermore, how the proposed edge counting method could be well adapted for calculating context-based similarity is showed. Thorough experimental results are provided for both edge counting and context-based similarity. The results of proposed edge counting were encouraging compared with other combined approaches, and the context-based similarity also showed understandable results. The novel contributions of this paper come from two aspects.First, the similarity is increased to the viable level for edge counting. Second, a mechanism is provided to derive a contextbased similarity in taxonomy-based system, which has emerged as a hot issue in the literature such as Semantic Web, MDR,and other ontology-mapping environments.

  12. 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.

  13. Spectral representation of fingerprints

    NARCIS (Netherlands)

    Xu, Haiyun; Bazen, Asker M.; Veldhuis, Raymond N.J.; Kevenaar, Tom A.M.; Akkermans, Anton H.M.

    2007-01-01

    Most fingerprint recognition systems are based on the use of a minutiae set, which is an unordered collection of minutiae locations and directions suffering from various deformations such as translation, rotation and scaling. The spectral minutiae representation introduced in this paper is a novel m

  14. 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…

  15. Image Classification System Based on Cortical Representations and Unsupervised Neural Network Learning

    NARCIS (Netherlands)

    Petkov, Nikolay

    1995-01-01

    A preprocessor based on a computational model of simple cells in the mammalian primary visual cortex is combined with a self-organising artificial neural network classifier. After learning with a sequence of input images, the output units of the system turn out to correspond to classes of input imag

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

    DEFF Research Database (Denmark)

    Dolog, Peter

    2006-01-01

    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...

  17. 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.…

  18. 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…

  19. Knot invariants and higher representation theory II: the categorification of quantum knot invariants

    CERN Document Server

    Webster, Ben

    2010-01-01

    We construct knot invariants categorifying the quantum knot variants for all representations of quantum groups. We show that these invariants coincide with previous invariants defined by Khovanov for sl_2 and sl_3 and by Mazorchuk-Stroppel and Sussan for sl_n. We also suggest an approach to showing that these knot homologies are functorial. Our technique uses categorifications of the tensor products of integrable representations of Kac-Moody algebras and quantum groups, constructed a prequel to this paper. In particular, we construct functors on these categorifying the action of the braiding and duality of quantum group representations. These categories are based on the pictorial approach of Khovanov and Lauda.

  20. Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yi; YAN Li

    2007-01-01

    A scheme for an automatic road surface modeling from a noisy point cloud is presented. The normal vectors of the point cloud are estimated by distance-weighted fitting of local plane. Then, an automatic recognition of the road surface from noise is performed based on the fuzzy clustering of normal vectors, with which the mean value is calculated and the projecting plane of point cloud is created to obtain the geometric model accordingly. Based on fuzzy clustering of the intensity attributed to each point, different objects on the road surface are assigned different colors for representing abundant appearances.This unsupervised method is demonstrated in the experiment and shows great effectiveness in reconstructing and rendering better road surface.

  1. View-based encoding of actions in mirror neurons of area f5 in macaque premotor cortex.

    Science.gov (United States)

    Caggiano, Vittorio; Fogassi, Leonardo; Rizzolatti, Giacomo; Pomper, Joern K; Thier, Peter; Giese, Martin A; Casile, Antonino

    2011-01-25

    Converging experimental evidence indicates that mirror neurons in the monkey premotor area F5 encode the goals of observed motor acts [1-3]. However, it is unknown whether they also contribute to encoding the perspective from which the motor acts of others are seen. In order to address this issue, we recorded the visual responses of mirror neurons of monkey area F5 by using a novel experimental paradigm based on the presentation of movies showing grasping motor acts from different visual perspectives. We found that the majority of the tested mirror neurons (74%) exhibited view-dependent activity with responses tuned to specific points of view. A minority of the tested mirror neurons (26%) exhibited view-independent responses. We conclude that view-independent mirror neurons encode action goals irrespective of the details of the observed motor acts, whereas the view-dependent ones might either form an intermediate step in the formation of view independence or contribute to a modulation of view-dependent representations in higher-level visual areas, potentially linking the goals of observed motor acts with their pictorial aspects.

  2. Application of Passivity-Based Control and Time-Frequency Representation in a Doubly Fed Induction Generator System

    Directory of Open Access Journals (Sweden)

    Yingpei Liu

    2015-01-01

    Full Text Available In order to improve the performance of a doubly fed induction generator (DFIG system, we put forward a high performance nonlinear passivity-based control (PBC method on DFIG. Firstly, we build a PBC mathematical model for DFIG. We design the passive controller for the inner loop in the control system based on passivity theory. Then we calculate the rotor’s control voltages which are modulated afterwards to pulse to control the rotor side converter. The maximal wind energy capture is effectively realized. The rotor speed and DFIG currents fast track their expected values. The independent regulation of the stator active power and reactive power is achieved. Finally we perform simulations to verify the effectiveness of the proposed method. Furthermore, we employ the Wigner-Ville distribution (WVD and continuous wavelet transform (CWT as two time-frequency representation methods to indicate that the proposed method in the paper performs well from the perspective of energy distribution in time and frequency domain.

  3. Sparse Representation of Transients Based on Wavelet Basis and Majorization-Minimization Algorithm for Machinery Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Wei Fan

    2014-01-01

    Full Text Available Vibration signals captured from faulty mechanical components are often associated with transients which are significant for machinery fault diagnosis. However, the existence of strong background noise makes the detection of transients a basis pursuit denoising (BPD problem, which is hard to be solved in explicit form. With sparse representation theory, this paper proposes a novel method for machinery fault diagnosis by combining the wavelet basis and majorization-minimization (MM algorithm. This method converts transients hidden in the noisy signal into sparse coefficients; thus the transients can be detected sparsely. Simulated study concerning cyclic transient signals with different signal-to-noise ratio (SNR shows that the effectiveness of this method. The comparison in the simulated study shows that the proposed method outperforms the method based on split augmented Lagrangian shrinkage algorithm (SALSA in convergence and detection effect. Application in defective gearbox fault diagnosis shows the fault feature of gearbox can be sparsely and effectively detected. A further comparison between this method and the method based on SALSA shows the superiority of the proposed method in machinery fault diagnosis.

  4. Detecting Protein-Protein Interactions with a Novel Matrix-Based Protein Sequence Representation and Support Vector Machines

    Directory of Open Access Journals (Sweden)

    Zhu-Hong You

    2015-01-01

    Full Text Available Proteins and their interactions lie at the heart of most underlying biological processes. Consequently, correct detection of protein-protein interactions (PPIs is of fundamental importance to understand the molecular mechanisms in biological systems. Although the convenience brought by high-throughput experiment in technological advances makes it possible to detect a large amount of PPIs, the data generated through these methods is unreliable and may not be completely inclusive of all possible PPIs. Targeting at this problem, this study develops a novel computational approach to effectively detect the protein interactions. This approach is proposed based on a novel matrix-based representation of protein sequence combined with the algorithm of support vector machine (SVM, which fully considers the sequence order and dipeptide information of the protein primary sequence. When performed on yeast PPIs datasets, the proposed method can reach 90.06% prediction accuracy with 94.37% specificity at the sensitivity of 85.74%, indicating that this predictor is a useful tool to predict PPIs. Achieved results also demonstrate that our approach can be a helpful supplement for the interactions that have been detected experimentally.

  5. Action Theory Based on the Dynamic Description Logic DDL%基于动态描述逻辑DDL的动作理论

    Institute of Scientific and Technical Information of China (English)

    常亮; 陈立民

    2011-01-01

    There is a gap on expressive power and reasoning ability between the action theories which are based on first-or higher-order logics and the action theories which are only propositional. As a kind of dynamic extensions of description logics, the dynamic description logic DDL provides an approach for describing and reasoning about actions. An action theory based on DDL was presented and studied systematically. Firstly, based on a representation of static domain knowledge with description logics, the parameterized atomic action definitions and the parameterized complex action definitions were introduced for describing the knowledge of actions;both of these knowledge,and together with the knowledge on the state of the world,are unified as a DDL-based knowledge representation system. Secondly,many reasoning tasks on the knowledge represented in this system were formally defined corresponding reasoning mechanisms were also provided. Finally, the application of this action theory for the modeling of intelligent agents was discussed. The action theory based on DDL offers not only considerable expressive power but also attractive reasoning services; it is suitable for the description and reasoning of actions in the environment of the semantic Web.%基于一阶谓词逻辑或高阶逻辑的动作理论与采用命题语言的动作理论之间存在一个关于描述和推理能力的鸿沟;作为描述逻辑的动态扩展,动态描述逻辑DDL为基于描述逻辑的动作刻画和推理提供了一种途径.系统地研究了基于DDL的动作表示和推理问题.首先,在应用描述逻辑对静态领域知识进行刻画的基础上,引入带参数的原子动作定义式和带参数的复杂动作定义式,刻画出关于动作的知识;这两部分知识与关于具体状态的知识一起构成基于DDL的知识表示系统.接下来,针对该系统中刻画的各种知识,对相关推理问题进行了严格定义,给出了相应的推理机制和

  6. Closing the Learning-Planning Loop with Predictive State Representations

    CERN Document Server

    Boots, Byron; Gordon, Geoffrey J

    2009-01-01

    A central problem in artificial intelligence is that of planning to maximize future reward under uncertainty in a partially observable environment. In this paper we propose and demonstrate a novel algorithm which accurately learns a model of such an environment directly from sequences of action-observation pairs. We then close the loop from observations to actions by planning in the learned model and recovering a policy which is near-optimal in the original environment. Specifically, we present an efficient and statistically consistent spectral algorithm for learning the parameters of a Predictive State Representation (PSR). We demonstrate the algorithm by learning a model of a simulated high-dimensional, vision-based mobile robot planning task, and then perform approximate point-based planning in the learned PSR. Analysis of our results shows that the algorithm learns a state space which efficiently captures the essential features of the environment. This representation allows accurate prediction with a smal...

  7. 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...... with proteomics studies together with detailed peptide and protein identification and quantification information. Statistical criteria for peptide identification and their posttranslational modifications have largely been established for individual projects. However, the current practice of indiscriminately...... mechanisms for community-wide sharing of these data....

  8. 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...... equations (PDEs) are applied on the pixonal image for noise removing. The proposed algorithm has been examined on variety of standard images and their performance compared with the existing algorithms. Experimental results show that in comparison with the other existing methods, the proposed algorithm has...... a better performance in denoising and preserving image edges....

  9. Feature Extraction of Chinese Materia Medica Fingerprint Based on Star Plot Representation of Multivariate Data

    Institute of Scientific and Technical Information of China (English)

    CUI Jian-xin; HONG Wen-xue; ZHOU Rong-juan; GAO Hai-bo

    2011-01-01

    Objective To study a novel feature extraction method of Chinese materia medica (CMM) fingerprint. Methods On the basis of the radar graphical presentation theory of multivariate, the radar map was used to figure the non-map parameters of the CMM fingerprint, then to extract the map features and to propose the feature fusion. Results Better performance was achieved when using this method to test data. Conclusion This shows that the feature extraction based on radar chart presentation can mine the valuable features that facilitate the identification of Chinese medicine.

  10. On-line and Model-based Approaches to the Visual Control of Action

    OpenAIRE

    Zhao, Huaiyong; Warren, William H.

    2014-01-01

    Two general approaches to the visual control of action have emerged in last few decades, known as the on-line and model-based approaches. The key difference between them is whether action is controlled by current visual information or on the basis of an internal world model. In this paper, we evaluate three hypotheses: strong on-line control, strong model-based control, and a hybrid solution that combines on-line control with weak off-line strategies. We review experimental research on the co...

  11. Noise correlation-based adaptive polarimetric image representation for contrast enhancement of a polarized beacon in fog

    Science.gov (United States)

    Panigrahi, Swapnesh; Fade, Julien; Alouini, Mehdi

    2015-10-01

    We show the use of a simplified snapshot polarimetric camera along with an adaptive image processing for optimal detection of a polarized light beacon through fog. The adaptive representation is derived using theoretical noise analysis of the data at hand and is shown to be optimal in the Maximum likelihood sense. We report that the contrast enhancing optimal representation that depends on the background noise correlation differs in general from standard representations like polarimetric difference image or polarization filtered image. Lastly, we discuss a detection strategy to reduce the false positive counts.

  12. A Perceptual Audio Representation for Low Rate Coding Based on Sines+Noise Modeling

    Institute of Scientific and Technical Information of China (English)

    AL-MoussawyRaed; YINJunxun; HUANGJiancheng

    2003-01-01

    This work is concerned with the develop-ment and optimization of an efficient (which allows high compression ratios) and flexible (which allows scalability)signal model for perceptual audio coding at low bitrates.A novel, complementary two-part model for audio consist-ing of sines+ noise (SN) is presented. The SN model uses a sinusoidal model that explicitly takes into account the human hearing system by using psychoacoustically based matching pursuits. This technique iteratively extracts si-nusoidal components according to their perceptually im-portant signal-to-mask ratio (SMR). The second modeling stage is for noise-like components. The SN model uses the equivalent rectangular bandwidth (ERB) noise model;that is based on observations that for noise-like signals,energy in the ERBs describes the underlying signal with perceptual accuracy. The SN model has an intuitive inter-pretation in terms of discrete fourier transform (DFT) and can be efficiently implemented via the fast fourier trans-form (FFT). Informal listening tests demonstrate that the synthesized (sines + noise) signal is almost perceptually identical to the original. A compression ratio of typically 16 to 19.5 can be readily reached with SN model.

  13. A Novel Clustering-Based Feature Representation for the Classification of Hyperspectral Imagery

    Directory of Open Access Journals (Sweden)

    Qikai Lu

    2014-06-01

    Full Text Available In this study, a new clustering-based feature extraction algorithm is proposed for the spectral-spatial classification of hyperspectral imagery. The clustering approach is able to group the high-dimensional data into a subspace by mining the salient information and suppressing the redundant information. In this way, the relationship between neighboring pixels, which was hidden in the original data, can be extracted more effectively. Specifically, in the proposed algorithm, a two-step process is adopted to make use of the clustering-based information. A clustering approach is first used to produce the initial clustering map, and, subsequently, a multiscale cluster histogram (MCH is proposed to represent the spatial information around each pixel. In order to evaluate the robustness of the proposed MCH, four clustering techniques are employed to analyze the influence of the clustering methods. Meanwhile, the performance of the MCH is compared to three other widely used spatial features: the gray-level co-occurrence matrix (GLCM, the 3D wavelet texture, and differential morphological profiles (DMPs. The experiments conducted on four well-known hyperspectral datasets verify that the proposed MCH can significantly improve the classification accuracy, and it outperforms other commonly used spatial features.

  14. Protein submitochondrial localization from integrated sequence representation and SVM-based backward feature extraction.

    Science.gov (United States)

    Li, Liqi; Yu, Sanjiu; Xiao, Weidong; Li, Yongsheng; Hu, Wenjuan; Huang, Lan; Zheng, Xiaoqi; Zhou, Shiwen; Yang, Hua

    2015-01-01

    Mitochondrion, a tiny energy factory, plays an important role in various biological processes of most eukaryotic cells. Mitochondrial defection is associated with a series of human diseases. Knowledge of the submitochondrial locations of proteins can help to reveal the biological functions of novel proteins, and understand the mechanisms underlying various biological processes occurring in the mitochondrion. However, experimental methods to determine protein submitochondrial locations are costly and time consuming. Thus it is essential to develop a fast and reliable computational method to predict protein submitochondrial locations. Here, we proposed a support vector machine (SVM) based approach for predicting protein submitochondrial locations. Information from the position-specific score matrix (PSSM), gene ontology (GO) and the protein feature (PROFEAT) was integrated into the principal features of this model. Then a recursive feature selection scheme was employed to select the optimal features. Finally, an SVM module was used to predict protein submitochondrial locations based on the optimal features. Through the jackknife cross-validation test, our method achieved an accuracy of 99.37% on benchmark dataset M317, and 100% on the other two datasets, M1105 and T86. These results indicate that our method is economic and effective for accurate prediction of the protein submitochondrial location.

  15. An Online Continuous Human Action Recognition Algorithm Based on the Kinect Sensor

    Directory of Open Access Journals (Sweden)

    Guangming Zhu

    2016-01-01

    Full Text Available Continuous human action recognition (CHAR is more practical in human-robot interactions. In this paper, an online CHAR algorithm is proposed based on skeletal data extracted from RGB-D images captured by Kinect sensors. Each human action is modeled by a sequence of key poses and atomic motions in a particular order. In order to extract key poses and atomic motions, feature sequences are divided into pose feature segments and motion feature segments, by use of the online segmentation method based on potential differences of features. Likelihood probabilities that each feature segment can be labeled as the extracted key poses or atomic motions, are computed in the online model matching process. An online classification method with variable-length maximal entropy Markov model (MEMM is performed based on the likelihood probabilities, for recognizing continuous human actions. The variable-length MEMM method ensures the effectiveness and efficiency of the proposed CHAR method. Compared with the published CHAR methods, the proposed algorithm does not need to detect the start and end points of each human action in advance. The experimental results on public datasets show that the proposed algorithm is effective and highly-efficient for recognizing continuous human actions.

  16. Hybrid Feature Extraction-based Approach for Facial Parts Representation and Recognition

    Science.gov (United States)

    Rouabhia, C.; Tebbikh, H.

    2008-06-01

    Face recognition is a specialized image processing which has attracted a considerable attention in computer vision. In this article, we develop a new facial recognition system from video sequences images dedicated to person identification whose face is partly occulted. This system is based on a hybrid image feature extraction technique called ACPDL2D (Rouabhia et al. 2007), it combines two-dimensional principal component analysis and two-dimensional linear discriminant analysis with neural network. We performed the feature extraction task on the eyes and the nose images separately then a Multi-Layers Perceptron classifier is used. Compared to the whole face, the results of simulation are in favor of the facial parts in terms of memory capacity and recognition (99.41% for the eyes part, 98.16% for the nose part and 97.25 % for the whole face).

  17. Novel similarity measures for face representation based on local binary pattern

    Institute of Scientific and Technical Information of China (English)

    ZHU Shi-hu; FENG Ju-fu

    2009-01-01

    The successful face recognition based on local binary pattern (LBP) relies on the effective extraction of LBP features and the inferring of similarity between the extracted features. In this paper, we focus on the latter and propose two novel similarity measures for the local matching methods and the holistic matching methods respectively. One is Earth Mover's Distance with Hamming and Lp ground distance (EMD-HammingLp),which is a cross-bin dissimilarity measure for LBP histograms. The other is IMage Hamming Distance (IMHD),which is a dissimilarity measure for the whole LBP images. Experiments on FERET database show that the proposed two similarity measures outperform the state-of-the-art Chi-square similarity measure for extraction of LBP features.

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

    CERN Document Server

    Alessandretti, Laura; Gauvin, Laetitia

    2015-01-01

    Multimodal transportation systems can be represented as time-resolved multilayer networks where different transportation modes connecting the same set of nodes are associated to distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geolocalised 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, our aim is to provide a novel user-based methodological framework to represent public transportation systems considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. Using this framework we analyse public transportation systems in several French municipal areas. We incorporate travel routes and times over multiple transportation modes to identify efficient transportation connections and non-trivial connectivity patterns. The proposed method ...

  19. Framework based on MDA and ontology for the representation and validation of components model

    Directory of Open Access Journals (Sweden)

    Nemury Silega-Martínez

    2014-05-01

    Full Text Available Model Driven Architecture is one of the most prominent proposals in the area of software development, accepted by both the research community and software development industry. Moreover, in recent years have shown the potential of ontologies for representing a particular domain, example of this are the results in the semantic web. In this paper we present a proposal based on Model Driven Architecture paradigm and is complemented with ontology to represent and validate component models. This component model is restricted to the development of business management systems, so it includes concepts from that domain. The use of the framework will reduce the number of errors made during the development of the system architecture, will increase standardization and productivity at this stage.

  20. Auditory Sparse Representation for Robust Speaker Recognition Based on Tensor Structure

    Directory of Open Access Journals (Sweden)

    Liqing Zhang

    2008-11-01

    Full Text Available This paper investigates the problem of speaker recognition in noisy conditions. A new approach called nonnegative tensor principal component analysis (NTPCA with sparse constraint is proposed for speech feature extraction. We encode speech as a general higher-order tensor in order to extract discriminative features in spectrotemporal domain. Firstly, speech signals are represented by cochlear feature based on frequency selectivity characteristics at basilar membrane and inner hair cells; then, low-dimension sparse features are extracted by NTPCA for robust speaker modeling. The useful information of each subspace in the higher-order tensor can be preserved. Alternating projection algorithm is used to obtain a stable solution. Experimental results demonstrate that our method can increase the recognition accuracy specifically in noisy environments.

  1. Auditory Sparse Representation for Robust Speaker Recognition Based on Tensor Structure

    Directory of Open Access Journals (Sweden)

    Wu Qiang

    2008-01-01

    Full Text Available This paper investigates the problem of speaker recognition in noisy conditions. A new approach called nonnegative tensor principal component analysis (NTPCA with sparse constraint is proposed for speech feature extraction. We encode speech as a general higher-order tensor in order to extract discriminative features in spectrotemporal domain. Firstly, speech signals are represented by cochlear feature based on frequency selectivity characteristics at basilar membrane and inner hair cells; then, low-dimension sparse features are extracted by NTPCA for robust speaker modeling. The useful information of each subspace in the higher-order tensor can be preserved. Alternating projection algorithm is used to obtain a stable solution. Experimental results demonstrate that our method can increase the recognition accuracy specifically in noisy environments.

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

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Curtis L. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Prescott, Steven [Idaho National Lab. (INL), Idaho Falls, ID (United States); Kvarfordt, Kellie [Idaho National Lab. (INL), Idaho Falls, ID (United States); Sampath, Ram [Idaho National Lab. (INL), Idaho Falls, ID (United States); Larson, Katie [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2015-09-01

    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.

  3. Strength of object representation: its key role in object-based attention for determining the competition result between Gestalt and top-down objects.

    Science.gov (United States)

    Zhao, Jingjing; Wang, Yonghui; Liu, Donglai; Zhao, Liang; Liu, Peng

    2015-10-01

    It was found in previous studies that two types of objects (rectangles formed according to the Gestalt principle and Chinese words formed in a top-down fashion) can both induce an object-based effect. The aim of the present study was to investigate how the strength of an object representation affects the result of the competition between these two types of objects based on research carried out by Liu, Wang and Zhou [(2011) Acta Psychologica, 138(3), 397-404]. In Experiment 1, the rectangles were filled with two different colors to increase the strength of Gestalt object representation, and we found that the object effect changed significantly for the different stimulus types. Experiment 2 used Chinese words with various familiarities to manipulate the strength of the top-down object representation. As a result, the object-based effect induced by rectangles was observed only when the Chinese word familiarity was low. These results suggest that the strength of object representation determines the result of competition between different types of objects.

  4. 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.

  5. 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

  6. Quantum like representation of aSpiral Phase Plate

    CERN Document Server

    Bovino, Fabio A

    2011-01-01

    We introduce a quantum like representation of a Spiral Phase Plate, acting on an electromagnetic field, as a two mode phase operator. The representation is based on the Newton binomial expansion and on properties of rational power of lowering and raising operators of quantum field. The correctness of this representation is proved by obtaining the same results of the Paul's operator in the single mode limit and comparing the results of two particular problems solved both in the classical and quantum picture: the action of a Spiral Phase Plate on a Gaussian Beam (corresponding to the vacuum state of the two-dimensional harmonic oscillator) and on a off-axis Gaussian Beam (corresponding to the displaced vacuum state in quantum picture).

  7. 基于稀疏表示的QR码识别%QR code recognition based on sparse representation

    Institute of Scientific and Technical Information of China (English)

    孙道达; 赵健; 王瑞; 冯宁; 胡江华

    2013-01-01

    针对QR码图像受污染、破损、遮挡时识别软件无法识别的问题,提出一种基于稀疏表示的QR码识别方法.以40类QR码图像作为研究对象,每类13幅,其中每类随机选取3幅共120幅作为训练样本,余下400幅作为测试样本.所有训练样本组成稀疏表示字典,测试样本为训练样本的稀疏线性组合,表示系数是稀疏的,对每一个测试样本,计算其在字典上的投影,具有最小残差值的类别,即为分类所属类别.最后将提出的方法与QR码识读软件PsQREdit的识别结果做了对比和分析.实验结果表明:提出的方法对于部分受污染、破损、遮挡的图像仍能正确识别,具有很好的鲁棒性,为QR码的识别提供了一种新的有效方案.%With regard to the problem that recognition software does not work when the Quick Response ( QR) code image is contaminated, damaged or obscured, a QR code recognition method based on sparse representation was proposed. Forty categories QR code images were used as research subjects and each category has 13 images. Three images were randomly selected from each category and thus a total of 120 images were got as the training sample and the remaining 400 as test sample. Sparse representation dictionary was composed of all training samples. The test samples were a sparse linear combination of the training samples and the coefficients were sparse. The projection of each test sample in the dictionary was calculated, so category with the smallest residual was classification category. Finally, comparison and analysis were done between the recognition results of the proposed method and the QR code recognition software PsQREdit. The experimental results show that, the proposed method is able to correctly identify for partially contaminated, damaged and obscured image, and it has good robustness. It is a new effective means for the recognition of QR code.

  8. [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

  9. Promoting Student Engagement through Evidence-Based Action Research with Teachers

    Science.gov (United States)

    Strambler, Michael J.; McKown, Clark

    2013-01-01

    We present findings from a group-randomized teacher action research intervention to promote academic engagement and achievement among elementary school students. Eighteen teachers from 3 elementary schools were randomly assigned to 1 of 2 groups. Intervention teachers studied evidence-based instructional practices that cultivate academic…

  10. Catapulting Shifts in Images, Understandings, and Actions for Family Members through Research-Based Drama

    Science.gov (United States)

    Dupuis, Sherry L.; Gillies, Jennifer; Mitchell, Gail J.; Jonas-Simpson, Christine; Whyte, Colleen; Carson, Jennifer

    2011-01-01

    This article examined how images, understandings, and actions change for family members of persons with dementia after the introduction of a research-based drama called I'm Still Here. Guided by interpretivist phenomenology, a set of seven pre- and post-performance focus groups were conducted with family members (n = 48) in four cities. Findings…

  11. 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 seafood and thereby rep

  12. Scaffolding Strategies for Wiki-Based Collaboration: Action Research in a Multicultural Japanese Language Program

    Science.gov (United States)

    Jung, Insung; Suzuki, Yoko

    2015-01-01

    Wikis can be used to encourage and support collaborative constructivist learning. However, their effectiveness depends upon the use of scaffolding strategies to guide the students in their use. This action research investigated three scaffolding strategies for wiki-based multicultural Japanese language learning: worked examples, grouping and peer…

  13. 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…

  14. 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…

  15. Translation between representation languages

    Science.gov (United States)

    Vanbaalen, Jeffrey

    1994-01-01

    A capability for translating between representation languages is critical for effective knowledge base reuse. A translation technology for knowledge representation languages based on the use of an interlingua for communicating knowledge is described. The interlingua-based translation process consists of three major steps: translation from the source language into a subset of the interlingua, translation between subsets of the interlingua, and translation from a subset of the interlingua into the target language. The first translation step into the interlingua can typically be specified in the form of a grammar that describes how each top-level form in the source language translates into the interlingua. In cases where the source language does not have a declarative semantics, such a grammar is also a specification of a declarative semantics for the language. A methodology for building translators that is currently under development is described. A 'translator shell' based on this methodology is also under development. The shell has been used to build translators for multiple representation languages and those translators have successfully translated nontrivial knowledge bases.

  16. Revealing children's implicit spelling representations.

    Science.gov (United States)

    Critten, Sarah; Pine, Karen J; Messer, David J

    2013-06-01

    Conceptualizing the underlying representations and cognitive mechanisms of children's spelling development is a key challenge for literacy researchers. Using the Representational Redescription model (Karmiloff-Smith), Critten, Pine and Steffler (2007) demonstrated that the acquisition of phonological and morphological knowledge may be underpinned by increasingly explicit levels of spelling representation. However, their proposal that implicit representations may underlie early 'visually based' spelling remains unresolved. Children (N = 101, aged 4-6 years) were given a recognition task (Critten et al., 2007) and a novel production task, both involving verbal justifications of why spellings are correct/incorrect, strategy use and word pattern similarity. Results for both tasks supported an implicit level of spelling characterized by the ability to correctly recognize/produce words but the inability to explain operational strategies or generalize knowledge. Explicit levels and multiple representations were also in evidence across the two tasks. Implications for cognitive mechanisms underlying spelling development are discussed.

  17. Rank Pooling for Action Recognition.

    Science.gov (United States)

    Fernando, Basura; Gavves, Efstratios; Oramas M, Jose Oramas; Ghodrati, Amir; Tuytelaars, Tinne

    2017-04-01

    We propose a function-based temporal pooling method that captures the latent structure of the video sequence data - e.g., how frame-level features evolve over time in a video. We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation. As a specific example, we learn a pooling function via ranking machines. By learning to rank the frame-level features of a video in chronological order, we obtain a new representation that captures the video-wide temporal dynamics of a video, suitable for action recognition. Other than ranking functions, we explore different parametric models that could also explain the temporal changes in videos. The proposed functional pooling methods, and rank pooling in particular, is easy to interpret and implement, fast to compute and effective in recognizing a wide variety of actions. We evaluate our method on various benchmarks for generic action, fine-grained action and gesture recognition. Results show that rank pooling brings an absolute improvement of 7-10 average pooling baseline. At the same time, rank pooling is compatible with and complementary to several appearance and local motion based methods and features, such as improved trajectories and deep learning features.

  18. 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.

  19. 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.

  20. 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.

  1. Grasping actions and social interaction: neural bases and anatomical circuitry in the monkey.

    Directory of Open Access Journals (Sweden)

    Stefano eRozzi

    2015-07-01

    Full Text Available The study of the neural mechanisms underlying grasping actions showed that cognitive functions are deeply embedded in motor organization. In the first part of this review, we describe the anatomical structure of the motor cortex in the monkey and the cortical and sub-cortical connections of the different motor areas. In the second part, we review the neurophysiological literature showing that motor neurons are not only involved in movement execution, but also in the transformation of object physical features into motor programs appropriate to grasp them (through visuo-motor transformations. We also discuss evidence indicating that motor neurons can encode the goal of motor acts and the intention behind action execution. Then, we describe one of the mechanisms – the mirror mechanism – considered to be at the basis of action understanding and intention reading, and describe the anatomo-functional pathways through which information about the social context can reach the areas containing mirror neurons. Finally, we briefly show that a clear similarity exists between monkey and human in the organization of the motor and mirror systems. Based on monkey and human literature, we conclude that the mirror mechanism relies on a more extended network than previously thought, and possibly subserves basic social functions. We propose that this mechanism is also involved in preparing appropriate complementary response to observed actions, allowing two individuals to become attuned and cooperate in joint actions.

  2. 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.

  3. 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

  4. Conceptual representation of actions in sign language

    NARCIS (Netherlands)

    Dobel, Christian; Enriquez-Geppert, Stefanie; Hummert, Marja; Zwitserlood, Pienie; Bölte, Jens

    2011-01-01

    The idea that knowledge of events entails a universal spatial component, that is conceiving agents left of patients, was put to test by investigating native users of German sign language and native users of spoken German. Participants heard or saw event descriptions and had to illustrate the meaning

  5. A critical Action Research approach to curriculum development in a laboratory-based chemical engineering course

    Science.gov (United States)

    White, Scott R.

    This dissertation is a report of an attempt to critically evaluate a novel laboratory course from within the context of a chemical engineering curriculum. The research was done in a college classroom-laboratory setting, entrenched in the everydayness of classroom activities. All of the students, instructors, and educational researchers were knowing participants in this Action Research study. The students, a mixture of juniors, seniors, & graduate students, worked together on semester-long projects in groups that were mixed by age, gender and academic level. Qualitative techniques were used to gather different forms of representations of the students and instructors' experiences. Emergent patterns from the data gave strength to emergent knowledge claims that informed the instructors and the researcher about what the students were learning about performing experimental work and communicating results with their peers and instructor. The course challenged and in some cases changed the conceptions of instruction previously held by the students and the instructors. The course did not proceed without problems, yet the majority of these problems were overcome by the design of the course. Assertions and recommendations for improvement and application to other educational contexts are suggested.

  6. 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.

  7. An Action-Based Fine-Grained Access Control Mechanism for Structured Documents and Its Application

    Directory of Open Access Journals (Sweden)

    Mang Su

    2014-01-01

    Full Text Available This paper presents an action-based fine-grained access control mechanism for structured documents. Firstly, we define a describing model for structured documents and analyze the application scenarios. The describing model could support the permission management on chapters, pages, sections, words, and pictures of structured documents. Secondly, based on the action-based access control (ABAC model, we propose a fine-grained control protocol for structured documents by introducing temporal state and environmental state. The protocol covering different stages from document creation, to permission specification and usage control are given by using the Z-notation. Finally, we give the implementation of our mechanism and make the comparisons between the existing methods and our mechanism. The result shows that our mechanism could provide the better solution of fine-grained access control for structured documents in complicated networks. Moreover, it is more flexible and practical.

  8. Renormalized action improvements

    Energy Technology Data Exchange (ETDEWEB)

    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.

  9. Action physics

    Science.gov (United States)

    McGinness, Lachlan P.; Savage, C. M.

    2016-09-01

    More than a decade ago, Edwin Taylor issued a "call to action" that presented the case for basing introductory university mechanics teaching around the principle of stationary action [E. F. Taylor, Am. J. Phys. 71, 423-425 (2003)]. We report on our response to that call in the form of an investigation of the teaching and learning of the stationary action formulation of physics in a first-year university course. Our action physics instruction proceeded from the many-paths approach to quantum physics to ray optics, classical mechanics, and relativity. Despite the challenges presented by action physics, students reported it to be accessible, interesting, motivational, and valuable.

  10. 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.

  11. The extended loop representation of quantum gravity

    CERN Document Server

    Di Bartolo, C; Griego, J R

    1995-01-01

    A new representation of Quantum Gravity is developed. This formulation is based on an extension of the group of loops. The enlarged group, that we call the Extended Loop Group, behaves locally as an infinite dimensional Lie group. Quantum Gravity can be realized on the state space of extended loop dependent wavefunctions. The extended representation generalizes the loop representation and contains this representation as a particular case. The resulting diffeomorphism and hamiltonian constraints take a very simple form and allow to apply functional methods and simplify the loop calculus. In particular we show that the constraints are linear in the momenta. The nondegenerate solutions known in the loop representation are also solutions of the constraints in the new representation. The practical calculation advantages allows to find a new solution to the Wheeler-DeWitt equation. Moreover, the extended representation puts in a precise framework some of the regularization problems of the loop representation. We sh...

  12. Evidence-Based Practices: Applications of Concrete Representational Abstract Framework across Math Concepts for Students with Mathematics Disabilities

    Science.gov (United States)

    Agrawal, Jugnu; Morin, Lisa L.

    2016-01-01

    Students with mathematics disabilities (MD) experience difficulties with both conceptual and procedural knowledge of different math concepts across grade levels. Research shows that concrete representational abstract framework of instruction helps to bridge this gap for students with MD. In this article, we provide an overview of this strategy…

  13. Image Denoising Algorithm Based on Nonlocally Sparse Representation and Group%组约束与非局部稀疏的图像去噪算法

    Institute of Scientific and Technical Information of China (English)

    陈利霞; 赛朋飞

    2015-01-01

    The most existing denoising algorithms based on nonlocal sparse representation are strictly dependent on patch matching ,and the denoising performance is subject to the numbers of similar patches .So a image denoising algorithm based on nonlocally sparse representation and group is proposed . The group‐based constraints is introduced to the nonlocal sparse representation ,which can enhance the nonlocal similarity between image patches and the patch matching is more accurate .Experiments show that the model has a good performance in both visual effect and peak signal to noise ratio .%现有的非局部稀疏表示去噪算法大多严格依赖于块匹配,且其去噪性能受制于匹配的相似块的数量。鉴于此,提出了组约束与非局部稀疏的图像去噪模型。模型在非局部稀疏的基础上加入了分组约束,增强了图像块之间的非局部相似度,块匹配更加精确。实验表明,模型无论是在视觉效果还是峰值信噪比上均具有较好的性能。

  14. 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....

  15. Proteomic Approaches in Understanding Action Mechanisms of Metal-Based Anticancer Drugs

    OpenAIRE

    Wang, Ying; Chiu, Jen-Fu

    2008-01-01

    Medicinal inorganic chemistry has been stimulating largely by the success of the anticancer drug, cisplatin. Various metal complexes are currently used as therapeutic agents (e.g., Pt, Au, and Ru) in the treatment of malignant diseases, including several types of cancers. Understanding the mechanism of action of these metal-based drugs is for the design of more effective drugs. Proteomic approaches combined with other biochemical methods can provide comprehensive understanding of responses th...

  16. Nonlinear signal-based control with an error feedback action for nonlinear substructuring control

    Science.gov (United States)

    Enokida, Ryuta; Kajiwara, Koichi

    2017-01-01

    A nonlinear signal-based control (NSBC) method utilises the 'nonlinear signal' that is obtained from the outputs of a controlled system and its linear model under the same input signal. Although this method has been examined in numerical simulations of nonlinear systems, its application in physical experiments has not been studied. In this paper, we study an application of NSBC in physical experiments and incorporate an error feedback action into the method to minimise the error and enhance the feasibility in practice. Focusing on NSBC in substructure testing methods, we propose nonlinear substructuring control (NLSC), that is a more general form of linear substructuring control (LSC) developed for dynamical substructured systems. In this study, we experimentally and numerically verified the proposed NLSC via substructuring tests on a rubber bearing used in base-isolated structures. In the examinations, NLSC succeeded in gaining accurate results despite significant nonlinear hysteresis and unknown parameters in the substructures. The nonlinear signal feedback action in NLSC was found to be notably effective in minimising the error caused by nonlinearity or unknown properties in the controlled system. In addition, the error feedback action in NLSC was found to be essential for maintaining stability. A stability analysis based on the Nyquist criterion, which is used particularly for linear systems, was also found to be efficient for predicting the instability conditions of substructuring tests with NLSC and useful for the error feedback controller design.

  17. Script representation in patients with Alzheimer's disease.

    Science.gov (United States)

    Allain, Philippe; Le Gall, Didier; Foucher, Céline; Etcharry-Bouyx, Frédérique; Barré, Jean; Dubas, Frédéric; Berrut, Gilles

    2008-03-01

    We examined script representation in 26 patients with Alzheimer's disease (AD) compared to 31 healthy elderly subjects (HE). Participants were asked to sort cards describing actions belonging to eight scripts according to the script to which they belonged and according to their order of execution. Each script included actions which were low in centrality and distinctiveness (non-central actions and non-distinctive actions--NCA & NDA), and which were high in centrality (central actions--CA), distinctiveness (distinctive actions--DA), centrality and distinctiveness (central actions and distinctive action--CA & DA). These actions were presented in three conditions. In the first condition (scripts with headers--SH), the 43 actions belonging to three different scripts were given with each script header written on separate cards. The second condition (scripts without headers--SwH) used 46 actions belonging to three other scripts, but no script header was provided. In the third condition (scripts with distractor header--SDH), the 28 actions belonging to two other scripts were given with each script header and a distractor header written on separate cards. The results showed that performance of subjects with AD was significantly lower in all conditions. Overall, AD patients made significantly more sequencing errors than HE subjects. AD patients also committed significantly more sorting errors than HE subjects for all types of actions (NCA & NDA, CA, DA, CA & DA). These data are consistent with the view that AD produces impairment of both the syntactic and semantic dimensions of script representation.

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

    Directory of Open Access Journals (Sweden)

    Wolf Steven L

    2011-08-01

    Full Text Available Abstract 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.

  19. Women and trauma: transformation of self through mask making and action-based mask work

    OpenAIRE

    Birch, June Elizabeth

    2011-01-01

    This secondary analysis study examined the stories of six women who were impacted by trauma. These women attended a ten-week counselling group in which they participated in the construction of masks and in action-based mask work as a means of expressing and working through their trauma experiences. Based on a constructivist approach, the methodology employed in this study was a narrative inquiry centred on the work of Lieblich, Tuval-Mashiach, and Zilber (1998). The data were generated from o...

  20. Action Learning: Avoiding Conflict or Enabling Action

    Science.gov (United States)

    Corley, Aileen; Thorne, Ann

    2006-01-01

    Action learning is based on the premise that action and learning are inextricably entwined and it is this potential, to enable action, which has contributed to the growth of action learning within education and management development programmes. However has this growth in action learning lead to an evolution or a dilution of Revan's classical…

  1. 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.

  2. Mental Representations in Art Discourse

    Directory of Open Access Journals (Sweden)

    Katja Sudec

    2014-03-01

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

  3. THE SUBSIDIARY NATURE OF THE UNJUST ENRICHMENT ACTION. CONTRACT-BASED ACTION VS. ACTIO DE IN REM VERSO. JURISPRUDENCE SEPARATION ONLY

    Directory of Open Access Journals (Sweden)

    Eugenia VOICHECI

    2014-05-01

    Full Text Available For the purpose of recovering a paid amount within the insured sum, however, in addition to the owed amount, the insurer sues his client for claims. Does the insurer have, to this end, a cleared way towards unjust enrichment? The provisions of the 1864 Civil Code do not contain definitions of ex contractu and actio de in rem verso. The doctrine has established the acceptability requirements of actio de in rem verso, however, it did not do the same for ex contractu, and there is no notable change to this matter after the Civil Code became effective. This situation is also maintained in the current Law No.287/2009 on the Civil Code. Hence, the separation of the configuration and enforcement area of the two types of actions continues to be done in terms of jurisprudence by strictly relating to the case at hand. The study starts from an actual case the settling of which highlights the issue of determining the subsidiary nature, hence the acceptability of the unjust enrichment. The purpose of this study is to re/focus on an old dichotomy, i.e. the contract-based action (ex contractu and the action based on an licit deed, that of unjust enrichment (actio de in rem verso. The primary goal of the study consists of highlighting the aspects that the provisions of the 1864 Civil Code and those of the new Civil Code have in common or not in terms of the two types of actions before the court, the doctrine-related solutions given as concerns the characteristics and legal status of the two actions and the fact that, in the nex Civil Code as well, the separation line between the two actions is determined on the basis of jurisprudence, being left at the judges' discretion and wisdom, with all related consequences thereof.

  4. A NEW MODELLING METHOD FOR EVALUATING EXTERNAL DISTURBING POTENTIAL BASED ON THEORY OF UNIFIED REPRESENTATION OF GRAVITATIONAL FIELD

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    For a special use a new modelling method of evaluating external disturbing potential is presented in this paper. Being different from classical methods in physical geodesy this method is grounded upon the theory of unified representation of gravitational field. The models created in this way are particularly satisfactory for a high-speed computation of gravitational field in low altitude because they take account of topographic effects and have their kernel functions with simple structure and weak singularity.

  5. Community Action-Based Field Work: Training Counselors to Become Social Agents in Schools and Communities

    Directory of Open Access Journals (Sweden)

    Adonay Antonio Montes

    2011-12-01

    Full Text Available The requirement to complete field work hours as “action based pedagogy” allowed candidates in a school counseling program to broaden their cultural perceptions of diverse groups by engaging in action research projects of their own choosing, led by their interest in and commitment to becoming familiar with diverse populations of K-12 students. This assignment allowed candidates to immerse themselves in culturally rich schools as researchers to understand better the experiences of diverse students. In the planning and implementation of these projects, the school counseling trainees deconstructed cultural barriers, changed their perceptions and preconceived stereotypical notions about diverse groups and gained social advocacy skills for use in their work as professional counselors supporting the academic and aspirational growth of minority students. Candidates also became familiar with multicultural literature and resources available concerning diverse populations.

  6. 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.

  7. [Time perceptions and representations].

    Science.gov (United States)

    Tordjman, S

    2015-09-01

    fundamentally lacking in their physiological development due to possibly altered circadian rhythms, including arhythmy and asynchrony. Time measurement, based on the repetition of discontinuity at regular intervals, involves also a spatial representation. It is our own trajectory through space-time, and thus our own motion, including the physiological process of aging, that affords us a representation of the passing of time, just as the countryside seems to be moving past us when we travel in a vehicle. Chinese and Indian societies actually have circular representations of time, and linear representations of time and its trajectory through space-time are currently a feature of Western societies. Circular time is collective time, and its metaphysical representations go beyond the life of a single individual, referring to the cyclical, or at least nonlinear, nature of time. Linear time is individual time, in that it refers to the scale of a person's lifetime, and it is physically represented by an arrow flying ineluctably from the past to the future. An intermediate concept can be proposed that acknowledges the existence of linear time involving various arrows of time corresponding to different lifespans (human, animal, plant, planet lifespans, etc.). In fact, the very notion of time would depend on the trajectory of each arrow of time, like shooting stars in the sky with different trajectory lengths which would define different time scales. The time scale of these various lifespans are very different (for example, a few decades for humans and a few days or hours for insects). It would not make sense to try to understand the passage of time experienced by an insect which may live only a few hours based on a human time scale. One hour in an insect's life cannot be compared to one experienced by a human. Yet again, it appears that there is a coexistence of different clocks based here on different lifespans. Finally, the evolution of our society focused on the present moment and

  8. (Self)-representations on youtube

    DEFF Research Database (Denmark)

    Simonsen, Thomas Mosebo

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

  9. Unsupervised Learning of Action Primitives

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker; Kragic, Danica

    2010-01-01

    Action representation is a key issue in imitation learning for humanoids. With the recent finding of mirror neurons there has been a growing interest in expressing actions as a combination meaningful subparts called primitives. Primitives could be thought of as an alphabet for the human actions. ...

  10. Choosing goals, not rules: deciding among rule-based action plans.

    Science.gov (United States)

    Klaes, Christian; Westendorff, Stephanie; Chakrabarti, Shubhodeep; Gail, Alexander

    2011-05-12

    In natural situations, movements are often directed toward locations different from that of the evoking sensory stimulus. Movement goals must then be inferred from the sensory cue based on rules. When there is uncertainty about the rule that applies for a given cue, planning a movement involves both choosing the relevant rule and computing the movement goal based on that rule. Under these conditions, it is not clear whether primates compute multiple movement goals based on all possible rules before choosing an action, or whether they first choose a rule and then only represent the movement goal associated with that rule. Supporting the former hypothesis, we show that neurons in the frontoparietal reach areas of monkeys simultaneously represent two different rule-based movement goals, which are biased by the monkeys' choice preferences. Apparently, primates choose between multiple behavioral options by weighing against each other the movement goals associated with each option.

  11. Flexibility in infant actions during arm- and leg-based learning in a mobile paradigm.

    Science.gov (United States)

    Watanabe, Hama; Taga, Gentaro

    2009-01-01

    To understand young infants' flexible changes of learned actions when abrupt environmental changes occur, we examined fifty-four 3-month-olds who performed a mobile task, in which they learned to move the mobile by a string attached to their arms or legs (arm-based or leg-based learning). We manipulated the order of tests-arm to leg (AL) and leg to arm (LA)-and observed the time course of motion of four limbs. The infants in the AL condition showed a differentiated movement pattern, in which the movement of the connected arm was dominant, and when the connected limb changed, they immediately inhibited the prior movement pattern. The infants in the LA condition produced undifferentiated movement pattern of multiple limbs, which was maintained even when the critical limb was changed. The results suggest that the infants' flexibility of actions in a novel situation depends on the prior experience. We speculate neural mechanisms, which may underlie the difference between the arm-based and leg-based learning.

  12. Human-Nature for Climate Action: Nature-Based Solutions for Urban Sustainability

    Directory of Open Access Journals (Sweden)

    Helen Santiago Fink

    2016-03-01

    Full Text Available The global climate change agenda proceeds at an incremental pace while the Earth is approaching critical tipping points in its development trajectory. Climate action at this pinnacle juncture needs to be greatly accelerated and rooted in the fundamentals of the problem—human beings’ disconnection from nature. This paper underscores the valuable role nature and nature-based solutions can play in addressing climate change at the city scale and its implications for broader sustainability. Urban ecosystems (nature in cities are seen as an integral part of a proposed local climate action rubric wherein policy measures and integrated planning guide lowcarbon/impact development to create more resilient and sustainable urban environments. The use of green infrastructure is highlighted as a cost-effective means to contribute to mitigation and adaptation needs as well as to promote human wellbeing. The paper takes an exploratory view of the influence of ecosystem services, particularly cultural services, and its economics in relation to the individual and society to understand how biophilia can be nurtured to promote environmental stewardship and climate action.

  13. Tackling action-based video abstraction of animated movies for video browsing

    Science.gov (United States)

    Ionescu, Bogdan; Ott, Laurent; Lambert, Patrick; Coquin, Didier; Pacureanu, Alexandra; Buzuloiu, Vasile

    2010-07-01

    We address the issue of producing automatic video abstracts in the context of the video indexing of animated movies. For a quick browse of a movie's visual content, we propose a storyboard-like summary, which follows the movie's events by retaining one key frame for each specific scene. To capture the shot's visual activity, we use histograms of cumulative interframe distances, and the key frames are selected according to the distribution of the histogram's modes. For a preview of the movie's exciting action parts, we propose a trailer-like video highlight, whose aim is to show only the most interesting parts of the movie. Our method is based on a relatively standard approach, i.e., highlighting action through the analysis of the movie's rhythm and visual activity information. To suit every type of movie content, including predominantly static movies or movies without exciting parts, the concept of action depends on the movie's average rhythm. The efficiency of our approach is confirmed through several end-user studies.

  14. Kinetics of drug action in disease states: towards physiology-based pharmacodynamic (PBPD) models.

    Science.gov (United States)

    Danhof, Meindert

    2015-10-01

    Gerhard Levy started his investigations on the "Kinetics of Drug Action in Disease States" in the fall of 1980. The objective of his research was to study inter-individual variation in pharmacodynamics. To this end, theoretical concepts and experimental approaches were introduced, which enabled assessment of the changes in pharmacodynamics per se, while excluding or accounting for the cofounding effects of concomitant changes in pharmacokinetics. These concepts were applied in several studies. The results, which were published in 45 papers in the years 1984-1994, showed considerable variation in pharmacodynamics. These initial studies on kinetics of drug action in disease states triggered further experimental research on the relations between pharmacokinetics and pharmacodynamics. Together with the concepts in Levy's earlier publications "Kinetics of Pharmacologic Effects" (Clin Pharmacol Ther 7(3): 362-372, 1966) and "Kinetics of pharmacologic effects in man: the anticoagulant action of warfarin" (Clin Pharmacol Ther 10(1): 22-35, 1969), they form a significant impulse to the development of physiology-based pharmacodynamic (PBPD) modeling as novel discipline in the pharmaceutical sciences. This paper reviews Levy's research on the "Kinetics of Drug Action in Disease States". Next it addresses the significance of his research for the evolution of PBPD modeling as a scientific discipline. PBPD models contain specific expressions to characterize in a strictly quantitative manner processes on the causal path between exposure (in terms of concentration at the target site) and the drug effect (in terms of the change in biological function). Pertinent processes on the causal path are: (1) target site distribution, (2) target binding and activation and (3) transduction and homeostatic feedback.

  15. Method for Face Identification with Facial Action Coding System: FACS Based on Eigen Value Decomposion

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2012-12-01

    Full Text Available Method for face identification based on eigen value decomposition together with tracing trajectories in the eigen space after the eigen value decomposition is proposed. The proposed method allows person to person differences due to faces in the different emotions. By using the well known action unit approach, the proposed method admits the faces in the different emotions. Experimental results show that recognition performance depends on the number of targeted peoples. The face identification rate is 80% for four peoples of targeted number while 100% is achieved for the number of targeted number of peoples is two.

  16. Mindfulness-Action Based Cognitive Behavioral Therapy for concurrent Binge Eating Disorder and Substance Use Disorders.

    Science.gov (United States)

    Courbasson, Christine M; Nishikawa, Yasunori; Shapira, Leah B

    2011-01-01

    Individuals with Binge Eating Disorder (BED) often evidence comorbid Substance Use Disorders (SUD), resulting in poor outcome. This study is the first to examine treatment outcome for this concurrent disordered population. In this pilot study, 38 individuals diagnosed with BED and SUD participated in a 16-week group Mindfulness-Action Based Cognitive Behavioral Therapy (MACBT). Participants significantly improved on measures of objective binge eating episodes; disordered eating attitudes; alcohol and drug addiction severity; and depression. Taken together, MACBT appears to hold promise in treating individuals with co-existing BED-SUD.

  17. Action experience alters 3-month-old infants’ perception of others’ actions

    Science.gov (United States)

    Sommerville, Jessica A.; Woodward, Amanda L.; Needham, Amy

    2014-01-01

    An intervention facilitated 3-month-old infants’ apprehension of objects either prior to (reach first), or after (watch first) viewing another person grasp similar objects in a visual habituation procedure. Action experience facilitated action perception: reach-first infants focused on the relation between the actor and her goal, but watch-first infants did not. Infants’ sensitivity to the actor’s goal was correlated with their engagement in object-directed contact with the toys. These findings indicate that infants can rapidly form goal-based action representations and suggest a developmental link between infants’ goal directed actions and their ability to detect goals in the actions of others. PMID:15833301

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

    Science.gov (United States)

    Gabbard, Carl; Bobbio, Tatiana

    2011-03-01

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

  19. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian; Paulson, Olaf B

    2002-01-01

    Functional imaging studies have demonstrated that processing of man-made objects activate the left ventral premotor cortex, which is known to be concerned with motor function. This has led to the suggestion that the comprehension of man-made objects may rely on motor-based knowledge of object uti...... organized. Instead, the data are compatible with the suggestion that categories differ in the weight they put on different types of knowledge.......Functional imaging studies have demonstrated that processing of man-made objects activate the left ventral premotor cortex, which is known to be concerned with motor function. This has led to the suggestion that the comprehension of man-made objects may rely on motor-based knowledge of object...... utilization (action knowledge). Here we show that the left ventral premotor cortex is activated during categorization of "both" fruit/vegetables and articles of clothing, relative to animals and nonmanipulable man-made objects. This observation suggests that action knowledge may not be important...

  20. An Evaluation of Community-Based Action Research Program for Medical Undergraduates in Rural Pondicherry

    Directory of Open Access Journals (Sweden)

    Murugan V

    2013-11-01

    Full Text Available Objective: To obtain the learners’ reaction to a community-based action research program in a rural setting of Pondicherry. Methods: Both quantitative (post-then-pre rating and qualitative (response to open ended questions feedback from 125 medical students exposed to this program was obtained. Mean values were calculated for pre and post self-rating on skills acquired by the students in retro-pre feedback. The content analysis of the qualitative data was undertaken. Results: There was significant improvement in their perceived abilities to follow basic steps in carrying out research such as – problem identification, literature search, drafting a proposal, preparation of questionnaire, data collection, analysis and its reporting. Our approach could contribute to development of cognitive, social-emotional and vocational domains of the students. Conclusions: Overall, our community-based action research program is taking a shape and getting mainstreamed in the exiting curriculum. It could sensitize students to basic steps in research and contributed to their cognitive, social-emotional and vocational development. Further work is needed to increase its scope and intensity to achieve the development of cultural, moral and ethical domains.