WorldWideScience

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...... from the way the body parts are moving, but as well from how their eect on the involved object. While human movements can look vastly dierent even under minor changes in location, orientation and scale, the use of the object can provide a strong invariant for the detection of motion primitives...

  3. 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.

  4. 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.

  5. Representation dimension for Hopf actions

    Institute of Scientific and Technical Information of China (English)

    SUN JuXiang; LIU GongXiang

    2012-01-01

    Let H be a finite-dimensional Hopf algebra and assume that both H and H* are semisimple.The main result of this paper is to show that the representation dimension is an invariant under cleft extensions of H,that is,rep.dim(A) =rep.dim(A#σH).Some of the applications of this equality are also given.

  6. XML-BASED REPRESENTATION

    Energy Technology Data Exchange (ETDEWEB)

    R. KELSEY

    2001-02-01

    For focused applications with limited user and use application communities, XML can be the right choice for representation. It is easy to use, maintain, and extend and enjoys wide support in commercial and research sectors. When the knowledge and information to be represented is object-based and use of that knowledge and information is a high priority, then XML-based representation should be considered. This paper discusses some of the issues involved in using XML-based representation and presents an example application that successfully uses an XML-based representation.

  7. Action co-representation and social exclusion.

    Science.gov (United States)

    Costantini, Marcello; Ferri, Francesca

    2013-05-01

    Humans are thought to be able to form shared representations, considered a keystone of social cognition. However, whether and to what extent such representations are social in nature is still open for debate. In the present study, we address the question of whether action co-representation can be modulated by social attitudes, such as judgments about one's own social status. Two groups of participants performed an Interactive Simon task after the experimental induction of a feeling of social inclusion or exclusion (ostracism) by means of a virtual ball tossing game. Results showed a compatibility effect in included, but not in excluded participants. This indicates that judgments about one's own social status modulate action co-representation. We suggest that this modulation may occur by way of a redirection of one's attentional focus away from others when one experiences social exclusion. This is a far-reaching issue given the increasing need for integration in modern society. Indeed, if integration fails, modern society fails also. PMID:23543105

  8. 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

  9. 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

  10. Action and representation of action during childhood and adolescence: a functional approach.

    Science.gov (United States)

    Assaiante, C

    2012-01-01

    Our scientific activity is focused on the field of action and representation of action from various adaptative situations during the life span, including pathology and extreme environment such as microgravity. The early action/perception matching, subserving the motor simulation network, is probably a major milestone for the building of action and representation of action during the course of ontogenesis. We have developed a functional approach of motor development based on a gradual mastering of coordination, adaptation and anticipation in postural control in the course of ontogenesis from babies to adolescents. This functional approach is recently associated with studies of brain structures involved in action and representation of action in children and adolescents with typical or atypical neurodevelopment. From our developmental studies, it was possible to put in light two turning points during motor development, such as 6/7 years of age and adolescence. The first step for children consists in building a repertoire of postural strategies. The second step consists in learning to select postural strategy depending on the characteristics of the task and the environmental requirements. An appropriate selection means to anticipate the consequence of the movement in order to maintain balance control and efficiency of the task. Taking into account the complexity of the parameters to control and the late maturation of anticipation and representation of action, it is not surprising that the development of postural control continues up to late periods during childhood and adolescence. PMID:22200341

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

    Science.gov (United States)

    Tsagkaridis, Konstantinos; Watson, Christine E; Jax, Steven A; Buxbaum, Laurel J

    2014-01-01

    A number of studies have explored the role of associative/event-based (thematic) and categorical (taxonomic) relations in the organization of object representations. Recent evidence suggests that thematic information may be particularly important in determining relationships between manipulable artifacts. However, although sensorimotor information is on many accounts an important component of manipulable artifact representations, little is known about the role that action may play during the processing of semantic relationships (particularly thematic relationships) between multiple objects. In this study, we assessed healthy and left hemisphere stroke participants to explore three questions relevant to object relationship processing. First, we assessed whether participants tended to favor thematic relations including 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 with manipulable artifacts. Second, we assessed whether the underlying constructs of event relatedness, action relatedness, and categorical relatedness determined the choices that participants made. Third, we assessed the hypothesis that degraded action knowledge and/or damage to temporo-parietal cortex, a region of the brain associated with the representation of action knowledge, would reduce the influence of action on the choice task. Experiment 1 showed that explicit ratings of event, action, and categorical relatedness were differentially predictive of 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

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

    Science.gov (United States)

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

    2014-02-01

    In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach. PMID:26270909

  13. Building of action and representation of action during infancy, childhood and adolescence

    Directory of Open Access Journals (Sweden)

    Assaiante Christine

    2011-12-01

    Full Text Available The early action/perception matching, subserving the motor simulation network, is probably a major milestone for the building of action and representation of action during the course of ontogenesis.We have developed a functional approach of motor development based on a gradual mastering of coordination, adaptation and anticipation in postural control in the course of ontogenesis from babies to adolescents. This functional approach is recently associated with studies of brain structures involved in action and representation of action in children and adolescents. From our developmental studies, it was possible to put in light two turning points during motor development, such as 6/7 years of age and adolescence. The first step for children consists in building a repertoire of postural strategies. The second step consists in learning to select postural strategy depending on the characteristics of the task and the environmental requirements. An appropriate selection means to anticipate the consequence of the movement in order to maintain balance control and efficiency of the task. Taking into account the complexity of the parameters to control and the late maturation of anticipation and representation of action, it is not surprising that the development of postural control continues up to late periods during childhood and adolescence.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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...... and RLJC, our second method learns structural object models for robust object detection and pose estimation by probabilistic inference. To these models, the method associates grasp experiences autonomously learned by trial and error. These experiences form a nonparametric representation of grasp success...

  19. Repetition-induced plasticity of motor representations of action sounds.

    Science.gov (United States)

    Bourquin, Nathalie M-P; Simonin, Alexandre; Clarke, Stephanie

    2013-01-01

    Action-related sounds are known to increase the excitability of motoneurones within the primary motor cortex (M1), but the role of this auditory input remains unclear. We investigated repetition priming-induced plasticity, which is characteristic of semantic representations, in M1 by applying transcranial magnetic stimulation pulses to the hand area. Motor evoked potentials (MEPs) were larger while subjects were listening to sounds related versus unrelated to manual actions. Repeated exposure to the same manual-action-related sound yielded a significant decrease in MEPs when right, hand area was stimulated; no repetition effect was observed for manual-action-unrelated sounds. The shared repetition priming characteristics suggest that auditory input to the right primary motor cortex is part of auditory semantic representations. PMID:23064984

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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.

  7. The representation of knowledge within model-based control systems

    Energy Technology Data Exchange (ETDEWEB)

    Weygand, D.P.; Koul, R.

    1987-01-01

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

  8. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

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

  9. 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.

  10. On volume-source representations based on the representation theorem

    Science.gov (United States)

    Ichihara, Mie; Kusakabe, Tetsuya; Kame, Nobuki; Kumagai, Hiroyuki

    2016-01-01

    We discuss different ways to characterize a moment tensor associated with an actual volume change of ΔV C , which has been represented in terms of either the stress glut or the corresponding stress-free volume change ΔV T . Eshelby's virtual operation provides a conceptual model relating ΔV C to ΔV T and the stress glut, where non-elastic processes such as phase transitions allow ΔV T to be introduced and subsequent elastic deformation of - ΔV T is assumed to produce the stress glut. While it is true that ΔV T correctly represents the moment tensor of an actual volume source with volume change ΔV C , an explanation as to why such an operation relating ΔV C to ΔV T exists has not previously been given. This study presents a comprehensive explanation of the relationship between ΔV C and ΔV T based on the representation theorem. The displacement field is represented using Green's function, which consists of two integrals over the source surface: one for displacement and the other for traction. Both integrals are necessary for representing volumetric sources, whereas the representation of seismic faults includes only the first term, as the second integral over the two adjacent fault surfaces, across which the traction balances, always vanishes. Therefore, in a seismological framework, the contribution from the second term should be included as an additional surface displacement. We show that the seismic moment tensor of a volume source is directly obtained from the actual state of the displacement and stress at the source without considering any virtual non-elastic operations. A purely mathematical procedure based on the representation theorem enables us to specify the additional imaginary displacement necessary for representing a volume source only by the displacement term, which links ΔV C to ΔV T . It also specifies the additional imaginary stress necessary for representing a moment tensor solely by the traction term, which gives the "stress glut." The

  11. 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.

  12. 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.

  13. 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

    2015-01-01

    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. PMID:26193271

  14. 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

    2015-01-01

    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. PMID:26193271

  15. 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.

  16. 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.

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

    OpenAIRE

    Frey, Scott H.; POVINELLI, DANIEL J.

    2012-01-01

    The ability to adjust one's ongoing actions in the anticipation of forthcoming task demands is considered as strong evidence for the existence of internal action representations. Studies of action selection in tool use reveal that the behaviours that we choose in the present moment differ depending on what we intend to do next. Further, they point to a specialized role for mechanisms within the human cerebellum and dominant left cerebral hemisphere in representing the likely sensory costs of ...

  18. A shared numerical representation for action and perception

    Science.gov (United States)

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

    2016-01-01

    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. DOI: http://dx.doi.org/10.7554/eLife.16161.001 PMID:27504969

  19. A shared numerical representation for action and perception.

    Science.gov (United States)

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

    2016-01-01

    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. PMID:27504969

  20. 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...

  1. 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.

  2. 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

  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. 39 CFR 501.13 - False representations of Postal Service actions.

    Science.gov (United States)

    2010-07-01

    ... MANUFACTURE AND DISTRIBUTE POSTAGE EVIDENCING SYSTEMS § 501.13 False representations of Postal Service actions... Evidencing Systems. The Postal Service reserves the right to suspend and/or revoke the authorization to manufacture or distribute Postage Evidencing Systems throughout the United States or any part thereof...

  5. Entrainment and task co-representation effects for discrete and continuous action sequences.

    Science.gov (United States)

    van der Wel, Robrecht P R D; Fu, En

    2015-12-01

    A large body of work has established an influence of other people's actions on our own actions. For example, actors entrain to the movements of others, in studies that typically employ continuous movements. Likewise, studies on co-representation have shown that people automatically co-represent a co-actor's task, in studies that typically employ discrete actions. Here we examined entrainment and co-representation within a single task paradigm. Participants sat next to a confederate while simultaneously moving their right hand back and forth between two targets. We crossed whether or not the participant and the confederate moved over an obstacle and manipulated whether participants generated discrete or continuous movement sequences, while varying the space between the actors and whether the actors could see each other's movements. Participants moved higher when the confederate cleared an obstacle than when he did not. For continuous movements, this effect depended on the availability of visual information, as would be expected on the basis of entrainment. In contrast, the co-actor's task modulated the height of discrete movements, regardless of the availability of visual information, which is consistent with co-representation. Space did not have an effect. These results provide new insights into the interplay between co-representation and entrainment for discrete- and continuous-action tasks. PMID:25911443

  6. Spatial representations in older adults are not modified by action: Evidence from tool use.

    Science.gov (United States)

    Costello, Matthew C; Bloesch, Emily K; Davoli, Christopher C; Panting, Nicholas D; Abrams, Richard A; Brockmole, James R

    2015-09-01

    Theories of embodied perception hold that the visual system is calibrated by both the body schema and the action system, allowing for adaptive action-perception responses. One example of embodied perception involves the effects of tool use on distance perception, in which wielding a tool with the intention to act upon a target appears to bring that object closer. This tool-based spatial compression (i.e., tool-use effect) has been studied exclusively with younger adults, but it is unknown whether the phenomenon exists with older adults. In this study, we examined the effects of tool use on distance perception in younger and older adults in 2 experiments. In Experiment 1, younger and older adults estimated the distances of targets just beyond peripersonal space while either wielding a tool or pointing with the hand. Younger adults, but not older adults, estimated targets to be closer after reaching with a tool. In Experiment 2, younger and older adults estimated the distance to remote targets while using either a baton or a laser pointer. Younger adults displayed spatial compression with the laser pointer compared to the baton, although older adults did not. Taken together, these findings indicate a generalized absence of the tool-use effect in older adults during distance estimation, suggesting that the visuomotor system of older adults does not remap from peripersonal to extrapersonal spatial representations during tool use. PMID:26052886

  7. Unifying Class-Based Representation Formalisms

    CERN Document Server

    Calvanese, D; Nardi, D; 10.1613/jair.548

    2011-01-01

    The notion of class is ubiquitous in computer science and is central in many formalisms for the representation of structured knowledge used both in knowledge representation and in databases. In this paper we study the basic issues underlying such representation formalisms and single out both their common characteristics and their distinguishing features. Such investigation leads us to propose a unifying framework in which we are able to capture the fundamental aspects of several representation languages used in different contexts. The proposed formalism is expressed in the style of description logics, which have been introduced in knowledge representation as a means to provide a semantically well-founded basis for the structural aspects of knowledge representation systems. The description logic considered in this paper is a subset of first order logic with nice computational characteristics. It is quite expressive and features a novel combination of constructs that has not been studied before. The distinguish...

  8. FIRM - A Graph-Based Intermediate Representation

    OpenAIRE

    Braun, Matthias; Buchwald, Sebastian; Zwinkau, Andreas

    2011-01-01

    We present our compiler intermediate representation Firm. Programs are always in SSA-form enabling a representation as graphs. We argue that this naturally encodes context information simplifying many analyses and optimizations. Instructions are connected by dependency edges relaxing the total to a partial order inside a basic block. For example alias analysis results can be directly encoded in the graph structure. The paper gives an overview of the representation and focuses on its construct...

  9. 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 machin......-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.......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...

  10. Value representations: a value based dialogue tool

    DEFF Research Database (Denmark)

    Petersen, Marianne Graves; Rasmussen, Majken Kirkegaard

    2011-01-01

    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...

  11. Facial expression recognition with facial parts based sparse representation classifier

    Science.gov (United States)

    Zhi, Ruicong; Ruan, Qiuqi

    2009-10-01

    Facial expressions play important role in human communication. The understanding of facial expression is a basic requirement in the development of next generation human computer interaction systems. Researches show that the intrinsic facial features always hide in low dimensional facial subspaces. This paper presents facial parts based facial expression recognition system with sparse representation classifier. Sparse representation classifier exploits sparse representation to select face features and classify facial expressions. The sparse solution is obtained by solving l1 -norm minimization problem with constraint of linear combination equation. Experimental results show that sparse representation is efficient for facial expression recognition and sparse representation classifier obtain much higher recognition accuracies than other compared methods.

  12. 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. ...

  13. 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.

  14. Robust Pedestrian Classification Based on Hierarchical Kernel Sparse Representation.

    Science.gov (United States)

    Sun, Rui; Zhang, Guanghai; Yan, Xiaoxing; Gao, Jun

    2016-01-01

    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. PMID:27537888

  15. 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. PMID:26993491

  16. 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.

  17. 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...

  18. Active Dictionary Learning in Sparse Representation Based Classification

    OpenAIRE

    Xu, Jin; He, Haibo; Man, Hong

    2014-01-01

    Sparse representation, which uses dictionary atoms to reconstruct input vectors, has been studied intensively in recent years. A proper dictionary is a key for the success of sparse representation. In this paper, an active dictionary learning (ADL) method is introduced, in which classification error and reconstruction error are considered as the active learning criteria in selection of the atoms for dictionary construction. The learned dictionaries are caculated in sparse representation based...

  19. 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.

  20. 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.

  1. Improved Separability Criteria Based on Bloch Representation of Density Matrices.

    Science.gov (United States)

    Shen, Shu-Qian; Yu, Juan; Li, Ming; Fei, Shao-Ming

    2016-01-01

    The correlation matrices or tensors in the Bloch representation of density matrices are encoded with entanglement properties. In this paper, based on the Bloch representation of density matrices, we give some new separability criteria for bipartite and multipartite quantum states. Theoretical analysis and some examples show that the proposed criteria can be more efficient than the previous related criteria. PMID:27350031

  2. 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.

  3. The Representation of Objects in Apraxia: From Action Execution to Error Awareness.

    Science.gov (United States)

    Canzano, Loredana; Scandola, Michele; Gobbetto, Valeria; Moretto, Giuseppe; D'Imperio, Daniela; Moro, Valentina

    2016-01-01

    Apraxia is a well-known syndrome characterized by the sufferer's inability to perform routine gestures. In an attempt to understand the syndrome better, various different theories have been developed and a number of classifications of different subtypes have been proposed. In this article review, we will address these theories with a specific focus on how the use of objects helps us to better understand upper limb apraxia. With this aim, we will consider transitive vs. intransitive action dissociation as well as less frequent types of apraxia involving objects, i.e., constructive apraxia and magnetic apraxia. Pantomime and the imitation of objects in use are also considered with a view to dissociating the various different components involved in upper limb apraxia. Finally, we discuss the evidence relating to action recognition and awareness of errors in the execution of actions. Various different components concerning the use of objects emerge from our analysis and the results show that knowledge of an object and sensory-motor representations are supported by other functions such as spatial and body representations, executive functions and monitoring systems. PMID:26903843

  4. Crowd behavior representation: an attribute-based approach.

    Science.gov (United States)

    Rabiee, Hamidreza; Haddadnia, Javad; Mousavi, Hossein

    2016-01-01

    In crowd behavior studies, a model of crowd behavior needs to be trained using the information extracted from video sequences. Most of the previous methods are based on low-level visual features because there are only crowd behavior labels available as ground-truth information in crowd datasets. However, there is a huge semantic gap between low-level motion/appearance features and high-level concept of crowd behaviors. In this paper, we tackle the problem by introducing an attribute-based scheme. While similar strategies have been employed for action and object recognition, to the best of our knowledge, for the first time it is shown that the crowd emotions can be used as attributes for crowd behavior understanding. We explore the idea of training a set of emotion-based classifiers, which can subsequently be used to indicate the crowd motion. In this scheme, we collect a large dataset of video clips and provide them with both annotations of "crowd behaviors" and "crowd emotions". We test the proposed emotion based crowd representation methods on our dataset. The obtained promising results demonstrate that the crowd emotions enable the construction of more descriptive models for crowd behaviors. We aim at publishing the dataset with the article, to be used as a benchmark for the communities. PMID:27512638

  5. Navigation based on a sensorimotor representation: a virtual reality study

    Science.gov (United States)

    Zetzsche, Christoph; Galbraith, Christopher; Wolter, Johannes; Schill, Kerstin

    2007-02-01

    We investigate the hypothesis that the basic representation of space which underlies human navigation does not resemble an image-like map and is not restricted by the laws of Euclidean geometry. For this we developed a new experimental technique in which we use the properties of a virtual environment (VE) to directly influence the development of the representation. We compared the navigation performance of human observers under two conditions. Either the VE is consistent with the geometrical properties of physical space and could hence be represented in a map-like fashion, or it contains severe violations of Euclidean metric and planar topology, and would thus pose difficulties for the correct development of such a representation. Performance is not influenced by this difference, suggesting that a map-like representation is not the major basis of human navigation. Rather, the results are consistent with a representation which is similar to a non-planar graph augmented with path length information, or with a sensorimotor representation which combines sensory properties and motor actions. The latter may be seen as part of a revised view of perceptual processes due to recent results in psychology and neurobiology, which indicate that the traditional strict separation of sensory and motor systems is no longer tenable.

  6. 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.

  7. The representation of risk in routine medical experience: what actions for contemporary health policy?

    Directory of Open Access Journals (Sweden)

    Silvia Riva

    Full Text Available BACKGROUND: The comprehension of appropriate information about illnesses and treatments, can have beneficial effects on patients' satisfaction and on important health outcomes. However, it is questionable whether people are able to understand risk properly. AIM: To describe patients' representation of risk in common medical experiences by linking such a representation to the concept of trust. A further goal was to test whether the representation of risk in the medical domain is associated to the level of expertise. The third goal was to verify whether socio-demographic differences influence the representation of risk. METHODS: Eighty voluntary participants from 6 health-centers in northern Italy were enrolled to conduct a semi-structured interview which included demographic questions, term-associations about risk representation, closed and open questions about attitudes and perception of risk in the medical context, as well as about medical expertise and trust. RESULTS: The results showed that people do not have in mind a scientific definition of risk in medicine. Risk is seen as a synonym for surgery and disease and it is often confused with fear. However, general knowledge of medical matters helps people to have a better health management through risk identification and risk information, adoption of careful behaviors and tendency to have a critical view about safety and medical news. Finally, trust proved to be an important variable in risk representation and risk and trust were correlated positively. CONCLUSIONS: People must receive appropriate information about the risks and benefits of treatment, in a form that they can understand and apply to their own circumstances. Moreover, contemporary health policy should empower patients to adopt an active self-care attitude. Methodologies to enhance people's decision-making outcomes based on better risk communication should be improved in order to enable low literacy population as well elderly

  8. 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.

  9. 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.

  10. 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.

  11. A generalized representation-based approach for hyperspectral image classification

    Science.gov (United States)

    Li, Jiaojiao; Li, Wei; Du, Qian; Li, Yunsong

    2016-05-01

    Sparse representation-based classifier (SRC) is of great interest recently for hyperspectral image classification. It is assumed that a testing pixel is linearly combined with atoms of a dictionary. Under this circumstance, the dictionary includes all the training samples. The objective is to find a weight vector that yields a minimum L2 representation error with the constraint that the weight vector is sparse with a minimum L1 norm. The pixel is assigned to the class whose training samples yield the minimum error. In addition, collaborative representation-based classifier (CRC) is also proposed, where the weight vector has a minimum L2 norm. The CRC has a closed-form solution; when using class-specific representation it can yield even better performance than the SRC. Compared to traditional classifiers such as support vector machine (SVM), SRC and CRC do not have a traditional training-testing fashion as in supervised learning, while their performance is similar to or even better than SVM. In this paper, we investigate a generalized representation-based classifier which uses Lq representation error, Lp weight norm, and adaptive regularization. The classification performance of Lq and Lp combinations is evaluated with several real hyperspectral datasets. Based on these experiments, recommendation is provide for practical implementation.

  12. Cervigram image segmentation based on reconstructive sparse representations

    Science.gov (United States)

    Zhang, Shaoting; Huang, Junzhou; Wang, Wei; Huang, Xiaolei; Metaxas, Dimitris

    2010-03-01

    We proposed an approach based on reconstructive sparse representations to segment tissues in optical images of the uterine cervix. Because of large variations in image appearance caused by the changing of the illumination and specular reflection, the color and texture features in optical images often overlap with each other and are not linearly separable. By leveraging sparse representations the data can be transformed to higher dimensions with sparse constraints and become more separated. K-SVD algorithm is employed to find sparse representations and corresponding dictionaries. The data can be reconstructed from its sparse representations and positive and/or negative dictionaries. Classification can be achieved based on comparing the reconstructive errors. In the experiments we applied our method to automatically segment the biomarker AcetoWhite (AW) regions in an archive of 60,000 images of the uterine cervix. Compared with other general methods, our approach showed lower space and time complexity and higher sensitivity.

  13. Prototype Theory Based Feature Representation for PolSAR Images

    OpenAIRE

    Huang Xiaojing; Yang Xiangli; Huang Pingping; Yang Wen

    2016-01-01

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

  14. Action Capture: A VR-Based Method for Character Animation

    Science.gov (United States)

    Jung, Bernhard; Amor, Heni Ben; Heumer, Guido; Vitzthum, Arnd

    This contribution describes a Virtual Reality (VR) based method for character animation that extends conventional motion capture by not only tracking an actor's movements but also his or her interactions with the objects of a virtual environment. Rather than merely replaying the actor's movements, the idea is that virtual characters learn to imitate the actor's goal-directed behavior while interacting with the virtual scene. Following Arbib's equation action = movement + goal we call this approach Action Capture. For this, the VR user's body movements are analyzed and transformed into a multi-layered action representation. Behavioral animation techniques are then applied to synthesize animations which closely resemble the demonstrated action sequences. As an advantage, captured actions can often be naturally applied to virtual characters of different sizes and body proportions, thus avoiding retargeting problems of motion capture.

  15. Supervised Filter Learning for Representation Based Face Recognition

    Science.gov (United States)

    Bi, Chao; Zhang, Lei; Qi, Miao; Zheng, Caixia; Yi, Yugen; Wang, Jianzhong; Zhang, Baoxue

    2016-01-01

    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. PMID:27416030

  16. 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.

  17. 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.

  18. 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.

  19. The representation of knowledge within model-based control systems

    International Nuclear Information System (INIS)

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

  20. 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.

  1. 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.

  2. 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.

  3. Structure-Preserving Binary Representations for RGB-D Action Recognition.

    Science.gov (United States)

    Yu, Mengyang; Liu, Li; Shao, Ling

    2016-08-01

    In this paper, we propose a novel binary local representation for RGB-D video data fusion with a structure-preserving projection. Our contribution consists of two aspects. Toacquire a general feature for the video data, we convert the problem to describing the gradient fields of RGB and depth information of video sequences. With the local fluxes of the gradient fields, which include the orientation and the magnitude of the neighborhood of each point, a new kind of continuous local descriptor called Local Flux Feature(LFF) is obtained. Then the LFFs from RGB and depth channels are fused into a Hamming space via the Structure Preserving Projection (SPP). Specifically, an orthogonal projection matrix is applied to preserve the pairwise structure with a shape constraint to avoid the collapse of data structure in the projected space. Furthermore, a bipartite graph structure of data is taken into consideration, which is regarded as a higher level connection between samples and classes than the pairwise structure of local features. Theextensive experiments show not only the high efficiency of binary codes and the effectiveness of combining LFFs from RGB-D channels via SPP on various action recognition benchmarks of RGB-D data, but also the potential power of LFF for general action recognition. PMID:26485473

  4. Incorporating Feature-Based Annotations into Automatically Generated Knowledge Representations

    Science.gov (United States)

    Lumb, L. I.; Lederman, J. I.; Aldridge, K. D.

    2006-12-01

    Earth Science Markup Language (ESML) is efficient and effective in representing scientific data in an XML- based formalism. However, features of the data being represented are not accounted for in ESML. Such features might derive from events (e.g., a gap in data collection due to instrument servicing), identifications (e.g., a scientifically interesting area/volume in an image), or some other source. In order to account for features in an ESML context, we consider them from the perspective of annotation, i.e., the addition of information to existing documents without changing the originals. Although it is possible to extend ESML to incorporate feature-based annotations internally (e.g., by extending the XML schema for ESML), there are a number of complicating factors that we identify. Rather than pursuing the ESML-extension approach, we focus on an external representation for feature-based annotations via XML Pointer Language (XPointer). In previous work (Lumb &Aldridge, HPCS 2006, IEEE, doi:10.1109/HPCS.2006.26), we have shown that it is possible to extract relationships from ESML-based representations, and capture the results in the Resource Description Format (RDF). Thus we explore and report on this same requirement for XPointer-based annotations of ESML representations. As in our past efforts, the Global Geodynamics Project (GGP) allows us to illustrate with a real-world example this approach for introducing annotations into automatically generated knowledge representations.

  5. Argumentation-Based Collaborative Inquiry in Science Through Representational Work: Impact on Primary Students' Representational Fluency

    Science.gov (United States)

    Nichols, Kim; Gillies, Robyn; Hedberg, John

    2016-06-01

    This study explored the impact of argumentation-promoting collaborative inquiry and representational work in science on primary students' representational fluency. Two hundred sixty-six year 6 students received instruction on natural disasters with a focus on collaborative inquiry. Students in the Comparison condition received only this instruction. Students in the Explanation condition were also instructed with a focus on explanations using representations. Students in the Argumentation condition received similar instruction to the Comparison and Explanation conditions but were also instructed with a focus on argumentation using representations. Conceptual understanding and representational competencies (interpreting, explaining and constructing representations) were measured prior to and immediately following the instruction. A small group collaborative representational task was video recorded at the end of the instruction and coded for modes of knowledge-building discourse; knowledge-sharing and knowledge-construction. Higher measures of conceptual understanding, representational competencies and knowledge-construction discourse were taken together as representational fluency. Students in all conditions showed significant improvement in conceptual understanding, interpreting representations and explaining representations. Students in the Comparison and Argumentation conditions also showed significantly improved scores in constructing representations. When compared to the other conditions, the Explanation group had the highest scores in conceptual understanding and also interpreting and explaining representations. While the Argumentation group had the highest scores for constructing representations, their scores for conceptual understanding as well as interpreting and explaining representations were also high. There was no difference between the groups in knowledge-sharing discourse; however, the Argumentation group displayed the highest incidence of knowledge

  6. 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.

  7. New bases of representation for the unitary parasupersymmetry algebra

    CERN Document Server

    Fakhri,

    2003-01-01

    Representation bases of unitary parasupersymmetry algebra of arbitrary order p is constructed by some one-dimensional models which are shape invariant with respect to the main quantum number n. Consequently, the isospectral Hamiltonians and their exact solutions are obtained as labelled by the main quantum number n. (letter to the editor)

  8. New bases of representation for the unitary parasupersymmetry algebra

    Energy Technology Data Exchange (ETDEWEB)

    Fakhri, H

    2003-01-17

    Representation bases of unitary parasupersymmetry algebra of arbitrary order p is constructed by some one-dimensional models which are shape invariant with respect to the main quantum number n. Consequently, the isospectral Hamiltonians and their exact solutions are obtained as labelled by the main quantum number n. (letter to the editor)0.

  9. 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.

  10. Does training general practitioners to elicit patients’ illness representations and action plans influence their communication as a whole?

    NARCIS (Netherlands)

    Ridder, D.T.D. de; Theunissen, N.C.M.; Dulmen, A.M. van

    2007-01-01

    Objective: To examine whether the discussion of illness representations and action plans during medical encounters affects the way patients and general practitioners (GPs) communicate. Methods: In a quasi-experimental design, 10 GPs first performed care-as-usual conversations with patients. After a

  11. Does training general practitioner to elicit patients' illness representations and action plans influence their communication as a whole?

    NARCIS (Netherlands)

    Ridder, D.T.D. de; Theunissen, N.C.M.; Dulmen, A.M. van

    2007-01-01

    OBJECTIVE: To examine whether the discussion of illness representations and action plans during medical encounters affects the way patients and general practitioners (GPs) communicate. METHODS: In a quasi-experimental design, 10 GPs first performed care-as-usual conversations with patients. After a

  12. 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.

  13. Latent subspace sparse representation-based unsupervised domain adaptation

    Science.gov (United States)

    Shuai, Liu; Sun, Hao; Zhao, Fumin; Zhou, Shilin

    2015-12-01

    In this paper, we introduce and study a novel unsupervised domain adaptation (DA) algorithm, called latent subspace sparse representation based domain adaptation, based on the fact that source and target data that lie in different but related low-dimension subspaces. The key idea is that each point in a union of subspaces can be constructed by a combination of other points in the dataset. In this method, we propose to project the source and target data onto a common latent generalized subspace which is a union of subspaces of source and target domains and learn the sparse representation in the latent generalized subspace. By employing the minimum reconstruction error and maximum mean discrepancy (MMD) constraints, the structure of source and target domain are preserved and the discrepancy is reduced between the source and target domains and thus reflected in the sparse representation. We then utilize the sparse representation to build a weighted graph which reflect the relationship of points from the different domains (source-source, source- target, and target-target) to predict the labels of the target domain. We also proposed an efficient optimization method for the algorithm. Our method does not need to combine with any classifiers and therefore does not need train the test procedures. Various experiments show that the proposed method perform better than the competitive state of art subspace-based domain adaptation.

  14. 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.

  15. Action-based effects on music perception.

    Science.gov (United States)

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

    2014-01-01

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

  16. Action-based effects on music perception.

    Science.gov (United States)

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

    2014-01-01

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

  17. 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

  18. 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.

  19. 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.

  20. Mental Representation and Motor Imagery Training

    OpenAIRE

    Thomas eSchack; Kai eEssig; Cornelia eFrank; Dirk eKoester

    2014-01-01

    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. Th...

  1. Mental representation and motor imagery training

    OpenAIRE

    Schack, Thomas; Essig, Kai; Frank, Cornelia; Koester, Dirk

    2014-01-01

    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, the structural dimensional analysis of mental representation (SDA-M), to assess action-relevant representational structures that reflect the organization of BACs...

  2. Action-based flood forecasting for triggering humanitarian action

    OpenAIRE

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

    2016-01-01

    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 changi...

  3. 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

  4. 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.

  5. Room Categorization Based on a Hierarchical Representation of Space

    OpenAIRE

    Peter Uršič; Domen Tabernik; Marko Boben; Danijel Skočaj; Aleš Leonardis; Matej Kristan

    2013-01-01

    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‐d...

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

    OpenAIRE

    Goded Shahaf; Danny Eytan; Asaf Gal; Einat Kermany; Vladimir Lyakhov; Christoph Zrenner; Shimon Marom

    2008-01-01

    Author Summary The idea that sensory objects are represented by the order in which neurons are recruited in response to stimulus presentation was put forward over a decade ago, largely based on computational biology considerations. While intensively analyzed in simulation studies, the general biological applicability of this highly compacted and efficient representation scheme, as an ensemble neural code, was never established. In recent years, algorithmic and experimental technologies advanc...

  7. Piecewise Trend Approximation: A Ratio-Based Time Series Representation

    Directory of Open Access Journals (Sweden)

    Jingpei Dan

    2013-01-01

    Full Text Available A time series representation, piecewise trend approximation (PTA, is proposed to improve efficiency of time series data mining in high dimensional large databases. PTA represents time series in concise form while retaining main trends in original time series; the dimensionality of original data is therefore reduced, and the key features are maintained. Different from the representations that based on original data space, PTA transforms original data space into the feature space of ratio between any two consecutive data points in original time series, of which sign and magnitude indicate changing direction and degree of local trend, respectively. Based on the ratio-based feature space, segmentation is performed such that each two conjoint segments have different trends, and then the piecewise segments are approximated by the ratios between the first and last points within the segments. To validate the proposed PTA, it is compared with classical time series representations PAA and APCA on two classical datasets by applying the commonly used K-NN classification algorithm. For ControlChart dataset, PTA outperforms them by 3.55% and 2.33% higher classification accuracy and 8.94% and 7.07% higher for Mixed-BagShapes dataset, respectively. It is indicated that the proposed PTA is effective for high dimensional time series data mining.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Argumentation-Based Collaborative Inquiry in Science through Representational Work: Impact on Primary Students' Representational Fluency

    Science.gov (United States)

    Nichols, Kim; Gillies, Robyn; Hedberg, John

    2016-01-01

    This study explored the impact of argumentation-promoting collaborative inquiry and representational work in science on primary students' representational fluency. Two hundred sixty-six year 6 students received instruction on natural disasters with a focus on collaborative inquiry. Students in the Comparison condition received only this…

  13. 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.

  14. 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.

  15. 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.

  16. Voxel selection in FMRI data analysis based on sparse representation.

    Science.gov (United States)

    Li, Yuanqing; Namburi, Praneeth; Yu, Zhuliang; Guan, Cuntai; Feng, Jianfeng; Gu, Zhenghui

    2009-10-01

    Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI) data with task relevant information. In each iteration of the algorithm, a linear programming problem is solved and a sparse weight vector is subsequently obtained. The final weight vector is the mean of those obtained in all iterations. The characteristics of our algorithm are as follows: 1) the weight vector (output) is sparse; 2) the magnitude of each entry of the weight vector represents the significance of its corresponding variable or feature in a classification or regression problem; and 3) due to the convergence of this algorithm, a stable weight vector is obtained. To demonstrate the validity of our algorithm and illustrate its application, we apply the algorithm to the Pittsburgh Brain Activity Interpretation Competition 2007 functional fMRI dataset for selecting the voxels, which are the most relevant to the tasks of the subjects. Based on this dataset, the aforementioned characteristics of our algorithm are analyzed, and a comparison between our method with the univariate general-linear-model-based statistical parametric mapping is performed. Using our method, a combination of voxels are selected based on the principle of effective/sparse representation of a task. Data analysis results in this paper show that this combination of voxels is suitable for decoding tasks and demonstrate the effectiveness of our method. PMID:19567340

  17. Maturation and experience in action representation: Bilateral deficits in unilateral congenital amelia.

    Science.gov (United States)

    Philip, B A; Buckon, C; Sienko, S; Aiona, M; Ross, S; Frey, S H

    2015-08-01

    Congenital unilateral absence of the hand (amelia) completely deprives individuals of sensorimotor experiences with their absent effector. The consequences of such deprivation on motor planning abilities are poorly understood. Fourteen patients and matched controls performed two grip selection tasks: 1) overt grip selection (OGS), in which they used their intact hand to grasp a three-dimensional object that appeared in different orientations using the most natural (under-or over-hand) precision grip, and 2) prospective grip selection (PGS), in which they selected the most natural grip for either the intact or absent hand without moving. For the intact hand, we evaluated planning accuracy by comparing concordance between grip preferences expressed in PGS vs. OGS. For the absent hand, we compared PGS responses with OGS responses for the intact hand that had been phase shifted by 180°, thereby accounting for mirror symmetrical biomechanical constraints of the two limbs. Like controls, amelic individuals displayed a consistent preference for less awkward grips in both OGS and PGS. Unexpectedly, however, they were slower and less accurate for PGS based on either the intact or the absent hand. We conclude that direct sensorimotor experience with both hands may be important for the typical development or refinement of effector-specific internal representations of either limb. PMID:26092768

  18. Using Morphlet-Based Image Representation for Object Detection

    Science.gov (United States)

    Gorbatsevich, V. S.; Vizilter, Yu. V.

    2016-06-01

    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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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).

  4. Supporting students' learning with multiple representations in a dynamic simulation-based learning environment

    NARCIS (Netherlands)

    Meij, van der Jan; Jong, de Ton

    2006-01-01

    In this study, the effects of different types of support for learning from multiple representations in a simulation-based learning environment were examined. The study extends known research by examining the use of dynamic representations instead of static representations and it examines the role of

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

    Science.gov (United States)

    Yung, Hsin I.; Paas, Fred

    2015-01-01

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

  6. Supporting Students' Learning with Multiple Representations in a Dynamic Simulation-Based Learning Environment

    Science.gov (United States)

    van der Meij, Jan; de Jong, Ton

    2006-01-01

    In this study, the effects of different types of support for learning from multiple representations in a simulation-based learning environment were examined. The study extends known research by examining the use of dynamic representations instead of static representations and it examines the role of the complexity of the domain and the learning…

  7. Normal ECG Recognition for Express-Diagnostics Based on Scale-Space Representation and Dynamic Matching

    OpenAIRE

    Bilous, Nataliya; Bondarenko, Michael; Kobzar, Gleb; Krasov, Alexey; Rogozyanov, Artyom

    2008-01-01

    A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

  8. Pose Sentences: A new representation for action recognition using sequence of pose words

    NARCIS (Netherlands)

    Hatun, Kardelen; Duygulu, Pinar

    2008-01-01

    We propose a method for recognizing human actions in videos. Inspired from the recent bag-of-words approaches, we represent actions as documents consisting of words, where a word refers to the pose in a frame. Histogram of oriented gradients (HOG) features are used to describe poses, which are then

  9. 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

  10. 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

  11. Image Hierarchical Representations Models based on Latent Dirichlet Allocation

    Directory of Open Access Journals (Sweden)

    Fushun WANG

    2013-08-01

    Full Text Available Existing image layer representations methods are very feed-forward, and then not able to deal with small ambiguities. A probabilistic model is proposed, and it learns and deduces each layer in that hierarchy together. Therefore, we consider a recursive probabilistic decomposition process, and derive a new yielded method based on recursive Latent Dirichlet Allocation. We show 2 significant properties of the novel probabilistic method: 1 pulsing another hierarchical to represent the enhanced results on that smooth method; 2 an entire Bayesian method beats a feed-forward running of the novel method. The method can be evaluated on a criterion recognition dataset. It takes the probability of recursive decomposition process into account, and obtains multilayer structure pyramid LDA derived model through the derivation. Experiments demonstrate that the novel technique beats existing hierarchical approaches, and present better performance

  12. 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.

  13. A Patch-based Sparse Representation for Sketch Recognition

    DEFF Research Database (Denmark)

    Qi, Yonggong; Zhang, Honggang; Song, Yi-Zhe;

    2014-01-01

    Categorizing free-hand human sketches has profound implications in applications such as human computer interaction and image retrieval. The task is non-trivial due to the iconic nature of sketches, signified by large variances in both appearance and structure when compared with photographs. One of...... Symmetric-aware Flip Invariant Sketch Histogram (SYM-FISH). We present a novel patch-based sparse representation (PSR) for describing sketch image and it is evaluated under a sketch recognition framework. Extensive experiments on a large scale human drawn sketch dataset demonstrate the effectiveness of the...... the most fundamental problem is how to effectively describe a sketch image. Many existing descriptors, such as Histogram of Oriented Gradients (HOG) and Shape Context (SC), have achieved great success. Moreover, some works have attempted to design features specifically engineered for sketches, such as...

  14. 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.

  15. 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.

  16. 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. PMID:23259955

  17. Human responses to climate change: social representation, identity and socio-psychological action

    OpenAIRE

    Jaspal, Rusi; Nerlich, Brigitte; Cinirella, Marco

    2014-01-01

    Climate change is one of the most important global challenges in the twenty-first century, given that a changing climate is likely to have negative and potentially irreversible consequences for the environment and human beings. Drawing upon Social Representations Theory (SRT) and Identity Process Theory (IPT) from social psychology, we argue that research should focus upon, and successfully integrate, three levels of analysis, namely (1) how climate change knowledge is constructed and circula...

  18. Representation of others' action by neurons in monkey medial frontal cortex.

    Science.gov (United States)

    Yoshida, Kyoko; Saito, Nobuhito; Iriki, Atsushi; Isoda, Masaki

    2011-02-01

    Successful social interaction depends on not only the ability to identify with others but also the ability to distinguish between aspects of self and others. Although there is considerable knowledge of a shared neural substrate between self-action and others' action, it remains unknown where and how in the brain the action of others is uniquely represented. Exploring such agent-specific neural codes is important because one's action and intention can differ between individuals. Moreover, the assignment of social agency breaks down in a range of mental disorders. Here, using two monkeys monitoring each other's action for adaptive behavioral planning, we show that the medial frontal cortex (MFC) contains a group of neurons that selectively encode others' action. These neurons, observed in both dominant and submissive monkeys, were significantly more prevalent in the dorsomedial convexity region of the MFC including the pre-supplementary motor area than in the cingulate sulcus region of the MFC including the rostral cingulate motor area. Further tests revealed that the difference in neuronal activity was not due to gaze direction or muscular activity. We suggest that the MFC is involved in self-other differentiation in the domain of motor action and provides a fundamental neural signal for social learning. PMID:21256015

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

    Science.gov (United States)

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

    2016-07-01

    Action observation leads to a representation of both the motor aspect of an observed action (motor simulation) and its somatosensory consequences (action-based somatosensory simulation) in the observer's brain. In the current electroencephalography-study, we investigated the neuronal interplay of action-based somatosensory simulation and felt touch. We presented index or middle finger tapping movements of a human or a wooden hand, while simultaneously presenting 'tap-like' tactile sensations to either the corresponding or non-corresponding fingertip of the participant. We focused on an early stage of somatosensory processing [P50, N100 and N140 sensory evoked potentials (SEPs)] and on a later stage of higher-order processing (P3-complex). The results revealed an interaction effect of animacy and congruency in the early P50 SEP and an animacy effect in the N100/N140 SEPs. In the P3-complex, we found an interaction effect indicating that the influence of congruency was larger in the human than in the wooden hand. We argue that the P3-complex may reflect higher-order self-other distinction by signaling simulated action-based touch that does not match own tactile information. As such, the action-based somatosensory congruency paradigm might help understand higher-order social processes from a somatosensory point of view. PMID:26152577

  20. Object-Based Benefits without Object-Based Representations

    OpenAIRE

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

    2012-01-01

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

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

    OpenAIRE

    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 pha...

  2. A New Penta-valued Logic Based Knowledge Representation

    OpenAIRE

    Patrascu, Vasile

    2015-01-01

    In this paper a knowledge representation model are proposed, FP5, which combine the ideas from fuzzy sets and penta-valued logic. FP5 represents imprecise properties whose accomplished degree is undefined, contradictory or indeterminate for some objects. Basic operations of conjunction, disjunction and negation are introduced. Relations to other representation models like fuzzy sets, intuitionistic, paraconsistent and bipolar fuzzy sets are discussed.

  3. Learning Spatio-Temporal Representations for Action Recognition: A Genetic Programming Approach.

    Science.gov (United States)

    Liu, Li; Shao, Ling; Li, Xuelong; Lu, Ke

    2016-01-01

    Extracting discriminative and robust features from video sequences is the first and most critical step in human action recognition. In this paper, instead of using handcrafted features, we automatically learn spatio-temporal motion features for action recognition. This is achieved via an evolutionary method, i.e., genetic programming (GP), which evolves the motion feature descriptor on a population of primitive 3D operators (e.g., 3D-Gabor and wavelet). In this way, the scale and shift invariant features can be effectively extracted from both color and optical flow sequences. We intend to learn data adaptive descriptors for different datasets with multiple layers, which makes fully use of the knowledge to mimic the physical structure of the human visual cortex for action recognition and simultaneously reduce the GP searching space to effectively accelerate the convergence of optimal solutions. In our evolutionary architecture, the average cross-validation classification error, which is calculated by an support-vector-machine classifier on the training set, is adopted as the evaluation criterion for the GP fitness function. After the entire evolution procedure finishes, the best-so-far solution selected by GP is regarded as the (near-)optimal action descriptor obtained. The GP-evolving feature extraction method is evaluated on four popular action datasets, namely KTH, HMDB51, UCF YouTube, and Hollywood2. Experimental results show that our method significantly outperforms other types of features, either hand-designed or machine-learned. PMID:25700480

  4. 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.

  5. 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.

  6. Combinatorial bases for covariant representations of the Lie superalgebra gl(m|n)

    OpenAIRE

    Molev, A. I.

    2010-01-01

    Covariant tensor representations of gl(m|n) occur as irreducible components of tensor powers of the natural (m+n)-dimensional representation. We construct a basis of each covariant representation and give explicit formulas for the action of the generators of gl(m|n) in this basis. The basis has the property that the natural Lie subalgebras gl(m) and gl(n) act by the classical Gelfand-Tsetlin formulas. The main role in the construction is played by the fact that the subspace of gl(m)-highest v...

  7. 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.

  8. 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.

  9. Compositional connectionist structures based on in situ grounded representations

    NARCIS (Netherlands)

    Velde, van der Frank; Kamps, de Marc

    2011-01-01

    The combination of productivity, dynamics and grounding imposes constraints that require specific architectures for their combined implementation. Grounding of representations can be achieved with specific neuronal assembly structures, which can be distributed over different brain areas. This entail

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

    DEFF Research Database (Denmark)

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

    2009-01-01

    HERXML has been proven to be an appropriate solution in supporting the Web representation of health information. It can be used by health practitioners, policy makers, and the public in disease etiology, health planning, health resource management, health promotion and health education. The utilization....... 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...

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. Progression in Multiple Representations: Supporting students' learning with multiple representations in a dynamic simulation-based learning environment

    OpenAIRE

    Van Der Meij, Jan; De Jong, Ton

    2006-01-01

    Relating multiple representations and translating between them is important to acquire deeper knowledge about a domain. To relate representations, learners have to mentally search for similarities and differences. To translate between representations, learners need to interpret the effects that changes in one representation have on corresponding representations. The question is how presenting representations may improve or hinder the processes of relation and translation. In this study we exa...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Automatic ECG Analysis for Preliminary and Detailed Diagnostics Based on Scale-space Representation

    OpenAIRE

    Belous, Natalie; Kobzar, Gleb

    2008-01-01

    A novel approach of automatic ECG analysis based on scale-scale signal representation is proposed. The approach uses curvature scale-space representation to locate main ECG waveform limits and peaks and may be used to correct results of other ECG analysis techniques or independently. Moreover dynamic matching of ECG CSS representations provides robust preliminary recognition of ECG abnormalities which has been proven by experimental results.

  3. 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.

  4. A Knowledge-Based Representation Scheme for Environmental Science Models

    Science.gov (United States)

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

    1994-01-01

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

  5. Sparse image representation by discrete cosine/spline based dictionaries

    CERN Document Server

    Bowley, James

    2009-01-01

    Mixed dictionaries generated by cosine and B-spline functions are considered. It is shown that, by highly nonlinear approaches such as Orthogonal Matching Pursuit, the discrete version of the proposed dictionaries yields a significant gain in the sparsity of an image representation.

  6. Representation of 1/f signal with wavelet bases

    Institute of Scientific and Technical Information of China (English)

    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.

  7. 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 ...... diverse NLP tasks, showing state-of-the-art results....

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

    DEFF Research Database (Denmark)

    Chen, Xiaoshuang; Lin, Jin; Wan, Can;

    2016-01-01

    . Under this background, this paper proposes a circuit representation model to represent SE errors. Based on the matrix formulation of the circuit representation model, the problem of optimal meter placement can be transformed to a mixed integer linear programming problem (MILP) via the disjunctive model...

  9. 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.

  10. 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. PMID:27138360

  11. 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.

  12. SAR target classification based on multiscale sparse representation

    Science.gov (United States)

    Ruan, Huaiyu; Zhang, Rong; Li, Jingge; Zhan, Yibing

    2016-03-01

    We propose a novel multiscale sparse representation approach for SAR target classification. It firstly extracts the dense SIFT descriptors on multiple scales, then trains a global multiscale dictionary by sparse coding algorithm. After obtaining the sparse representation, the method applies spatial pyramid matching (SPM) and max pooling to summarize the features for each image. The proposed method can provide more information and descriptive ability than single-scale ones. Moreover, it costs less extra computation than existing multiscale methods which compute a dictionary for each scale. The MSTAR database and ship database collected from TerraSAR-X images are used in classification setup. Results show that the best overall classification rate of the proposed approach can achieve 98.83% on the MSTAR database and 92.67% on the TerraSAR-X ship database.

  13. Action-based effects on music perception

    OpenAIRE

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

    2014-01-01

    The classical, disembodied approach to music cognition conceptualizes action and perception as separate, peripheral processes. In contrast, embodied accounts of music cognition emphasize the central role of the close coupling of action and perception. It is a commonly established fact that perception spurs action tendencies. We present a theoretical framework that captures the ways in which the human motor system and its actions can reciprocally influence the perception of music. The cornerst...

  14. Action-based effects on music perception

    OpenAIRE

    Pieter-Jan eMaes; Marc eLeman; Caroline ePalmer; Marcelo eWanderley

    2014-01-01

    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 co...

  15. Knowledge Representation on the Web revisited: Tools for Prototype Based Ontologies

    OpenAIRE

    Cochez, Michael; Decker, Stefan; Prud'hommeaux, Eric

    2016-01-01

    In recent years RDF and OWL have become the most common knowledge representation languages in use on the Web, propelled by the recommendation of the W3C. In this paper we present a practical implementation of a different kind of knowledge representation based on Prototypes. In detail, we present a concrete syntax easily and effectively parsable by applications. We also present extensible implementations of a prototype knowledge base, specifically designed for storage of Prototypes. These impl...

  16. 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...

  17. 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.

  18. 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.

  19. Street-based Topological Representations and Analyses for Predicting Traffic Flow in GIS

    CERN Document Server

    Jiang, Bin

    2007-01-01

    It is well received in the space syntax community that traffic flow is significantly correlated to a morphological property of streets, which are represented by axial lines, forming a so called axial map. The correlation co-efficient (R square value) approaches 0.8 and even a higher value according to the space syntax literature. In this paper, we study the same issue using the Hong Kong street network and the Hong Kong Annual Average Daily Traffic (AADT) datasets, and find surprisingly that street-based topological representations (or street-street topologies) tend to be better representations than the axial map. In other words, vehicle flow is correlated to a morphological property of streets better than that of axial lines. Based on the finding, we suggest the street-based topological representations as an alternative GIS representation, and the topological analyses as a new analytical means for geographic knowledge discovery.

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

    Science.gov (United States)

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

    2016-02-01

    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 ability to balance self-other distinction and integration, resulting in personal distress in reaction to other people's emotions or even a loss of self [e.g., in (subclinical) psychosis]. Previous research has demonstrated that the integration and distinction of others' actions cause interference with one's own action performance (commonly assessed with a social Simon task). The present study had two goals. First, as previous studies on the social Simon effect employed relatively small samples (N test), we aimed for a sample size that allowed us to test the robustness of the action interference effect. Second, we tested to what extent action interference reflects individual differences in traits related to self-other distinction (i.e., personal distress in reaction to other people's emotions and subclinical psychotic symptoms). Based on a questionnaire study among a large sample (N = 745), we selected a subsample (N = 130) of participants scoring low, average, or high on subclinical psychotic symptoms, or on personal distress. The selected participants performed a social Simon task. Results showed a robust social Simon effect, regardless of individual differences in personal distress or subclinical psychotic symptoms. However, exploratory analyses revealed that the sex composition of interaction pairs modulated social Simon effects. Possible explanations for these findings are discussed. PMID:26525711

  1. 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 ...

  2. 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.

  3. 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.

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

    OpenAIRE

    Qi Jia; Xinkai Gao; He Guo; Zhongxuan Luo; Yi Wang(Kavli Institute for the Physics and Mathematics of the Universe, Todai Institutes for Advanced Study, University of Tokyo (WPI), 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8583, Japan)

    2015-01-01

    In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set...

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

    DEFF Research Database (Denmark)

    Endelt, Line Ørtoft

    We introduce a new method for generating time-frequency distributions, which is particularly useful for the analysis of music signals. The method presented here is based on $\\ell1$ sparse representations of music signals in a redundant wavelet packet dictionary. The representations are found usin......, by masking the energy from less structured music instruments. We present four examples for visualizing structured content, including vocal and single instrument....

  6. 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.

  7. Representing Performance | Performing Representation : Ontology in accounting practice

    OpenAIRE

    Sundström, Andreas

    2015-01-01

    Social studies of accounting have drawn attention to the dubious role of accounting as a representational link between organizational realities and action. Based on five years immersion with performance management and board work in a theatre company, this thesis inquires into the ontological significance of accounting practices. The study takes a praxiographic approach, which emphasizes action and relocates questions of representation towards the practices in which representations are mobiliz...

  8. 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.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Qi Jia

    2015-03-01

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

  11. Multi-layer sparse representation for weighted LBP-patches based facial expression recognition.

    Science.gov (United States)

    Jia, Qi; Gao, Xinkai; Guo, He; Luo, Zhongxuan; Wang, Yi

    2015-01-01

    In this paper, a novel facial expression recognition method based on sparse representation is proposed. Most contemporary facial expression recognition systems suffer from limited ability to handle image nuisances such as low resolution and noise. Especially for low intensity expression, most of the existing training methods have quite low recognition rates. Motivated by sparse representation, the problem can be solved by finding sparse coefficients of the test image by the whole training set. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. We evaluate facial representation based on weighted local binary patterns, and Fisher separation criterion is used to calculate the weighs of patches. A multi-layer sparse representation framework is proposed for multi-intensity facial expression recognition, especially for low-intensity expressions and noisy expressions in reality, which is a critical problem but seldom addressed in the existing works. To this end, several experiments based on low-resolution and multi-intensity expressions are carried out. Promising results on publicly available databases demonstrate the potential of the proposed approach. PMID:25808772

  12. 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.

  13. Robust Face Recognition via Minimum Error Entropy-Based Atomic Representation.

    Science.gov (United States)

    Wang, Yulong; Tang, Yuan Yan; Li, Luoqing

    2015-12-01

    Representation-based classifiers (RCs) have attracted considerable attention in face recognition in recent years. However, most existing RCs use the mean square error (MSE) criterion as the cost function, which relies on the Gaussianity assumption of the error distribution and is sensitive to non-Gaussian noise. This may severely degrade the performance of MSE-based RCs in recognizing facial images with random occlusion and corruption. In this paper, we present a minimum error entropy-based atomic representation (MEEAR) framework for face recognition. Unlike existing MSE-based RCs, our framework is based on the minimum error entropy criterion, which is not dependent on the error distribution and shown to be more robust to noise. In particular, MEEAR can produce discriminative representation vector by minimizing the atomic norm regularized Renyi's entropy of the reconstruction error. The optimality conditions are provided for general atomic representation model. As a general framework, MEEAR can also be used as a platform to develop new classifiers. Two effective MEE-based RCs are proposed by defining appropriate atomic sets. The experimental results on popular face databases show that MEEAR can improve both the recognition accuracy and the reconstructed results compared with the state-of-the-art MSE-based RCs. PMID:26513784

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Tao Chen

    2015-08-01

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

  16. 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

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

    DEFF Research Database (Denmark)

    Galle, Per

    2000-01-01

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

  18. TARGET-ORIENTED GENERIC FINGERPRINT-BASED MOLECULAR REPRESENTATION

    OpenAIRE

    Petr Skoda; David Hoksza

    2014-01-01

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

  19. Sparse coding based dense feature representation model for hyperspectral image classification

    Science.gov (United States)

    Oguslu, Ender; Zhou, Guoqing; Zheng, Zezhong; Iftekharuddin, Khan; Li, Jiang

    2015-11-01

    We present a sparse coding based dense feature representation model (a preliminary version of the paper was presented at the SPIE Remote Sensing Conference, Dresden, Germany, 2013) for hyperspectral image (HSI) classification. The proposed method learns a new representation for each pixel in HSI through the following four steps: sub-band construction, dictionary learning, encoding, and feature selection. The new representation usually has a very high dimensionality requiring a large amount of computational resources. We applied the l1/lq regularized multiclass logistic regression technique to reduce the size of the new representation. We integrated the method with a linear support vector machine (SVM) and a composite kernels SVM (CKSVM) 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, and image fusion and recursive filtering. Experimental results show 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.

  20. 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.

  1. TOWARDS AN ONTOLOGY-BASED MODEL FOR USER PROFILE REPRESENTATION IN A CLOUD INFRASTRUCTURE

    Directory of Open Access Journals (Sweden)

    Vassilis Koutkias

    2013-12-01

    Full Text Available This paper presents an approach for the semantic representation of user profiles through an ontology conducted in the scope of the Cloud4all project. Employing the cloud computing paradigm, Cloud4allaims torealize a global public inclusive infrastructure that will reinforce accessibility of information and communication technologies(ICT. The proposed ontology aims to provide the required representation formalism to sufficiently express personal user needs and preferences based on domain knowledge and the association of interaction-related concepts in order to support automatic reasoning mechanisms for user profile management.

  2. LETTER TO THE EDITOR: New bases of representation for the unitary parasupersymmetry algebra

    Science.gov (United States)

    Fakhri, H.

    2003-01-01

    Representation bases of unitary parasupersymmetry algebra of arbitrary order p is constructed by some one-dimensional models which are shape invariant with respect to the main quantum number n. Consequently, the isospectral Hamiltonians and their exact solutions are obtained as labelled by the main quantum number n.

  3. Training data representation in a neural based robot position estimation system

    International Nuclear Information System (INIS)

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

  4. 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

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

    Science.gov (United States)

    de Vries, Erica

    2006-01-01

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

  6. Facial action detection using block-based pyramid appearance descriptors

    OpenAIRE

    Jiang, Bihan; Valstar, Michel F.; Pantic, Maja

    2012-01-01

    Facial expression is one of the most important non-verbal behavioural cues in social signals. Constructing an effective face representation from images is an essential step for successful facial behaviour analysis. Most existing face descriptors operate on the same scale, and do not leverage coarse v.s. fine methods such as image pyramids. In this work, we propose the sparse appearance descriptors Block-based Pyramid Local Binary Pattern (B-PLBP) and Block-based Pyramid Local Phase Quantisati...

  7. 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.

  8. Deep Learning of Part-based Representation of Data Using Sparse Autoencoders with Nonnegativity Constraints

    OpenAIRE

    Hosseini-Asl, Ehsan; Zurada, Jacek M.; Nasraoui, Olfa

    2016-01-01

    We demonstrate a new deep learning autoencoder network, trained by a nonnegativity constraint algorithm (NCAE), that learns features which show part-based representation of data. The learning algorithm is based on constraining negative weights. The performance of the algorithm is assessed based on decomposing data into parts and its prediction performance is tested on three standard image data sets and one text dataset. The results indicate that the nonnegativity constraint forces the autoenc...

  9. 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.

  10. Perceptual-Cognitive Changes During Motor Learning: The Influence of Mental and Physical Practice on Mental Representation, Gaze Behavior, and Performance of a Complex Action.

    Science.gov (United States)

    Frank, Cornelia; Land, William M; Schack, Thomas

    2015-01-01

    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, combined physical plus mental practice, and no practice. Participants in the practice groups trained on a golf putting task over the course of 3 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. PMID:26779089

  11. 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.

  12. Acoustic emission source localization based on distance domain signal representation

    Science.gov (United States)

    Gawronski, M.; Grabowski, K.; Russek, P.; Staszewski, W. J.; Uhl, T.; Packo, P.

    2016-04-01

    Acoustic emission is a vital non-destructive testing technique and is widely used in industry for damage detection, localisation and characterization. The latter two aspects are particularly challenging, as AE data are typically noisy. What is more, elastic waves generated by an AE event, propagate through a structural path and are significantly distorted. This effect is particularly prominent for thin elastic plates. In these media the dispersion phenomenon results in severe localisation and characterization issues. Traditional Time Difference of Arrival methods for localisation techniques typically fail when signals are highly dispersive. Hence, algorithms capable of dispersion compensation are sought. This paper presents a method based on the Time - Distance Domain Transform for an accurate AE event localisation. The source localisation is found through a minimization problem. The proposed technique focuses on transforming the time signal to the distance domain response, which would be recorded at the source. Only, basic elastic material properties and plate thickness are used in the approach, avoiding arbitrary parameters tuning.

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

    Directory of Open Access Journals (Sweden)

    Jianzhong Wang

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

  14. 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...

  15. GRAPES-Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain.

    Science.gov (United States)

    Martin, Alex

    2016-08-01

    In this article, I discuss some of the latest functional neuroimaging findings on the organization of object concepts in the human brain. I argue that these data provide strong support for viewing concepts as the products of highly interactive neural circuits grounded in the action, perception, and emotion systems. The nodes of these circuits are defined by regions representing specific object properties (e.g., form, color, and motion) and thus are property-specific, rather than strictly modality-specific. How these circuits are modified by external and internal environmental demands, the distinction between representational content and format, and the grounding of abstract social concepts are also discussed. PMID:25968087

  16. 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

  17. 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.

  18. Mental representation and motor imagery training.

    Science.gov (United States)

    Schack, Thomas; Essig, Kai; Frank, Cornelia; Koester, Dirk

    2014-01-01

    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, the structural dimensional analysis of mental representation (SDA-M), 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 (MTMR) 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. PMID:24904368

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. A quick search method for audio signals based on a piecewise linear representation of feature trajectories

    CERN Document Server

    Kimura, Akisato; Kurozumi, Takayuki; Murase, Hiroshi

    2007-01-01

    This paper presents a new method for a quick similarity-based search through long unlabeled audio streams to detect and locate audio clips provided by users. The method involves feature-dimension reduction based on a piecewise linear representation of a sequential feature trajectory extracted from a long audio stream. Two techniques enable us to obtain a piecewise linear representation: the dynamic segmentation of feature trajectories and the segment-based Karhunen-L\\'{o}eve (KL) transform. The proposed search method guarantees the same search results as the search method without the proposed feature-dimension reduction method in principle. Experiment results indicate significant improvements in search speed. For example the proposed method reduced the total search time to approximately 1/12 that of previous methods and detected queries in approximately 0.3 seconds from a 200-hour audio database.

  4. AIN-Based Action Selection Mechanism for Soccer Robot Systems

    Directory of Open Access Journals (Sweden)

    Yin-Tien Wang

    2009-01-01

    Full Text Available Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure developed based on geometry approach will become a very complex task. In this paper, a novel action-select algorithm for soccer robots is proposed by using the concepts of artificial immune network (AIN. This AIN-based action-select provides an efficient and robust algorithm for robot role selection. Meanwhile, a reinforcement learning mechanism is applied in the proposed algorithm to enhance the response of the adaptive immune system. Simulation and experiment are carried out to verify the proposed AIN-based algorithm, and the results show that the proposed algorithm provides an efficient and applicable algorithm for mobile robots to play soccer game.

  5. Simulation modifies prehension: evidence for a conjoined representation of the graspable features of an object and the action of grasping it.

    Directory of Open Access Journals (Sweden)

    Victor Frak

    Full Text Available Movement formulas, engrams, kinesthetic images and internal models of the body in action are notions derived mostly from clinical observations of brain-damaged subjects. They also suggest that the prehensile geometry of an object is integrated in the neural circuits and includes the object's graspable characteristics as well as its semantic properties. In order to determine whether there is a conjoined representation of the graspable characteristics of an object in relation to the actual grasping, it is necessary to separate the graspable (low-level from the semantic (high-level properties of the object. Right-handed subjects were asked to grasp and lift a smooth 300-g cylinder with one hand, before and after judging the level of difficulty of a "grasping for pouring" action, involving a smaller cylinder and using the opposite hand. The results showed that simulated grasps with the right hand exert a direct influence on actual motor acts with the left hand. These observations add to the evidence that there is a conjoined representation of the graspable characteristics of the object and the biomechanical constraints of the arm.

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

    Science.gov (United States)

    Alessandretti, Laura; Karsai, Márton; Gauvin, Laetitia

    2016-07-01

    Multimodal transportation systems, with several coexisting services like bus, tram and metro, can be represented as time-resolved multilayer networks where the different transportation modes connecting the same set of nodes are associated with distinct network layers. Their quantitative description became possible recently due to openly accessible datasets describing the geo-localized transportation dynamics of large urban areas. Advancements call for novel analytics, which combines earlier established methods and exploits the inherent complexity of the data. Here, we provide a novel user-based representation of public transportation systems, which combines representations, accounting for the presence of multiple lines and reducing the effect of spatial embeddedness, while considering the total travel time, its variability across the schedule, and taking into account the number of transfers necessary. After the adjustment of earlier techniques to the novel representation framework, we analyse the public transportation systems of several French municipal areas and identify hidden patterns of privileged connections. Furthermore, we study their efficiency as compared to the commuting flow. The proposed representation could help to enhance resilience of local transportation systems to provide better design policies for future developments. PMID:27493773

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

    OpenAIRE

    Cormier, K.; Smith, S.; Sevcikova, Z.

    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 t...

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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

    2016-01-01

    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

  14. Electromyography-Based Quantitative Representation Method for Upper-Limb Elbow Joint Angle in Sagittal Plane

    OpenAIRE

    Pang, Muye; Guo, Shuxiang; Huang, Qiang; Ishihara, Hidenori; Hirata, Hideyuki

    2015-01-01

    This paper presents a quantitative representation method for the upper-limb elbow joint angle using only electromyography (EMG) signals for continuous elbow joint voluntary flexion and extension in the sagittal plane. The dynamics relation between the musculotendon force exerted by the biceps brachii muscle and the elbow joint angle is developed for a modified musculoskeletal model. Based on the dynamics model, a quadratic-like quantitative relationship between EMG signals and the elbow joint...

  15. Shared Representation of SAR Target and Shadow Based on Multilayer Auto-encoder

    OpenAIRE

    Sun Zhi-jun; Xue Lei; Xu Yang-ming; Sun Zhi-yong

    2013-01-01

    Automatic Target Recognition (ATR) of Synthetic Aperture Radar (SAR) image is investigated. A SAR feature extraction algorithm based on multilayer auto-encoder is proposed. The method makes use of a probabilistic neural network, Restricted Boltzmann Machine (RBM) modeling probability distribution of environment. Through the formation of more expressive multilayer neural network, the deep learning model learns shared representation of the target and its shadow outline reflecting the target sha...

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

    OpenAIRE

    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 experimental conditions were provided with a simulation-based learning environment. The experimental manipulation concerned the format of the simulations. These were diagrammatical, arithmetical, text...

  17. Improving Sparse Representation-Based Classification Using Local Principal Component Analysis

    OpenAIRE

    Weaver, Chelsea; Saito, Naoki

    2016-01-01

    Sparse representation-based classification (SRC), proposed by Wright et al., seeks the sparsest decomposition of a test sample over the dictionary of training samples, with classification to the most-contributing class. Because it assumes test samples can be written as linear combinations of their same-class training samples, the success of SRC depends on the size and representativeness of the training set. Our proposed classification algorithm enlarges the training set by using local princip...

  18. Model based matching using simulated annealing and a minimum representation size criterion

    Science.gov (United States)

    Ravichandran, B.; Sanderson, A. C.

    1992-01-01

    We define the model based matching problem in terms of the correspondence and transformation that relate the model and scene, and the search and evaluation measures needed to find the best correspondence and transformation. Simulated annealing is proposed as a method for search and optimization, and the minimum representation size criterion is used as the evaluation measure in an algorithm that finds the best correspondence. An algorithm based on simulated annealing is presented and evaluated. This algorithm is viewed as a part of an adaptive, hierarchical approach which provides robust results for a variety of model based matching problems.

  19. Representações sociais e culturas de ação The social and cultural representations of action

    Directory of Open Access Journals (Sweden)

    Jean-Marie Barvier

    2010-08-01

    Full Text Available Sustentado por constatações realizadas no mundo profissional e, em particular, no mundo da educação e da formação, o autor propõe o conceito de cultura da ação como um modo compartilhado de organização de construção de sentido sobre as atividades. Este conceito transversal às diferentes formas de ação busca unir os aspectos individuais e coletivos, as permanências e as mudanças, os aspectos mentais e os aspectos conativos na abordagem do envolvimento com a ação. O conceito se inscreve no quadro mais amplo da criação de ferramentas capazes de descrever a construção simultânea de ações de sujeitos individuais e coletivos.Sustained by findings in the professional world and, in particular, in the world of education and training the author proposes the concept of action culture as a shared way of organizing the construction of the meaning of activities. This transversal concept of the different forms of action seeks to unite individual and collective aspects, what remains and what changes and the mental and conative aspects in the approach to involvement with action. The concept is inscribed within the broader frame of the creation of tools that are capable of describing the simultaneous construction of the actions of individuals and groups.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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%.

  5. 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...

  6. 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. PMID:23670881

  7. Shared Representation of SAR Target and Shadow Based on Multilayer Auto-encoder

    Directory of Open Access Journals (Sweden)

    Sun Zhi-jun

    2013-06-01

    Full Text Available Automatic Target Recognition (ATR of Synthetic Aperture Radar (SAR image is investigated. A SAR feature extraction algorithm based on multilayer auto-encoder is proposed. The method makes use of a probabilistic neural network, Restricted Boltzmann Machine (RBM modeling probability distribution of environment. Through the formation of more expressive multilayer neural network, the deep learning model learns shared representation of the target and its shadow outline reflecting the target shape characteristics. Targets are classified automatically through two recognition models. The experiment results based on the MSTAR verify the effectiveness of proposed algorithm.

  8. 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.

  9. Merging linear discriminant analysis with Bag of Words model for human action recognition

    OpenAIRE

    Iosifidis, Alexandros; Tefas, Anastasios; Pitas, Ioannis

    2016-01-01

    In this paper we propose a novel method for human action recognition, that unifies discriminative Bag of Words (BoW)-based video representation and discriminant subspace learning. An iterative optimization scheme is proposed for sequential discriminant BoWs-based action representation and codebook adaptation based on action discrimination in a reduced dimensionality feature space where action classes are better discriminated. Experiments on four publicly available action recognition data sets...

  10. Sparse representation based latent components analysis for machinery weak fault detection

    Science.gov (United States)

    Tang, Haifeng; Chen, Jin; Dong, Guangming

    2014-06-01

    Weak machinery fault detection is a difficult task because of two main reasons (1) At the early stage of fault development, signature of fault related component performs incompletely and is quite different from that at the apparent failure stage. In most instances, it seems almost identical with the normal operating state. (2) The fault feature is always submerged and distorted by relatively strong background noise and macro-structural vibrations even if the fault component already performs completely, especially when the structure of fault components and interference are close. To solve these problems, we should penetrate into the underlying structure of the signal. Sparse representation provides a class of algorithms for finding succinct representations of signal that capture higher-level features in the data. With the purpose of extracting incomplete or seriously overwhelmed fault components, a sparse representation based latent components decomposition method is proposed in this paper. As a special case of sparse representation, shift-invariant sparse coding algorithm provides an effective basis functions learning scheme for capturing the underlying structure of machinery fault signal by iteratively solving two convex optimization problems: an L1-regularized least squares problem and an L2-constrained least squares problem. Among these basis functions, fault feature can be probably contained and extracted if optimal latent component is filtered. The proposed scheme is applied to analyze vibration signals of both rolling bearings and gears. Experiment of accelerated lifetime test of bearings validates the proposed method's ability of detecting early fault. Besides, experiments of fault bearings and gears with heavy noise and interference show the approach can effectively distinguish subtle differences between defect and interference. All the experimental data are analyzed by wavelet shrinkage and basis pursuit de-noising (BPDN) method for comparison.

  11. Network analysis shows novel molecular mechanisms of action for copper-based chemotherapy

    Directory of Open Access Journals (Sweden)

    Jesús eEspinal-Enríquez

    2016-01-01

    Full Text Available 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. Casiope'inas 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 Casiope'inas 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 Casiope'inas, 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.

  12. State-of-the-art in Comprehensive Cascade Control Approach through Monte-Carlo Based Representation

    Directory of Open Access Journals (Sweden)

    A.H. Mazinan

    2015-10-01

    Full Text Available The research relies on the comprehensive cascade control approach to be developed in the area of spacecraft, as long as Monte-Carlo based representation is taken into real consideration with respect to state-of-the-art. It is obvious that the conventional methods do not have sufficient merit to be able to deal with such a process under control, constantly, provided that a number of system parameters variations are to be used in providing real situations. It is to note that the new insights in the area of the research’s topic are valuable to outperform a class of spacecrafts performance as the realizations of the acquired results are to be addressed in both real and academic environments. In a word, there are a combination of double closed loop based upon quaternion based control approach in connection with Euler based control approach to handle the three-axis rotational angles and its rates, synchronously, in association with pulse modulation analysis and control allocation, where the dynamics and kinematics of the present system under control are analyzed. A series of experiments are carried out to consider the approach performance in which the aforementioned Monte-Carlo based representation is to be realized in verifying the investigated outcomes.

  13. 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.

  14. 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. PMID:26540666

  15. Building Community Linkages: Some Thoughts on Community Based Action Research.

    Science.gov (United States)

    Mora, Juana

    An original goal of Chicano Studies was to promote improvement of social and economic conditions in the community, with Chicana and Chicano scholars at the forefront of community struggles. Within this perspective, research is problem-based and part of the community action process. Chicano community groups want to work with researchers and…

  16. 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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  18. 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.

  19. 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.

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

    Science.gov (United States)

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

    2016-01-01

    According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations. PMID:27168323

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

    Directory of Open Access Journals (Sweden)

    Stella J Faerber

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

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

    Science.gov (United States)

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

    2016-01-01

    According to the norm-based version of the multidimensional face space model (nMDFS, Valentine, 1991), any given face and its corresponding anti-face (which deviates from the norm in exactly opposite direction as the original face) should be equidistant to a hypothetical prototype face (norm), such that by definition face and anti-face should bear the same level of perceived typicality. However, it has been argued that familiarity affects perceived typicality and that representations of familiar faces are qualitatively different (e.g., more robust and image-independent) from those for unfamiliar faces. Here we investigated the role of face familiarity for rated typicality, using two frequently used operationalisations of typicality (deviation-based: DEV), and distinctiveness (face in the crowd: FITC) for faces of celebrities and their corresponding anti-faces. We further assessed attractiveness, likeability and trustworthiness ratings of the stimuli, which are potentially related to typicality. For unfamiliar faces and their corresponding anti-faces, in line with the predictions of the nMDFS, our results demonstrate comparable levels of perceived typicality (DEV). In contrast, familiar faces were perceived much less typical than their anti-faces. Furthermore, familiar faces were rated higher than their anti-faces in distinctiveness, attractiveness, likability and trustworthiness. These findings suggest that familiarity strongly affects the distribution of facial representations in norm-based face space. Overall, our study suggests (1) that familiarity needs to be considered in studies of mental representations of faces, and (2) that familiarity, general distance-to-norm and more specific vector directions in face space make different and interactive contributions to different types of facial evaluations. PMID:27168323

  3. Representation is representation of similarities.

    Science.gov (United States)

    Edelman, S

    1998-08-01

    Advanced perceptual systems are faced with the problem of securing a principled (ideally, veridical) relationship between the world and its internal representation. I propose a unified approach to visual representation, addressing the need for superordinate and basic-level categorization and for the identification of specific instances of familiar categories. According to the proposed theory, a shape is represented internally by the responses of a small number of tuned modules, each broadly selective for some reference shape, whose similarity to the stimulus it measures. This amounts to embedding the stimulus in a low-dimensional proximal shape space spanned by the outputs of the active modules. This shape space supports representations of distal shape similarities that are veridical as Shepard's (1968) second-order isomorphisms (i.e., correspondence between distal and proximal similarities among shapes, rather than between distal shapes and their proximal representations). Representation in terms of similarities to reference shapes supports processing (e.g., discrimination) of shapes that are radically different from the reference ones, without the need for the computationally problematic decomposition into parts required by other theories. Furthermore, a general expression for similarity between two stimuli, based on comparisons to reference shapes, can be used to derive models of perceived similarity ranging from continuous, symmetric, and hierarchical ones, as in multidimensional scaling (Shepard 1980), to discrete and nonhierarchical ones, as in the general contrast models (Shepard & Arabie 1979; Tversky 1977). PMID:10097019

  4. 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.

  5. 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.

  6. Deep Learning-Based Feature Representation for AD/MCI Classification

    OpenAIRE

    Suk, Heung-Il; Shen, Dinggang

    2013-01-01

    In recent years, there has been a great interest in computer-aided diagnosis of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI). Unlike the previous methods that consider simple low-level features such as gray matter tissue volumes from MRI, mean signal intensities from PET, in this paper, we propose a deep learning-based feature representation with a stacked auto-encoder. We believe that there exist latent complicated patterns, e.g., non-linear relations, in...

  7. Gyrator transform based double random phase encoding with sparse representation for information authentication

    Science.gov (United States)

    Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

    2015-07-01

    Optical information security systems have drawn long-term concerns. In this paper, an optical information authentication approach using gyrator transform based double random phase encoding with sparse representation is proposed. Different from traditional optical encryption schemes, only sparse version of the ciphertext is preserved, and hence the decrypted result is completely unrecognizable and shows no similarity to the plaintext. However, we demonstrate that the noise-like decipher result can be effectively authenticated by means of optical correlation approach. Simulations prove that the proposed method is feasible and effective, and can provide additional protection for optical security systems.

  8. 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.

  9. Can Verbalisers Learn as well as Visualisers in Simulation-Based CAL with Predominantly Visual Representations? Preliminary Evidence from a Pilot Study

    Science.gov (United States)

    Liu, Tzu-Chien; Kinshuk; Lin, Yi-Chun; Wang, Ssu-Chin

    2012-01-01

    Simulation-based computer-assisted learning (CAL) is emerging as new technologies are finding a place in mainstream education. Dynamically linked multiple representations (DLMRs) is at the core of simulation-based CAL. DLMRs includes multiple visual representations, and it enables students to manipulate one representation and to immediately…

  10. 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.

  11. Voxel Based Representation of Full-Waveform Airborne Laser Scanner Data for Forestry Applications

    Science.gov (United States)

    Stelling, N.; Richter, K.

    2016-06-01

    The advantages of using airborne full-waveform laser scanner data in forest applications, e.g. for the description of the vertical vegetation structure or accurate biomass estimation, have been emphasized in many publications. To exploit the full potential offered by airborne full-waveform laser scanning data, the development of voxel based methods for data analysis is essential. In contrast to existing approaches based on the extraction of discrete 3D points by a Gaussian decomposition, it is very promising to derive the voxel attributes from the digitised waveform directly. For this purpose, the waveform data have to be transferred into a 3D voxel representation. This requires a series of radiometric and geometric transformations of the raw full-waveform laser scanner data. Thus, the paper deals with the geometric aspects and describes a processing chain from the raw waveform data to an attenuationcorrected volumetric forest stand reconstruction. The integration of attenuation-corrected waveform data into the voxel space is realised with an efficient parametric voxel traversal method operating on an octree data structure. The voxel attributes are derived from the amplitudes of the attenuation-corrected waveforms. Additionally, a new 3D filtering approach is presented to eliminate non-object voxel. Applying these methods to real full-waveform laser scanning data, a voxel based representation of a spruce was generated combining three flight strips from different viewing directions.

  12. Learning Deep Face Representation

    OpenAIRE

    Fan, Haoqiang; Cao, Zhimin; Jiang, Yuning; Yin, Qi; Doudou, Chinchilla

    2014-01-01

    Face representation is a crucial step of face recognition systems. An optimal face representation should be discriminative, robust, compact, and very easy-to-implement. While numerous hand-crafted and learning-based representations have been proposed, considerable room for improvement is still present. In this paper, we present a very easy-to-implement deep learning framework for face representation. Our method bases on a new structure of deep network (called Pyramid CNN). The proposed Pyrami...

  13. [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. PMID:24783534

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2006-10-01

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

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

    OpenAIRE

    Pasi Nieminen,; Antti Savinainen; Jouni Viiri

    2010-01-01

    This study investigates students’ ability to interpret multiple representations consistently (i.e., representational consistency) in the context of the force concept. For this purpose we developed the Representational Variant of the Force Concept Inventory (R-FCI), which makes use of nine items from the 1995 version of the Force Concept Inventory (FCI). These original FCI items were redesigned using various representations (such as motion map, vectorial and graphical), yielding 27 multiple-ch...

  16. A new graph-based molecular descriptor using the canonical representation of the molecule.

    Science.gov (United States)

    Hentabli, Hamza; Saeed, Faisal; Abdo, Ammar; Salim, Naomie

    2014-01-01

    Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD) is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE) using the Tanimoto coefficient (TAN) and the basic local alignment search tool (BLAST) when searches were carried. PMID:25140330

  17. A New Graph-Based Molecular Descriptor Using the Canonical Representation of the Molecule

    Directory of Open Access Journals (Sweden)

    Hamza Hentabli

    2014-01-01

    Full Text Available Molecular similarity is a pervasive concept in drug design. The basic idea underlying molecular similarity is the similar property principle, which states that structurally similar molecules will exhibit similar physicochemical and biological properties. In this paper, a new graph-based molecular descriptor (GBMD is introduced. The GBMD is a new method of obtaining a rough description of 2D molecular structure in textual form based on the canonical representations of the molecule outline shape and it allows rigorous structure specification using small and natural grammars. Simulated virtual screening experiments with the MDDR database show clearly the superiority of the graph-based descriptor compared to many standard descriptors (ALOGP, MACCS, EPFP4, CDKFP, PCFP, and SMILE using the Tanimoto coefficient (TAN and the basic local alignment search tool (BLAST when searches were carried.

  18. Covert imitation of transitive actions activates effector-independent motor representations affecting "motor" knowledge of target-object properties.

    Science.gov (United States)

    Campione, Giovanna Cristina; Gentilucci, Maurizio

    2010-03-01

    The present study aimed at determining whether, and in what conditions, covert imitation of different manual grasps of the same object influences estimation of those object properties whose variations afford those different grasp interactions. Participants matched the size of spheres after observation of the same spheres being grasped using both a power and a precision grasp: these actions are used preferentially to grasp large and small objects, respectively. The type of matching varied across four experiments. In experiment 1, participants matched the object size by opening their thumb and index finger; in experiment 2, they abducted their index and middle fingers as in a finger opening of a cutting pantomime, and in experiment 3, they opened their mouth. In experiment 4, the sphere size was reproduced on a PC monitor by moving the mouse forward/backward. Grasp observation affected matching in experiments 1 and 3. Kinematics analysis showed overestimation after observation of a power grasp as compared to a precision grasp. The data are interpreted as a consequence of covert imitation of the observed hand kinematics, which varied congruently with the object sizes potentially activating that type-of-grasp. This affected estimation of object size. Covert imitation was favored by the types of matching requiring motor patterns related to grasp movements independently of the effector used. This finding supports the existence of motor commands to the hand as well as to the mouth, activated when the same potential goal guides the movements of both these effectors. PMID:19850083

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

    Science.gov (United States)

    Koparan, Timur; Güven, Bülent

    2015-07-01

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

  20. 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.

  1. 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.

  2. 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.

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

    Science.gov (United States)

    Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

    2010-01-01

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

  4. 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.

  5. 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

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

    International Nuclear Information System (INIS)

    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

  7. 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.

  8. The Activation of the Representation of Subject's Profession Feature and Action during Language Comprehension%语言理解中主体职业特征与动作表征的激活

    Institute of Scientific and Technical Information of China (English)

    何先友; 晏赛君; 张大巍

    2012-01-01

    Three experiments were designed to explore the activation of the representation of subject's profession feature and action during language comprehension. Experiment 1 explored the activation of the subjects' profession feature during the comprehension of the sentences which are in the pattern of "the person who does something is ", and Experiment 2 further explored the problem in "' somebody does something ". In Experiment 3, participants were asked to recognize the pictures through mouth instead of hands. To integrate the results of Experiment 1, Experiment 3a explored the activation of the representation of the action performer during the comprehension of the sentences "the person who does something is "and whether the representation of profession feature can be activated at the same time. Experiment 3b explored the activation of the representation of the action performer during the comprehension of the sentences "somebody does something "and whether the representation of profession feature will be activated at the same time. The conclusions can be summarized as follows. The representation of subjects' profession feature is activated during the comprehen- sion of the sentences which are in the pattern of "the person who does something is " ; while with sentences such as "somebody does something", the representation of subjects' profession feature is activated only when the participants' performer is in accordance with the action performer in the sentence. The representation of the action performer is activated during processing sentences like "the person who does something is " ; while with sentences like "somebody does something", the representation of the action performer is obviously activated only when the profession described in the sentence is in accordance with that in the picture. Both the representation of subjects' profession feature and action performer are activated during comprehending sentences like "the person who does something is " ;while during

  9. An algorithm for inverse synthetic aperture imaging lidar based on sparse signal representation

    International Nuclear Information System (INIS)

    In actual applications of inverse synthetic aperture imaging lidar, the issue of sparse aperture data arises when continuous measurements are impossible or the collected data during some periods are not valid. Hence, the imaging results obtained by traditional methods are limited by high sidelobes. Considering the sparse structure of actual target space in high frequency radar application, a novel imaging method based on sparse signal representation is proposed in this paper. Firstly, the range image is acquired by traditional pulse compression of the optical heterodyne process. Then, the redundant dictionary is constructed through the sparse azimuth sampling positions and the signal form after the range compression. Finally, the imaging results are obtained by solving an ill-posed problem based on sparse regularization. Simulation results confirm the effectiveness of the proposed method. (paper)

  10. The extraction of spot signal in Shack-Hartmann wavefront sensor based on sparse representation

    Science.gov (United States)

    Zhang, Yanyan; Xu, Wentao; Chen, Suting; Ge, Junxiang; Wan, Fayu

    2016-07-01

    Several techniques have been used with Shack-Hartmann wavefront sensors to determine the local wave-front gradient across each lenslet. While the centroid error of Shack-Hartmann wavefront sensor is relatively large since the skylight background and the detector noise. In this paper, we introduce a new method based on sparse representation to extract the target signal from the background and the noise. First, an over complete dictionary of the spot signal is constructed based on two-dimensional Gaussian model. Then the Shack-Hartmann image is divided into sub blocks. The corresponding coefficients of each block is computed in the over complete dictionary. Since the coefficients of the noise and the target are large different, then extract the target by setting a threshold to the coefficients. Experimental results show that the target can be well extracted and the deviation, RMS and PV of the centroid are all smaller than the method of subtracting threshold.

  11. 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.

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

    Science.gov (United States)

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

    2008-08-01

    We present a new tensor-based morphometric framework that quantifies cortical shape variations using a local area element. The local area element is computed from the Riemannian metric tensors, which are obtained from the smooth functional parametrization of a cortical mesh. For the smooth parametrization, we have developed a novel weighted spherical harmonic (SPHARM) representation, which generalizes the traditional SPHARM as a special case. For a specific choice of weights, the weighted-SPHARM is shown to be the least squares approximation to the solution of an isotropic heat diffusion on a unit sphere. The main aims of this paper are to present the weighted-SPHARM and to show how it can be used in the tensor-based morphometry. As an illustration, the methodology has been applied in the problem of detecting abnormal cortical regions in the group of high functioning autistic subjects. PMID:18672431

  13. Springback Control of Sheet Metal Forming Based on High Dimension Model Representation and Genetic Algorithm

    Science.gov (United States)

    Long, Tang; Hu, Wang; Yong, Cai; Lichen, Mao; Guangyao, Li

    2011-08-01

    Springback is related to multi-factors in the process of metal forming. In order to construct an accurate metamodel between technical parameters and springback, a general set of quantitative model assessment and analysis tool, termed high dimension model representations (HDMR), is applied to building metamodel. Genetic algorithm is also integrated for optimization based on metamodel. Compared with widely used metamodeling techniques, the most remarkable advantage of this method is its capacity to dramatically reduce sampling effort for learning the input-output behavior from exponential growth to polynomial level. In this work, the blank holding forces (BHFs) and corresponding key time are design variables. The final springback is well controlled by the HDMR-based metamodeling technique.

  14. A reconstruction algorithm based on sparse representation for Raman signal processing under high background noise

    Science.gov (United States)

    Fan, X.; Wang, X.; Wang, X.; Xu, Y.; Que, J.; He, H.; Wang, X.; Tang, M.

    2016-02-01

    Background noise is one of the main interference sources of the Raman spectroscopy measurement and imaging technique. In this paper, a sparse representation based algorithm is presented to process the Raman signals under high background noise. In contrast with the existing de-noising methods, the proposed method reconstructs the pure Raman signals by estimating the Raman peak information. The advantage of the proposed algorithm is its high anti-noise capacity and low pure Raman signal reduction contributed by its reconstruction principle. Meanwhile, the Batch-OMP algorithm is applied to accelerate the training of the sparse representation. Therefore, it is very suitable to be adopted in the Raman measurement or imaging instruments to observe fast dynamic processes where the scanning time has to be shortened and the signal-to-noise ratio (SNR) of the raw tested signal is reduced. In the simulation and experiment, the de-noising result obtained by the proposed algorithm was better than the traditional Savitzky-Golay (S-G) filter and the fixed-threshold wavelet de-noising algorithm.

  15. Blind image deblurring based on trained dictionary and curvelet using sparse representation

    Science.gov (United States)

    Feng, Liang; Huang, Qian; Xu, Tingfa; Li, Shao

    2015-04-01

    Motion blur is one of the most significant and common artifacts causing poor image quality in digital photography, in which many factors resulted. In imaging process, if the objects are moving quickly in the scene or the camera moves in the exposure interval, the image of the scene would blur along the direction of relative motion between the camera and the scene, e.g. camera shake, atmospheric turbulence. Recently, sparse representation model has been widely used in signal and image processing, which is an effective method to describe the natural images. In this article, a new deblurring approach based on sparse representation is proposed. An overcomplete dictionary learned from the trained image samples via the KSVD algorithm is designed to represent the latent image. The motion-blur kernel can be treated as a piece-wise smooth function in image domain, whose support is approximately a thin smooth curve, so we employed curvelet to represent the blur kernel. Both of overcomplete dictionary and curvelet system have high sparsity, which improves the robustness to the noise and more satisfies the observer's visual demand. With the two priors, we constructed restoration model of blurred images and succeeded to solve the optimization problem with the help of alternating minimization technique. The experiment results prove the method can preserve the texture of original images and suppress the ring artifacts effectively.

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

    Science.gov (United States)

    Zhang, Xinzheng; Yang, Qiuyue; Liu, Miaomiao; Jia, Yunjian; Liu, Shujun; Li, Guojun

    2016-01-01

    Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS) sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ1-regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR) database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance. PMID:27598172

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

    Directory of Open Access Journals (Sweden)

    Xiuquan Du

    2015-01-01

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

  18. 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.

  19. A reconstruction algorithm based on sparse representation for Raman signal processing under high background noise

    International Nuclear Information System (INIS)

    Background noise is one of the main interference sources of the Raman spectroscopy measurement and imaging technique. In this paper, a sparse representation based algorithm is presented to process the Raman signals under high background noise. In contrast with the existing de-noising methods, the proposed method reconstructs the pure Raman signals by estimating the Raman peak information. The advantage of the proposed algorithm is its high anti-noise capacity and low pure Raman signal reduction contributed by its reconstruction principle. Meanwhile, the Batch-OMP algorithm is applied to accelerate the training of the sparse representation. Therefore, it is very suitable to be adopted in the Raman measurement or imaging instruments to observe fast dynamic processes where the scanning time has to be shortened and the signal-to-noise ratio (SNR) of the raw tested signal is reduced. In the simulation and experiment, the de-noising result obtained by the proposed algorithm was better than the traditional Savitzky-Golay (S-G) filter and the fixed-threshold wavelet de-noising algorithm

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

    Directory of Open Access Journals (Sweden)

    Xinzheng Zhang

    2016-09-01

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

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

    Science.gov (United States)

    Zhang, Xinzheng; Yang, Qiuyue; Liu, Miaomiao; Jia, Yunjian; Liu, Shujun; Li, Guojun

    2016-01-01

    Classification of target microwave images is an important application in much areas such as security, surveillance, etc. With respect to the task of microwave image classification, a recognition algorithm based on aspect-aided dynamic non-negative least square (ADNNLS) sparse representation is proposed. Firstly, an aspect sector is determined, the center of which is the estimated aspect angle of the testing sample. The training samples in the aspect sector are divided into active atoms and inactive atoms by smooth self-representative learning. Secondly, for each testing sample, the corresponding active atoms are selected dynamically, thereby establishing dynamic dictionary. Thirdly, the testing sample is represented with ℓ 1 -regularized non-negative sparse representation under the corresponding dynamic dictionary. Finally, the class label of the testing sample is identified by use of the minimum reconstruction error. Verification of the proposed algorithm was conducted using the Moving and Stationary Target Acquisition and Recognition (MSTAR) database which was acquired by synthetic aperture radar. Experiment results validated that the proposed approach was able to capture the local aspect characteristics of microwave images effectively, thereby improving the classification performance. PMID:27598172

  2. 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.

  3. 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.

  4. Sparse representation based on local time-frequency template matching for bearing transient fault feature extraction

    Science.gov (United States)

    He, Qingbo; Ding, Xiaoxi

    2016-05-01

    The transients caused by the localized fault are important measurement information for bearing fault diagnosis. Thus it is crucial to extract the transients from the bearing vibration or acoustic signals that are always corrupted by a large amount of background noise. In this paper, an iterative transient feature extraction approach is proposed based on time-frequency (TF) domain sparse representation. The approach is realized by presenting a new method, called local TF template matching. In this method, the TF atoms are constructed based on the TF distribution (TFD) of the Morlet wavelet bases and local TF templates are formulated from the TF atoms for the matching process. The instantaneous frequency (IF) ridge calculated from the TFD of an analyzed signal provides the frequency parameter values for the TF atoms as well as an effective template matching path on the TF plane. In each iteration, local TF templates are employed to do correlation with the TFD of the analyzed signal along the IF ridge tube for identifying the optimum parameters of transient wavelet model. With this iterative procedure, transients can be extracted in the TF domain from measured signals one by one. The final signal can be synthesized by combining the extracted TF atoms and the phase of the raw signal. The local TF template matching builds an effective TF matching-based sparse representation approach with the merit of satisfying the native pulse waveform structure of transients. The effectiveness of the proposed method is verified by practical defective bearing signals. Comparison results also show that the proposed method is superior to traditional methods in transient feature extraction.

  5. 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...

  6. The Effects of Directive Self-Explanation Prompts to Support Active Processing of Multiple Representations in a Simulation-Based Learning Environment

    Science.gov (United States)

    van der Meij, J.; de Jong, T.

    2011-01-01

    Processing of multiple representations in multimedia learning environments is considered to help learners obtain a more complete overview of the domain and gain deeper knowledge. This is based on the idea that relating and translating different representations leads to reflection beyond the boundaries and details of the separate representations.…

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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...

  14. 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.

  15. Deep Learning-Based Feature Representation for AD/MCI Classification

    Science.gov (United States)

    Suk, Heung-Il; Shen, Dinggang

    2014-01-01

    In recent years, there has been a great interest in computer-aided diagnosis of Alzheimer’s Disease (AD) and its prodromal stage, Mild Cognitive Impairment (MCI). Unlike the previous methods that consider simple low-level features such as gray matter tissue volumes from MRI, mean signal intensities from PET, in this paper, we propose a deep learning-based feature representation with a stacked auto-encoder. We believe that there exist latent complicated patterns, e.g., non-linear relations, inherent in the low-level features. Combining latent information with the original low-level features helps build a robust model for AD/MCI classification with high diagnostic accuracy. Using the ADNI dataset, we conducted experiments showing that the proposed method is 95.9%, 85.0%, and 75.8% accurate for AD, MCI, and MCI-converter diagnosis, respectively. PMID:24579188

  16. 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.

  17. Representational Thickness

    DEFF Research Database (Denmark)

    Mullins, Michael

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

  18. 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.

  19. 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.

  20. 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. PMID:26906674

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

    Science.gov (United States)

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

    2016-05-01

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

  2. 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.

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

    Directory of Open Access Journals (Sweden)

    Radovanović Bojana

    2014-01-01

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

  5. 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.

  6. A Sparse Representation Based Method to Classify Pulmonary Patterns of Diffuse Lung Diseases

    Directory of Open Access Journals (Sweden)

    Wei Zhao

    2015-01-01

    Full Text Available 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.

  7. 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.

  8. A nonparametric feature for neonatal EEG seizure detection based on a representation of pseudo-periodicity.

    Science.gov (United States)

    Stevenson, N J; O'Toole, J M; Rankine, L J; Boylan, G B; Boashash, B

    2012-05-01

    Automated methods of neonatal EEG seizure detection attempt to highlight the evolving, stereotypical, pseudo-periodic, nature of EEG seizure while rejecting the nonstationary, modulated, coloured stochastic background in the presence of various EEG artefacts. An important aspect of neonatal seizure detection is, therefore, the accurate representation and detection of pseudo-periodicity in the neonatal EEG. This paper describes a method of detecting pseudo-periodic components associated with neonatal EEG seizure based on a novel signal representation; the nonstationary frequency marginal (NFM). The NFM can be considered as an alternative time-frequency distribution (TFD) frequency marginal. This method integrates the TFD along data-dependent, time-frequency paths that are automatically extracted from the TFD using an edge linking procedure and has the advantage of reducing the dimension of a TFD. The reduction in dimension simplifies the process of estimating a decision statistic designed for the detection of the pseudo-periodicity associated with neonatal EEG seizure. The use of the NFM resulted in a significant detection improvement compared to existing stationary and nonstationary methods. The decision statistic estimated using the NFM was then combined with a measurement of EEG amplitude and nominal pre- and post-processing stages to form a seizure detection algorithm. This algorithm was tested on a neonatal EEG database of 18 neonates, 826 h in length with 1389 seizures, and achieved comparable performance to existing second generation algorithms (a median receiver operating characteristic area of 0.902; IQR 0.835-0.943 across 18 neonates). PMID:21925920

  9. Multi-class remote sensing object recognition based on discriminative sparse representation.

    Science.gov (United States)

    Wang, Xin; Shen, Siqiu; Ning, Chen; Huang, Fengchen; Gao, Hongmin

    2016-02-20

    The automatic recognition of multi-class objects with various backgrounds is a big challenge in the field of remote sensing (RS) image analysis. In this paper, we propose a novel recognition framework for multi-class RS objects based on the discriminative sparse representation. In this framework, the recognition problem is implemented in two stages. In the first, or discriminative dictionary learning stage, considering the characterization of remote sensing objects, the scale-invariant feature transform descriptor is first combined with an improved bag-of-words model for multi-class objects feature extraction and representation. Then, information about each class of training samples is fused into the dictionary learning process; by using the K-singular value decomposition algorithm, a discriminative dictionary can be learned for sparse coding. In the second, or recognition, stage, to improve the computational efficiency, the phase spectrum of a quaternion Fourier transform model is applied to the test image to predict a small set of object candidate locations. Then, a multi-scale sliding window mechanism is utilized to scan the image over those candidate locations to obtain the object candidates (or objects of interest). Subsequently, the sparse coding coefficients of these candidates under the discriminative dictionary are mapped to the discriminative vectors that have a good ability to distinguish different classes of objects. Finally, multi-class object recognition can be accomplished by analyzing these vectors. The experimental results show that the proposed work outperforms a number of state-of-the-art methods for multi-class remote sensing object recognition. PMID:26906591

  10. Gender Difference in the Use of Thought Representation--A Corpus-Based Study

    Science.gov (United States)

    Riissanen, Anne; Watson, Greg

    2014-01-01

    This study (Note 1) investigates potential differences in language use between genders, by applying a modified model of thought representation. Our hypothesis is that women use more direct forms of thought representation than men in modern spoken British English. Women are said to favour "private speech" that creates intimacy and…

  11. Research-Based Worksheets on Using Multiple Representations in Science Classrooms

    Science.gov (United States)

    Hill, Matthew; Sharma, Manjula

    2015-01-01

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

  12. 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.

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

    Science.gov (United States)

    Rau, Martina A.; Pardos, Zachary A.

    2012-01-01

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

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

    Science.gov (United States)

    Wang, Shunfang; Liu, Shuhui

    2015-12-19

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

  15. 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.

  16. Joint action changes valence-based action coding in an implicit attitude task.

    Science.gov (United States)

    Stenzel, Anna; Liepelt, Roman

    2016-09-01

    Recent studies suggest that co-acting with another person induces a problem to discriminate between one's own and the other's actions which can be resolved by emphasizing action features that discriminate best between both persons' actions in a given task context. Mostly, overt action features like the spatial position of responses have been suggested as discriminating action features. In the present study, we tested whether non-externally perceivable, covert action features can be used for resolving the action discrimination problem during joint action. Therefore, we compared task performance between a joint and an individual version of the Go/Nogo Association Task, a task requiring the association of a valence to the response. We found a larger implicit attitude effect in the joint than in the individual setting for person-related (self and other, Experiment 1) as well as for non-person-related attitude objects (fruit and insect, Experiment 2) suggesting that the weight of valence information is increased in the internal coding of responses when valence discriminates between both responses. In contrast, we found a smaller implicit attitude effect in a person present setting than an individual setting (Experiment 3) indicating that the enhanced implicit attitude effect observed in the joint settings of Experiments 1 and 2 is not due to social facilitation. Our results suggest that action discrimination during joint action can rely on covert action features. The results are in line with the referential coding account, and specify the kind of action features that are represented when sharing a task with another person. PMID:26215432

  17. AIN-Based Action Selection Mechanism for Soccer Robot Systems

    OpenAIRE

    Yin-Tien Wang; Zhi-Jun You; Chia-Hsing Chen

    2009-01-01

    Role and action selections are two major procedures of the game strategy for multiple robots playing the soccer game. In role-select procedure, a formation is planned for the soccer team, and a role is assigned to each individual robot. In action-select procedure, each robot executes an action provided by an action selection mechanism to fulfill its role playing. The role-select procedure was often designed efficiently by using the geometry approach. However, the action-select procedure devel...

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

    Science.gov (United States)

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

    2012-03-01

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

  19. Cell-based representation and analysis of social-economic data in grid-city construction

    Science.gov (United States)

    Liu, Xiangnan; Huang, Fang; Wang, Ping

    2007-06-01

    Grid-city management currently attracts a wider audience globally. Socio-economic data is an essential part of grid-city management system. Social-economic data of an urban is characterized by discrete, time-varying, statistical, distributed and complicated. Most of data are with no exactly spatial location or from various statistical units. There is obvious gap while matching social-economic data with existing grid map of natural geographical elements emerges. It may cause many difficulties in data input, organization, processing and analysis while the grid system constructing and executing. The issue of how to allocate and integrate the huge social-economic data into each grid effectively is crucial for grid-city construction. In this paper, we discussed the characteristics of social-economic data in a grid-city systematically, thereafter a cell-based model for social-economic data representing and analyzing is presented in this paper. The kernel issues of the cell-based model establishment include cell size determining, cell capabilities developing for multi-dimension representation and evaluation, and cell dynamic simulation functions designing. The cell-based model supplements the methods system of spatial data mining, and is also promising in application to the spatialization of statistical data obtained from other researches including environmental monitoring, hydrological and meteorological observation.

  20. 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.

  1. 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...

  2. 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.

  3. 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.

  4. 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.

  5. Force Concept Inventory-based multiple-choice test for investigating students' representational consistency

    Science.gov (United States)

    Nieminen, Pasi; Savinainen, Antti; Viiri, Jouni

    2010-07-01

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

  6. Neural underpinnings of superior action prediction abilities in soccer players

    OpenAIRE

    Makris, Stergios; Urgesi, Cosimo

    2014-01-01

    The ability to form anticipatory representations of ongoing actions is crucial for effective interactions in dynamic environments. In sports, elite athletes exhibit greater ability than novices in predicting other players’ actions, mainly based on reading their body kinematics. This superior perceptual ability has been associated with a modulation of visual and motor areas by visual and motor expertise. Here, we investigated the causative role of visual and motor action representations in exp...

  7. 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…

  8. 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

    2008-01-01

    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…

  9. 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.

  10. Beyond sensory images: Object-based representation in the human ventral pathway

    OpenAIRE

    Pietrini, Pietro; Furey, Maura L.; Ricciardi, Emiliano; Gobbini, M. Ida; Wu, W.-H. Carolyn; Cohen, Leonardo; Guazzelli, Mario; Haxby, James V.

    2004-01-01

    We investigated whether the topographically organized, category-related patterns of neural response in the ventral visual pathway are a representation of sensory images or a more abstract representation of object form that is not dependent on sensory modality. We used functional MRI to measure patterns of response evoked during visual and tactile recognition of faces and manmade objects in sighted subjects and during tactile recognition in blind subjects. Results showed that visual and tactil...

  11. Dim moving target tracking algorithm based on particle discriminative sparse representation

    Science.gov (United States)

    Li, Zhengzhou; Li, Jianing; Ge, Fengzeng; Shao, Wanxing; Liu, Bing; Jin, Gang

    2016-03-01

    The small dim moving target usually submerged in strong noise, and its motion observability is debased by numerous false alarms for low signal-to-noise ratio (SNR). A target tracking algorithm based on particle filter and discriminative sparse representation is proposed in this paper to cope with the uncertainty of dim moving target tracking. The weight of every particle is the crucial factor to ensuring the accuracy of dim target tracking for particle filter (PF) that can achieve excellent performance even under the situation of non-linear and non-Gaussian motion. In discriminative over-complete dictionary constructed according to image sequence, the target dictionary describes target signal and the background dictionary embeds background clutter. The difference between target particle and background particle is enhanced to a great extent, and the weight of every particle is then measured by means of the residual after reconstruction using the prescribed number of target atoms and their corresponding coefficients. The movement state of dim moving target is then estimated and finally tracked by these weighted particles. Meanwhile, the subspace of over-complete dictionary is updated online by the stochastic estimation algorithm. Some experiments are induced and the experimental results show the proposed algorithm could improve the performance of moving target tracking by enhancing the consistency between the posteriori probability distribution and the moving target state.

  12. 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.

  13. 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.

  14. System II: A Native RDF Repository Based on the Hypergraph Representation for RDF Data Model

    Institute of Scientific and Technical Information of China (English)

    Gang Wu; Juan-Zi Li; Jian-Qiang Hu; Ke-Hong Wang

    2009-01-01

    RDF is the data interchange layer for the Semantic Web. In order to manage the increasing amount of RDF data, an RDF repository should provide not only the necessary scalability and efficiency, but also sufficient inference capabilities. Though existing RDF repositories have made progress towards these goals, there is still ample space for improving the overall performance. In this paper, we propose a native RDF repository, System II, to pursue a better tradeoff among system scalability, query efficiency, and inference capabilities. System II takes a hypergraph representation for RDF as the data model for its persistent storage, which effectively avoids the costs of data model transformation when accessing RDF data. Based on this native storage scheme, a set of efficient semantic query processing techniques are designed. First, several indices are built to accelerate RDF data access including a value index, a labeling scheme for transitive closure computation, and three triple indices. Second, we propose a hybrid inference strategy under the pD* semantics to support inference for OWL-Lite with a relatively low computational complexity. Finally, we extend the SPARQL algebra to explicitly express inference semantics in logical query plan by defining some new algebra operators. In addition, MD5 hash value of URI and schema level cacheare introduced as practical implementation techniques. The results of performance evaluation on the LUBM benchmark and a real data set show that System II has a better combined metric value than other comparable systems.

  15. 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.

  16. 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...

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

    Science.gov (United States)

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

    2013-03-01

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

  18. Building the knowledge base for environmental action and sustainability

    DEFF Research Database (Denmark)

    2015-01-01

    and – no conference without them ‐ all paper and poster authors, workshop organisers, helping hands, and participants for their work, enthusiasm and participation! Copenhagen, September 2015 Vivian Kvist Johannsen, Stefan Jensen, Volker Wohlgemuth, Chris Preist and Elina Eriksson (Chair Persons and Proceedings...... was “Building the knowledge base for environmental action and sustainability”. The joint conference was designed to facilitate ‘within‐the‐domain’, as well as to create a space for developing synergies between the two communities. Altogether 125 research and applied papers (including extended abstracts) from 42...... abstracts of applied papers were published in the Adjunct Proceedings, together with abstracts of 26 poster submissions and 11 workshop descriptions. The conference aims at renewing and vitalizing the concept of scientific conferences with the help of a partly new design, tiled ”ConverStations”, sessions...

  19. Representation Discovery using Harmonic Analysis

    CERN Document Server

    Mahadevan, Sridhar

    2008-01-01

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

  20. Performance improvement in multi-ship imaging for ScanSAR based on sparse representation

    Institute of Scientific and Technical Information of China (English)

    XU Gang; SHENG JiaLian; ZHANG Lei; XING MengDao

    2012-01-01

    There is always a compromise between unambiguous wide-swath imaging and high cross-range resolution owing to the constraint of minimum antenna area for conventional single-channel spaceborne synthetic aperture radar (SAR) imaging.To overcome the inherent systemic limitation,multi-channel SAR imaging has been developed. Nevertheless,this still suffers from various problems such as high system complexity. To simplify the system structure,a novel algorithm for high resolution multi-ship ScanSAR imaging based on sparse representation is proposed in this paper,where the SAR imaging model is established via maximum a posterior estimation by utilizing the sparsity prior of multi-ship targets.In the scheme,a wide swath is generated in the ScanSAR mode by continuously switching the radar footprint between subswaths.Meanwhile,high crossrange resolution is realized from sparse subapertures by exploiting the sparsity feature of multi-ship imaging.In particular,the SAR observation operator is constructed approximately as the inverse of conventional SAR imaging and then high resolution SAR imaging including range cell migration compensation is achieved by solving the optimization.Compared with multi-channel SAR imaging,the system complexity is effectively reduced in the ScanSAR mode.In addition,enhancement of the cross-range resolution is realized by incorporating the sparsity prior with sparse subapertures.As a result,the amount of data is effectively reduced.Experiments based on measured data have been carried out to confirm the effectiveness and validity of the proposed algorithm.

  1. 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.

  2. A graph-cut approach to image segmentation using an affinity graph based on l0−sparse representation of features

    OpenAIRE

    Wang, Xiaofang; Li, Huibin; Bichot, Charles-Edmond; Masnou, Simon; Chen, Liming

    2013-01-01

    International audience We propose a graph-cut based image segmentation method by constructing an affinity graph using l0 sparse representation. Computing first oversegmented images, we associate with all segments, that we call superpixels, a collection of features. We find the sparse representation of each set of features over the dictionary of all features by solving a l0-minimization problem. Then, the connection information between superpixels is encoded as the non-zero representation c...

  3. Facial action detection using block-based pyramid appearance descriptors

    NARCIS (Netherlands)

    Jiang, Bihan; Valstar, Michel F.; Pantic, Maja

    2012-01-01

    Facial expression is one of the most important non-verbal behavioural cues in social signals. Constructing an effective face representation from images is an essential step for successful facial behaviour analysis. Most existing face descriptors operate on the same scale, and do not leverage coarse

  4. Developing representations of compound stimuli

    NARCIS (Netherlands)

    I. Visser; M.E.J. Raijmakers

    2012-01-01

    Classification based on multiple dimensions of stimuli is usually associated with similarity-based representations, whereas uni-dimensional classifications are associated with rule-based representations. This paper studies classification of stimuli and category representations in school-aged childre

  5. 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.

  6. 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…

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

    Directory of Open Access Journals (Sweden)

    Farley Simon Nobre

    2014-04-01

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

  8. Relationship of students' conceptual representations and problem-solving abilities in acid-base chemistry

    Science.gov (United States)

    Powers, Angela R.

    2000-10-01

    This study explored the relationship between secondary chemistry students' conceptual representations of acid-base chemistry, as shown in student-constructed concept maps, and their ability to solve acid-base problems, represented by their score on an 18-item paper and pencil test, the Acid-Base Concept Assessment (ABCA). The ABCA, consisting of both multiple-choice and short-answer items, was originally designed using a question-type by subtopic matrix, validated by a panel of experts, and refined through pilot studies and factor analysis to create the final instrument. The concept map task included a short introduction to concept mapping, a prototype concept map, a practice concept-mapping activity, and the instructions for the acid-base concept map task. The instruments were administered to chemistry students at two high schools; 108 subjects completed both instruments for this study. Factor analysis of ABCA results indicated that the test was unifactorial for these students, despite the intention to create an instrument with multiple "question-type" scales. Concept maps were scored both holistically and by counting valid concepts. The two approaches were highly correlated (r = 0.75). The correlation between ABCA score and concept-map score was 0.29 for holistically-scored concept maps and 0.33 for counted-concept maps. Although both correlations were significant, they accounted for only 8.8 and 10.2% of variance in ABCA scores, respectively. However, when the reliability of the instruments used is considered, more than 20% of the variance in ABCA scores may be explained by concept map scores. MANOVAs for ABCA and concept map scores by instructor, student gender, and year in school showed significant differences for both holistic and counted concept-map scores. Discriminant analysis revealed that the source of these differences was the instruction variable. Significant differences between classes receiving different instruction were found in the frequency of

  9. 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.

  10. 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.

  11. 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)

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    Action recognition systems mostly work with videos of proper quality and resolution. Even most challenging bench- mark databases for action recognition, hardly include videos of low-resolution from, e.g., surveillance cameras. In videos recorded by such cameras, due to the distance between people...

  13. 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

  14. 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.

  15. 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.

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

    OpenAIRE

    Zhongwen Hu; Qingquan Li; Qian Zhang; Guofeng Wu

    2016-01-01

    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 refin...

  17. Shifting internal parent-child representations among caregivers of teens with serious behaviour problems: An attachment-based approach

    OpenAIRE

    Moretti, M. M.; Obsuth, I.; Mayseless, O.; SCHARF, M.

    2012-01-01

    Attachment theory provides a rich framework for the development of interventions for trauma. This study examined processes underlying treatment outcomes of an attachment-based program (Connect; Moretti, Braber, & Obsuth, 2009) for parents of teens with severe behavior problems. Caregivers completed the Parenting Representations Interview and the Child Behavior Checklist prior to and following treatment. Results confirmed significant reductions in teens' problem behavior and changes in par...

  18. 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.

  19. 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

  20. 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…

  1. 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

  2. Graphical representations of the chemistry of garnets in a three-dimensional MATLAB based provenance plot

    Science.gov (United States)

    Knierzinger, Wolfgang; Palzer, Markus; Wagreich, Michael; Meszar, Maria; Gier, Susanne

    2016-04-01

    A newly developed, MATLAB based garnet provenance plot allows a three-dimensional tetrahedral representation of the chemistry of garnets for the endmembers almandine, pyrope, spessartine and grossular. Based on a freely accessible database of Suggate & Hall (2013) and additional EPMA-data on the internet, the chemistry of more than 2500 garnets was evaluated and used to create various subfields that correspond to different facies conditions of metapelitic, metasomatic and metaigneous rocks as well as granitic rocks. These triangulated subfields act as reference structures within the tetrahedron, facilitating assignments of garnet chemistries to different lithologies. In comparison with conventional tenary garnet discrimination diagrams by Mange & Morton (2007), Wright/Preston et al. (1938/2002) and Aubrecht et al. (2009), this tetrahedral provenance plot enables a better assessment of the conditions of formation of garnets by reducing the overlapping of certain subfields. In particular, a clearer distinction between greenschist facies rocks, amphibolite facies rocks and granitic rocks can be achieved. First applications of the tetrahedral garnet plot provided new insights on sedimentary processes during the Lower Miocene in the pre-Alpine Molasse basin. Bibliography Aubrecht, R., Meres, S., Sykora, M., Mikus, T. (2009). Provenance of the detrital garnets and spinels from the Albian sediments of the Czorsztyn Unit (Pieniny Klippen Belt , Western Carpathians, Slovakia). In: Geologica Carpathica, Dec. 2009, 60, 6, pp. 463-483. Mange, M.A., Morton, A.C. (2007). Geochemistry of Heavy Minerals. In: Mange, M.A. & Wright, D.T.(2007).Heavy Minerals in Use, Amsterdam, pp. 345-391. Preston, J., Hartley, A., Mange-Rajetzky, M., Hole, M., May, G., Buck, S., Vaughan, L. (2002). The provenance of Triassic continental sandstones from the Beryl Field, northern North Sea: Mineralogical, geochemical and sedimentological constraints. In: Journal of Sedimentary Research, 72, pp. 18

  3. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    , and dialogue, of situated participants. The article includes a lengthy example of a poetic representation of one participant’s story, and the author comments on the potentials of ‘doing’ poetic representations as an example of writing in ways that challenges what sometimes goes unasked in participative social...... be written up and disseminated. The article takes a methodological focus, considering general aims and methods of the research project, before turning to the elaboration on how poetic representations have been constructed and employed as a vehicle for certain kinds of participation, representation...

  4. 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. PMID:9929345

  5. 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.

  6. 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…

  7. 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.

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

    OpenAIRE

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

    2011-01-01

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

  9. Supporting the translation between multiple representations

    NARCIS (Netherlands)

    Meij, van der J.; Jong, de T.; Mason, Lucia; Andreuzza, Silvia; Arfè, Barbara; Del Favero, Laura

    2003-01-01

    Modern, computer based, learning environments often embrace a multitude of representations. Research with learning environments that contain multiple representations has revealed that learning with multiple representations can lead to deeper understanding but also that processing different represent

  10. 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.

  11. 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.

  12. Evaluation of a Computer-Based Training Program for Enhancing Arithmetic Skills and Spatial Number Representation in Primary School Children

    Science.gov (United States)

    Rauscher, Larissa; Kohn, Juliane; Käser, Tanja; Mayer, Verena; Kucian, Karin; McCaskey, Ursina; Esser, Günter; von Aster, Michael

    2016-01-01

    Calcularis is a computer-based training program which focuses on basic numerical skills, spatial representation of numbers and arithmetic operations. The program includes a user model allowing flexible adaptation to the child's individual knowledge and learning profile. The study design to evaluate the training comprises three conditions (Calcularis group, waiting control group, spelling training group). One hundred and thirty-eight children from second to fifth grade participated in the study. Training duration comprised a minimum of 24 training sessions of 20 min within a time period of 6–8 weeks. Compared to the group without training (waiting control group) and the group with an alternative training (spelling training group), the children of the Calcularis group demonstrated a higher benefit in subtraction and number line estimation with medium to large effect sizes. Therefore, Calcularis can be used effectively to support children in arithmetic performance and spatial number representation. PMID:27445889

  13. Evaluation of a Computer-Based Training Program for Enhancing Arithmetic Skills and Spatial Number Representation in Primary School Children.

    Science.gov (United States)

    Rauscher, Larissa; Kohn, Juliane; Käser, Tanja; Mayer, Verena; Kucian, Karin; McCaskey, Ursina; Esser, Günter; von Aster, Michael

    2016-01-01

    Calcularis is a computer-based training program which focuses on basic numerical skills, spatial representation of numbers and arithmetic operations. The program includes a user model allowing flexible adaptation to the child's individual knowledge and learning profile. The study design to evaluate the training comprises three conditions (Calcularis group, waiting control group, spelling training group). One hundred and thirty-eight children from second to fifth grade participated in the study. Training duration comprised a minimum of 24 training sessions of 20 min within a time period of 6-8 weeks. Compared to the group without training (waiting control group) and the group with an alternative training (spelling training group), the children of the Calcularis group demonstrated a higher benefit in subtraction and number line estimation with medium to large effect sizes. Therefore, Calcularis can be used effectively to support children in arithmetic performance and spatial number representation. PMID:27445889

  14. Generic Representation of Y( s o(3)) Based on the Lie Algebraic Basis of s o(3)

    Science.gov (United States)

    Zhang, Hong-Biao; Wang, Gang-Cheng

    2016-05-01

    We focus on constructing a generic representation of Y( s o(3)) based on the Lie algebraic basis of s o(3) basis, and further developing transition of Yangian operator hat Y. As an application of Y( s o(3)), we calculate all the matrix elements of unit vector operators hat n in angular momentum basis. It is also discovered that the Yangian operator hat Y may work in quantum vector space. In addition, some shift operators hat {O}^{(± )}_{μ } are naturally built on the basis of the representation of Y( s o(3)). As an another application of Y( s o(3)), we can derive the CG cofficients of two coupled angular momenta from the down-shift operator hat {O}^{(-)}_{-1} acting on a s o(3)-coupled tensor basis. This not only explores that Yangian algebras can work in quantum tensor space, but also provides a novel approach to solve CG coefficients for two coupled angular momenta.

  15. 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.…

  16. Function and Form of Action-Based Teaching in Higher Education

    DEFF Research Database (Denmark)

    Keiding, Tina Bering

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

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

    OpenAIRE

    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 datasets are stored in disparate data silos, using different models and schemas for their description. To overcome this interoperability barrier, the presented framework employs a modular and scalabl...

  18. 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.

  19. 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. PMID:27032953

  20. Wavelet-Based Interpolation and Representation of Non-Uniformly Sampled Spacecraft Mission Data

    Science.gov (United States)

    Bose, Tamal

    2000-01-01

    A well-documented problem in the analysis of data collected by spacecraft instruments is the need for an accurate, efficient representation of the data set. The data may suffer from several problems, including additive noise, data dropouts, an irregularly-spaced sampling grid, and time-delayed sampling. These data irregularities render most traditional signal processing techniques unusable, and thus the data must be interpolated onto an even grid before scientific analysis techniques can be applied. In addition, the extremely large volume of data collected by scientific instrumentation presents many challenging problems in the area of compression, visualization, and analysis. Therefore, a representation of the data is needed which provides a structure which is conducive to these applications. Wavelet representations of data have already been shown to possess excellent characteristics for compression, data analysis, and imaging. The main goal of this project is to develop a new adaptive filtering algorithm for image restoration and compression. The algorithm should have low computational complexity and a fast convergence rate. This will make the algorithm suitable for real-time applications. The algorithm should be able to remove additive noise and reconstruct lost data samples from images.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. 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

  8. 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.

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

    Science.gov (United States)

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

    2016-03-01

    Over the last years, in a series papers by Arecchi and others, a model for the cognitive processes involved in decision making has been proposed and investigated. The key element of this model is the expression of apprehension and judgment, basic cognitive process of decision making, as an inverse Bayes inference classifying the information content of neuron spike trains. It has been shown that for successive plural stimuli this inference, equipped with basic non-algorithmic jumps, is affected by quantum-like characteristics. We show here that such a decision making process is related consistently with an ambiguous representation by an observer within a universe of discourse. In our work the ambiguous representation of an object or a stimuli is defined as a pair of maps from objects of a set to their representations, where these two maps are interrelated in a particular structure. The a priori and a posteriori hypotheses in Bayes inference are replaced by the upper and lower approximations, correspondingly, for the initial data sets that are derived with respect to each map. Upper and lower approximations herein are defined in the context of "rough set" analysis. The inverse Bayes inference is implemented by the lower approximations with respect to the one map and for the upper approximation with respect to the other map for a given data set. We show further that, due to the particular structural relation between the two maps, the logical structure of such combined approximations can only be expressed as an orthomodular lattice and therefore can be represented by a quantum rather than a Boolean logic. To our knowledge, this is the first investigation aiming to reveal the concrete logic structure of inverse Bayes inference in cognitive processes. PMID:26861118

  10. An update on HL7's XML-based document representation standards.

    OpenAIRE

    Dolin, R H; Alschuler, L.; BOYER S.; Beebe, C.

    2000-01-01

    Many people know of HL7 as an organization that creates healthcare messaging standards. But HL7 is also developing standards for the representation of clinical documents (such as discharge summaries and consultation notes). These document standards comprise the HL7 Clinical Document Architecture (CDA). Last year we presented a high-level conceptual overview of the CDA. Since that time, CDA has entered HL7's formal ballot process (which when successful will make the CDA an ANSI-approved HL7 st...

  11. A Novel Face Recognition Approach Based on Two-Step Test Sample Representation

    OpenAIRE

    Zun-xiong Liu; Zhi-qiang Huang; Heng Zhang

    2013-01-01

    The two-step test sample representation method is proposed for face recognition. It first identifies k “representative” samples from each category training samples for the test sample then produces a weighted sum of all the “representative” samples that well approximates the test sample. This method assigns the test sample to the class whose training samples have the smallest deviation from the test sample. As the method proposed in this paper is able to reduce the side-effect of the other tr...

  12. 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,…

  13. 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

  14. Change detection based on deep feature representation and mapping transformation for multi-spatial-resolution remote sensing images

    Science.gov (United States)

    Zhang, Puzhao; Gong, Maoguo; Su, Linzhi; Liu, Jia; Li, Zhizhou

    2016-06-01

    Multi-spatial-resolution change detection is a newly proposed issue and it is of great significance in remote sensing, environmental and land use monitoring, etc. Though multi-spatial-resolution image-pair are two kinds of representations of the same reality, they are often incommensurable superficially due to their different modalities and properties. In this paper, we present a novel multi-spatial-resolution change detection framework, which incorporates deep-architecture-based unsupervised feature learning and mapping-based feature change analysis. Firstly, we transform multi-resolution image-pair into the same pixel-resolution through co-registration, followed by details recovery, which is designed to remedy the spatial details lost in the registration. Secondly, the denoising autoencoder is stacked to learn local and high-level representation/feature from the local neighborhood of the given pixel, in an unsupervised fashion. Thirdly, motivated by the fact that multi-resolution image-pair share the same reality in the unchanged regions, we try to explore the inner relationships between them by building a mapping neural network. And it can be used to learn a mapping function based on the most-unlikely-changed feature-pairs, which are selected from all the feature-pairs via a coarse initial change map generated in advance. The learned mapping function can bridge the different representations and highlight changes. Finally, we can build a robust and contractive change map through feature similarity analysis, and the change detection result is obtained through the segmentation of the final change map. Experiments are carried out on four real datasets, and the results confirmed the effectiveness and superiority of the proposed method.

  15. Memetics of representation

    Directory of Open Access Journals (Sweden)

    Roberto De Rubertis

    2012-06-01

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

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

    Science.gov (United States)

    Holsopple, Jared; Yang, Shanchieh; Argauer, Brian

    2008-03-01

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

  17. 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.

  18. 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...

  19. Value Representations

    DEFF Research Database (Denmark)

    Rasmussen, Majken Kirkegaard; Petersen, Marianne Graves

    2011-01-01

    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...... are fictional, value-driven concepts developed to promote dialogue with users about their values and how they may materialize with respect to interaction design in their everyday lives....

  20. 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.

  1. 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.

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

    OpenAIRE

    Levi Gimenez; Antonio Benedito Silva Oliveira

    2013-01-01

    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, con...

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

    OpenAIRE

    Konrad Graf

    2011-01-01

    Action-based legal theory is a discrete branch of praxeology and the basis of an emerging school of jurisprudence related to, but distinct from, natural law. Legal theory and economic theory share content that is part of praxeology itself: the action axiom, the a priori of argumentation, universalizable property theory, and counterfactual-deductive methodology. Praxeological property-norm justification is separate from the strictly ethical “ought” question of selecting ends in an action conte...

  4. Integration of Voxel Colouring Technique in the Volumetric Textures Representation Based on Image Layers

    Directory of Open Access Journals (Sweden)

    Babahenini M. Chaouki

    2006-01-01

    Full Text Available This paper presents a method for integrating a technique of reconstruction scene (voxel colouring starting from images of the reference element of a volumetric texture, this one will be converted in a second phase into a whole of layers (2D images considered as transparent textures, which will be projected and composed successively on surface defined as volumetric grid using the Z-buffer algorithm. The model suggested allows primarily made realistic of repetitive complex scenes lower cost of calculation due to the effective exploitation of the capacities of the graphics boards and to the fact that it takes account of the level of detail according to the distance of the observer and the vision angle, in the representation of the reference element.

  5. An efficient classification method based on principal component and sparse representation.

    Science.gov (United States)

    Zhai, Lin; Fu, Shujun; Zhang, Caiming; Liu, Yunxian; Wang, Lu; Liu, Guohua; Yang, Mingqiang

    2016-01-01

    As an important application in optical imaging, palmprint recognition is interfered by many unfavorable factors. An effective fusion of blockwise bi-directional two-dimensional principal component analysis and grouping sparse classification is presented. The dimension reduction and normalizing are implemented by the blockwise bi-directional two-dimensional principal component analysis for palmprint images to extract feature matrixes, which are assembled into an overcomplete dictionary in sparse classification. A subspace orthogonal matching pursuit algorithm is designed to solve the grouping sparse representation. Finally, the classification result is gained by comparing the residual between testing and reconstructed images. Experiments are carried out on a palmprint database, and the results show that this method has better robustness against position and illumination changes of palmprint images, and can get higher rate of palmprint recognition. PMID:27386281

  6. An update on HL7's XML-based document representation standards.

    Science.gov (United States)

    Dolin, R H; Alschuler, L; Boyer, S; Beebe, C

    2000-01-01

    Many people know of HL7 as an organization that creates healthcare messaging standards. But HL7 is also developing standards for the representation of clinical documents (such as discharge summaries and consultation notes). These document standards comprise the HL7 Clinical Document Architecture (CDA). Last year we presented a high-level conceptual overview of the CDA. Since that time, CDA has entered HL7's formal ballot process (which when successful will make the CDA an ANSI-approved HL7 standard). This article delves into the technical details of the current CDA proposal. Note that due to space limitations, only a subset of CDA details can be described. Also, because the ballot process elicits considerable feedback, it is likely that the material presented here will undergo evolution prior to becoming a final standard. The most up-to-date information is available on HL7's web site (www.hl7.org). PMID:11079871

  7. 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.

  8. 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.

  9. 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.

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

    Science.gov (United States)

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

    2014-12-01

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

  11. 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…

  12. More evidence for a refined Gribov-Zwanziger action based on an effective potential approach

    OpenAIRE

    Vandersickel, N.; Dudal, D.; Sorella, S.P.

    2011-01-01

    The purpose of this proceeding is twofold. Firstly, we shall make the refining of the Gribov-Zwanziger action more complete by taking into account more condensates than considered so far. Secondly, we shall provide more evidence for the refined Gribov-Zwanziger action based on an effective potential approach.

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

    DEFF Research Database (Denmark)

    Majgaard, Gunver

    2010-01-01

    Why is design based action research method important in the world of robot technology and learning? The article explores how action research and interaction-driven design can be used in development of educational robot technological tools. The actual case is the development of “Fraction Battle” w...

  14. 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....

  15. 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.

  16. 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.

  17. Dynamic Mental Representations of Habitual Behaviours: Food Choice on a Web-Based Environment

    Directory of Open Access Journals (Sweden)

    Rui Gaspar

    2016-08-01

    Full Text Available AimRather than being rigid, habitual behaviours may be determined by dynamic mental representations that can adapt to context changes. This adaptive potential may result from particular conditions dependent on the interaction between two sources of mental constructs activation: perceived context applicability and cognitive accessibility.MethodTwo web-shopping simulations offering the choice between habitually chosen and non-habitually chosen food products were presented to participants. This considered two choice contexts differing in the habitual behaviour perceived applicability (low vs. high and a measure of habitual behaviour chronicity.ResultsStudy 1 demonstrated a perceived applicability effect, with more habitual (non-organic than non-habitual (organic food products chosen in a high perceived applicability (familiar than in a low perceived applicability (new context. The adaptive potential of habitual behaviour was evident in the habitual products choice consistency across three successive choices, despite the decrease in perceived applicability. Study 2 evidenced the adaptive potential in strong habitual behaviour participants – high chronic accessibility – who chose a habitual product (milk more than a non-habitual product (orange juice, even when perceived applicability was reduced (new context.ConclusionResults portray consumers as adaptive decision makers that can flexibly cope with changes in their (inner and outer choice contexts.

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

    Science.gov (United States)

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

    2016-01-01

    In this paper, we present a vehicle active safety model for vehicle speed control based on driver vigilance detection using low-cost, comfortable, wearable electroencephalographic (EEG) sensors and sparse representation. The proposed system consists of three main steps, namely wireless wearable EEG collection, driver vigilance detection, and vehicle speed control strategy. First of all, a homemade low-cost comfortable wearable brain-computer interface (BCI) system with eight channels is designed for collecting the driver's EEG signal. Second, wavelet de-noising and down-sample algorithms are utilized to enhance the quality of EEG data, and Fast Fourier Transformation (FFT) is adopted to extract the EEG power spectrum density (PSD). In this step, sparse representation classification combined with k-singular value decomposition (KSVD) is firstly introduced in PSD to estimate the driver's vigilance level. Finally, a novel safety strategy of vehicle speed control, which controls the electronic throttle opening and automatic braking after driver fatigue detection using the above method, is presented to avoid serious collisions and traffic accidents. The simulation and practical testing results demonstrate the feasibility of the vehicle active safety model. PMID:26907278

  19. Mind the gap between both hands: evidence for internal finger-based number representations in children's mental calculation.

    Science.gov (United States)

    Domahs, Frank; Krinzinger, Helga; Willmes, Klaus

    2008-04-01

    At a certain stage of development, virtually all children use some kind of external finger-based number representation. However, only little is known about how internal traces of this early external representation may still influence calculation even when finger calculation ceases to be an efficient tool in mental calculation. In the present study, we provide evidence for a disproportionate number of split-five errors (i.e., errors with a difference of +/-5 from the correct result) in mental addition and subtraction (e.g., 18 - 7 = 6). We will argue that such errors may have different origins. For complex problems and initially also for simple problems they are due to failure to keep track of 'full hands' in counting or calculation procedures. However, for simple addition problems split-five errors may later also be caused by mistakes in directly retrieving the result from declarative memory. In general, the present results are interpreted in terms of a transient use of mental finger patterns - in particular the whole hand pattern - in children's mental calculation. PMID:18387566

  20. 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.

  1. 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.

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

    International Nuclear Information System (INIS)

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

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

    NARCIS (Netherlands)

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

    2009-01-01

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

  4. Assessing the Potential Impact of a Nationwide Class-Based Affirmative Action System

    OpenAIRE

    Xiang, Alice; Rubin, Donald B.

    2015-01-01

    We examine the possible consequences of a change in law school admissions in the United States from an affirmative action system based on race to one based on socioeconomic class. Using data from the 1991-1996 Law School Admission Council Bar Passage Study, students were reassigned attendance by simulation to law school tiers by transferring the affirmative action advantage for black students to students from low socioeconomic backgrounds. The hypothetical academic outcomes for the students w...

  5. Developing Representations of Compound Stimuli

    Directory of Open Access Journals (Sweden)

    Ingmar eVisser

    2012-03-01

    Full Text Available Classification based on multiple dimensions of stimuli is usually associated with similarity-based representations, whereas uni-dimensional classifications are associated with rule-based representations. This paper studies classification of stimuli and category representations in school-aged children and adults when learning to categorize compound, multidimensional stimuli. Stimuli were such that both similarity-based and rule-based representations would lead to correct classification. This allows testing whether children have a bias for formation of similarity-based representations. The results are at odds with this expectation. Children use both uni-dimensional and multidimensional classification, and the use of both strategies increases with age. Multidimensional classification is best characterized as resulting from an analytic strategy rather than from procedural processing of overall-similarity. The conclusion is that children are capable of using complex rule-based categorization strategies that involve the use of multiple features of the stimuli.

  6. Embedded data representations

    DEFF Research Database (Denmark)

    Willett, W.; Jansen, Yvonne; Dragicevic, P.

    2016-01-01

    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 ......-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.......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...

  7. 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.

  8. Freeman Chain Code (FCC Representation in Signature Fraud Detection Based On Nearest Neighbour and Artificial Neural Network (ANN Classifiers

    Directory of Open Access Journals (Sweden)

    Aini Najwa Azmi

    2014-12-01

    Full Text Available This paper presents a signature verification system that used Freeman Chain Code (FCC as directional feature and data representation. There are 47 features were extracted from the signature images from six global features. Before extracting the features, the raw images were undergoing pre-processing stages which were binarization, noise removal by using media filter, cropping and thinning to produce Thinned Binary Image (TBI. Euclidean distance is measured and matched between nearest neighbours to find the result. MCYT-SignatureOff-75 database was used. Based on our experiment, the lowest FRR achieved is 6.67% and lowest FAR is 12.44% with only 1.12 second computational time from nearest neighbour classifier. The results are compared with Artificial Neural Network (ANN classifier.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    Perzyński Konrad

    2015-06-01

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

  11. Live-action Virtual Reality Games

    OpenAIRE

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

    2016-01-01

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

  12. Improving mass detection using combined feature representations from projection views and reconstructed volume of DBT and boosting based classification with feature selection

    International Nuclear Information System (INIS)

    In digital breast tomosynthesis (DBT), image characteristics of projection views and reconstructed volume are different and both have the advantage of detecting breast masses, e.g. reconstructed volume mitigates a tissue overlap, while projection views have less reconstruction blur artifacts. In this paper, an improved mass detection is proposed by using combined feature representations from projection views and reconstructed volume in the DBT. To take advantage of complementary effects on different image characteristics of both data, combined feature representations are extracted from both projection views and reconstructed volume concurrently. An indirect region-of-interest segmentation in projection views, which projects volume-of-interest in reconstructed volume into the corresponding projection views, is proposed to extract combined feature representations. In addition, a boosting based classification with feature selection has been employed for selecting effective feature representations among a large number of combined feature representations, and for reducing false positives. Experiments have been conducted on a clinical data set that contains malignant masses. Experimental results demonstrate that the proposed mass detection can achieve high sensitivity with a small number of false positives. In addition, the experimental results demonstrate that the selected feature representations for classifying masses complementarily come from both projection views and reconstructed volume. (paper)

  13. Model-based action planning involves cortico-cerebellar and basal ganglia networks

    Science.gov (United States)

    Fermin, Alan S. R.; Yoshida, Takehiko; Yoshimoto, Junichiro; Ito, Makoto; Tanaka, Saori C.; Doya, Kenji

    2016-01-01

    Humans can select actions by learning, planning, or retrieving motor memories. Reinforcement Learning (RL) associates these processes with three major classes of strategies for action selection: exploratory RL learns state-action values by exploration, model-based RL uses internal models to simulate future states reached by hypothetical actions, and motor-memory RL selects past successful state-action mapping. In order to investigate the neural substrates that implement these strategies, we conducted a functional magnetic resonance imaging (fMRI) experiment while humans performed a sequential action selection task under conditions that promoted the use of a specific RL strategy. The ventromedial prefrontal cortex and ventral striatum increased activity in the exploratory condition; the dorsolateral prefrontal cortex, dorsomedial striatum, and lateral cerebellum in the model-based condition; and the supplementary motor area, putamen, and anterior cerebellum in the motor-memory condition. These findings suggest that a distinct prefrontal-basal ganglia and cerebellar network implements the model-based RL action selection strategy. PMID:27539554

  14. Model-based action planning involves cortico-cerebellar and basal ganglia networks.

    Science.gov (United States)

    Fermin, Alan S R; Yoshida, Takehiko; Yoshimoto, Junichiro; Ito, Makoto; Tanaka, Saori C; Doya, Kenji

    2016-01-01

    Humans can select actions by learning, planning, or retrieving motor memories. Reinforcement Learning (RL) associates these processes with three major classes of strategies for action selection: exploratory RL learns state-action values by exploration, model-based RL uses internal models to simulate future states reached by hypothetical actions, and motor-memory RL selects past successful state-action mapping. In order to investigate the neural substrates that implement these strategies, we conducted a functional magnetic resonance imaging (fMRI) experiment while humans performed a sequential action selection task under conditions that promoted the use of a specific RL strategy. The ventromedial prefrontal cortex and ventral striatum increased activity in the exploratory condition; the dorsolateral prefrontal cortex, dorsomedial striatum, and lateral cerebellum in the model-based condition; and the supplementary motor area, putamen, and anterior cerebellum in the motor-memory condition. These findings suggest that a distinct prefrontal-basal ganglia and cerebellar network implements the model-based RL action selection strategy. PMID:27539554

  15. A Multidisciplinary Osteoporosis Service-Based Action Research Study

    Science.gov (United States)

    Whitehead, Dean; Keast, John; Montgomery, Val; Hayman, Sue

    2004-01-01

    Objective: To investigate an existing Trust-based osteoporosis service's preventative activity, determine any issues and problems and use this data to reorganise the service, as part of a National Health Service Executive/Regional Office-commissioned and funded study. Setting: A UK Hospital Trust's Osteoporosis Service. Design & Method: A…

  16. Focussing on student actions through case based learning

    OpenAIRE

    Dejonckheere, Peter; Vervaet, Stephanie; Van De Keere, Kristof

    2015-01-01

    In the present study a case based approach for teaching scientific inquiry was designed and tested in one single teacher department with 60 preschool teacher students. A pretest, an intervention with video cases and a posttest was used. The following elements were measured in both the pretest and the posttest: a) to what extent, students rate themselves as competent in doing science in preschool classrooms, b) what is their attitude towards science in a professional context and c) which didac...

  17. Arsenic-Based Antineoplastic Drugs and Their Mechanisms of Action

    OpenAIRE

    Ralph, Stephen John

    2008-01-01

    Arsenic-based compounds have become accepted agents for cancer therapy providing high rates of remission of some cancers such as acute promyelocytic leukemia (APL). The mechanisms by which arsenic-containing compounds kill cells and reasons for selective killing of only certain types of cancer cells such as APLs have recently been delineated. This knowledge was gained in parallel with increasing understanding and awareness of the importance of intracellular redox systems and regulation of the...

  18. A LOOK AT NATURE. From observation to representation

    Directory of Open Access Journals (Sweden)

    Annina Ruf

    2010-06-01

    Full Text Available To look, to see, to observe, to represent. The exercises that are presented are based upon the above mentioned verbs. The first three verbs are related to knowledge that can be translated into representation. The looking action represents our most generic approach with fenomenic reality, it is the starting point of a fisiologic characteristic that belongs to us and to other living creatures. The seeing action is a voluntary consequence of the previous act and it represents the precise will to create a relationship based upon our decisions. The observing action is a deeping act that approaches reality focusing our attention on it. The representing action is another deeping act that both: a allows reality to reappear in front of us as we know it beacuse of our previous seeing action; b allows to translate reality into its evocation.

  19. Social representations and normative beliefs of aging.

    Science.gov (United States)

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

    2015-12-01

    This study adopted the theory of social representations as a theoretical framework in order to characterize similarities and differences in social representations and normative beliefs of aging for different age groups. The 638 participants responded to self-administered questionnaire and were equally distributed by sex and age. The results show that aging is characterized by positive stereotypes (knowledge and experience); however, retirement is linked to aging, but in a negative way, particularly for men, involving illness, loneliness and disability. When age was considered, it was verified that the connections with the representational elements became more complex for older groups, showing social representation functionality, largely for the elderly. Adulthood seems to be preferred and old age is disliked. There were divergences related to the perception of the beginning of life phases, especially that of old age. Work was characterized as the opposite of aging, and it revealed the need for actions intended for the elderly and retired workers, with post-retirement projects. In addition, it suggests investment in public policies that encourage intergenerational contact, with efforts to reduce intolerance and discrimination based on age of people. PMID:26691788

  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. 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.

  3. 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.

  4. A Comprehensive Noise Robust Speech Parameterization Algorithm Using Wavelet Packet Decomposition-Based Denoising and Speech Feature Representation Techniques

    Science.gov (United States)

    Kotnik, Bojan; Kačič, Zdravko

    2007-12-01

    This paper concerns the problem of automatic speech recognition in noise-intense and adverse environments. The main goal of the proposed work is the definition, implementation, and evaluation of a novel noise robust speech signal parameterization algorithm. The proposed procedure is based on time-frequency speech signal representation using wavelet packet decomposition. A new modified soft thresholding algorithm based on time-frequency adaptive threshold determination was developed to efficiently reduce the level of additive noise in the input noisy speech signal. A two-stage Gaussian mixture model (GMM)-based classifier was developed to perform speech/nonspeech as well as voiced/unvoiced classification. The adaptive topology of the wavelet packet decomposition tree based on voiced/unvoiced detection was introduced to separately analyze voiced and unvoiced segments of the speech signal. The main feature vector consists of a combination of log-root compressed wavelet packet parameters, and autoregressive parameters. The final output feature vector is produced using a two-staged feature vector postprocessing procedure. In the experimental framework, the noisy speech databases Aurora 2 and Aurora 3 were applied together with corresponding standardized acoustical model training/testing procedures. The automatic speech recognition performance achieved using the proposed noise robust speech parameterization procedure was compared to the standardized mel-frequency cepstral coefficient (MFCC) feature extraction procedures ETSI ES 201 108 and ETSI ES 202 050.

  5. 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. PMID:26800983

  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. 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.

  8. 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.

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

    OpenAIRE

    J Michael Pearson; Emad A. Abu Shanab; Khalil Md Nor

    2008-01-01

    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 fr...

  10. 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

  11. 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…

  12. 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.…

  13. Implementation of evidence-based health care using action research: An emancipatory approach.

    Science.gov (United States)

    Cordeiro, Luciana; Soares, Cassia Baldini

    2016-08-01

    The aim of the study is to discuss the emancipatory approach to action research as an appropriate methodology for workers' meaningful implementation of evidence-based health care. Implementation of evidence-based health care using action research is well supported by the literature. There are various approaches to action research, and they are coherent with the objectives and methods elected to develop the investigation. It is not clear which approach of action research is responsible for meaningful worker engagement in changing praxis. This is a discussion paper based on our experiences and supported by literature on collective health. Health care is defined as a social praxis, dependent upon the capitalist mode of production in which health workers engage themselves in a labour process that has negative (as alienation) as well as positive (as creativity) meanings. Emancipatory changes of social praxis through implementation of evidence-based health care require that participants understand the positive and negative meanings of their work and engage health workers in a conscious and intentional collaborative educational process. Implementation of evidence-based health care through emancipatory action research is capable of overcoming alienation and changing social practice through a participatory meaningful process of knowledge translation. PMID:27562664

  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. 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...... a user inferred from user interactions with the eLeanrning systems is used to adapt o®ered learning resources and guide a learner through them. This keynote gives an overview about knowledge and rules taken into account in current adaptive eLearning prototypes when adapting learning instructions....... Adaptation is usually based on knowledge about learning esources and users. Rules are used for heuristics to match the learning resources with learners and infer adaptation decisions....

  16. Word Sense Disambiguation using Aggregated Similarity based on WordNet Graph Representation

    Directory of Open Access Journals (Sweden)

    Mădălina ZURINI

    2013-01-01

    Full Text Available The term of word sense disambiguation, WSD, is introduced in the context of text document processing. A knowledge based approach is conducted using WordNet lexical ontology, describing its structure and components used for the process of identification of context related senses of each polysemy words. The principal distance measures using the graph associated to WordNet are presented, analyzing their advantages and disadvantages. A general model for aggregation of distances and probabilities is proposed and implemented in an application in order to detect the context senses of each word. For the non-existing words from WordNet, a similarity measure is used based on probabilities of co-occurrences. The module of WSD is proposed for integration in the step of processing documents such as supervised and unsupervised classification in order to maximize the correctness of the classification. Future work is related to the implementation of different domain oriented ontologies.

  17. 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.

  18. A Comprehensive Analysis of Deep Learning Based Representation for Face Recognition

    OpenAIRE

    Ghazi, Mostafa Mehdipour; Ekenel, Hazim Kemal

    2016-01-01

    Deep learning based approaches have been dominating the face recognition field due to the significant performance improvement they have provided on the challenging wild datasets. These approaches have been extensively tested on such unconstrained datasets, on the Labeled Faces in the Wild and YouTube Faces, to name a few. However, their capability to handle individual appearance variations caused by factors such as head pose, illumination, occlusion, and misalignment has not been thoroughly a...

  19. A Sparse Representation-Based Deployment Method for Optimizing the Observation Quality of Camera Networks

    OpenAIRE

    Guangming Shi; Xiaotian Wang; Fei Qi; Chang Wang

    2013-01-01

    Deployment is a critical issue affecting the quality of service of camera networks. The deployment aims at adopting the least number of cameras to cover the whole scene, which may have obstacles to occlude the line of sight, with expected observation quality. This is generally formulated as a non-convex optimization problem, which is hard to solve in polynomial time. In this paper, we propose an efficient convex solution for deployment optimizing the observation quality based on a novel aniso...

  20. Encyclopedia Fact Extraction, Querying and Answer Generation: Based On MRS Representations of Natural Language

    OpenAIRE

    Lyngaas, Ståle

    2008-01-01

    This master's thesis explores the possibility of using the Linguistic Knowledge Builder (LKB) in conjunction with a Prolog based program in a framework which integrates encyclypedia search for finding answer to natural language questions. I outline an architecture and a proof-of-concept implementation that shows that this is possible. With the current implementation, answers can be found when the question is just an anaphoric or simple ontological relational reference away from the sentences...

  1. Understanding representations in design

    DEFF Research Database (Denmark)

    Bødker, Susanne

    1998-01-01

    Representing computer applications and their use is an important aspect of design. In various ways, designers need to externalize design proposals and present them to other designers, users, or managers. This article deals with understanding design representations and the work they do in design....... The article is based on a series of theoretical concepts coming out of studies of scientific and other work practices and on practical experiences from design of computer applications. The article presents alternatives to the ideas that design representations are mappings of present or future work...... regarding use and design. The article proposes that abstraction, elevating the representation from the situation, is not the only way to do this, and it proposes alternatives....

  2. 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.

  3. 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.

  4. 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.

  5. Manipulating Representations.

    Science.gov (United States)

    Recchia-Luciani, Angelo N M

    2012-04-01

    The present paper proposes a definition for the complex polysemic concepts of consciousness and awareness (in humans as well as in other species), and puts forward the idea of a progressive ontological development of consciousness from a state of 'childhood' awareness, in order to explain that humans are not only able to manipulate objects, but also their mental representations. The paper builds on the idea of qualia intended as entities posing regular invariant requests to neural processes, trough the permanence of different properties. The concept of semantic differential introduces the properties of metaphorical qualia as an exclusively human ability. Furthermore this paper proposes a classification of qualia, according to the models-with different levels of abstraction-they are implied in, in a taxonomic perspective. This, in turn, becomes a source of categorization of divergent representations, sign systems, and forms of intentionality, relying always on biological criteria. New emerging image-of-the-world-devices are proposed, whose qualia are likely to be only accessible to humans: emotional qualia, where emotion accounts for the invariant and dominant property; and the qualic self where continuity, combined with the oneness of the self, accounts for the invariant and dominant property. The concept of congruence between different domains in a metaphor introduces the possibility of a general evaluation of truth and falsity of all kinds of metaphorical constructs, while the work of Matte Blanco enables us to classify conscious versus unconscious metaphors, both in individuals and in social organizations. PMID:22347988

  6. 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...

  7. The Representation of Legal Contracts

    OpenAIRE

    Daskalopulu, Aspassia; Sergot, Marek

    2001-01-01

    The paper outlines ongoing research on logic-based tools for the analysis and representation of legal contracts of the kind frequently encountered in large-scale engineering projects and complex, long-term trading agreements. We consider both contract formation and contract performance, in each case identifying the representational issues and the prospects for providing automated support tools.

  8. 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.

  9. a Topic Modeling Based Representation to Detect Tweet Locations. Example of the Event "je Suis Charlie"

    Science.gov (United States)

    Morchid, M.; Josselin, D.; Portilla, Y.; Dufour, R.; Altman, E.; Linarès, G.

    2015-09-01

    Social Networks became a major actor in information propagation. Using the Twitter popular platform, mobile users post or relay messages from different locations. The tweet content, meaning and location, show how an event-such as the bursty one "JeSuisCharlie", happened in France in January 2015, is comprehended in different countries. This research aims at clustering the tweets according to the co-occurrence of their terms, including the country, and forecasting the probable country of a non-located tweet, knowing its content. First, we present the process of collecting a large quantity of data from the Twitter website. We finally have a set of 2,189 located tweets about "Charlie", from the 7th to the 14th of January. We describe an original method adapted from the Author-Topic (AT) model based on the Latent Dirichlet Allocation (LDA) method. We define an homogeneous space containing both lexical content (words) and spatial information (country). During a training process on a part of the sample, we provide a set of clusters (topics) based on statistical relations between lexical and spatial terms. During a clustering task, we evaluate the method effectiveness on the rest of the sample that reaches up to 95% of good assignment. It shows that our model is pertinent to foresee tweet location after a learning process.

  10. Coupled circuit based representation of piezoelectric structures modeled using the finite volume method.

    Science.gov (United States)

    Bolborici, V; Dawson, F P

    2016-03-01

    This paper presents the methodology of generating a corresponding electrical circuit for a simple piezoelectric plate modeled with the finite volume method. The corresponding circuit is implemented using a circuit simulation software and the simulation results are compared to the finite volume modeling results for validation. It is noticed that both, the finite volume model and its corresponding circuit, generate identical results. The results of a corresponding circuit based on the finite volume model are also compared to the results of a corresponding circuit based on a simplified analytical model for a long piezoelectric plate, and to finite element simulation results for the same plate. It is observed that, for one control volume, the finite volume model corresponding circuit and the simplified analytical model corresponding circuit generate close results. It is also noticed that the results of the two corresponding circuits are different from the best approximation results obtained with high resolution finite element simulations due to the approximations made in the simplified analytical model and the fact that only one finite volume was used in the finite volume model. The implementation of the circuit can be automated for higher order systems by a program that takes as an input the matrix of the system and the forcing function vector, and returns a net list for the circuit. PMID:26639999

  11. Identification of Protein-Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information.

    Science.gov (United States)

    Ding, Yijie; Tang, Jijun; Guo, Fei

    2016-01-01

    Identification of protein-protein interactions (PPIs) is a difficult and important problem in biology. Since experimental methods for predicting PPIs are both expensive and time-consuming, many computational methods have been developed to predict PPIs and interaction networks, which can be used to complement experimental approaches. However, these methods have limitations to overcome. They need a large number of homology proteins or literature to be applied in their method. In this paper, we propose a novel matrix-based protein sequence representation approach to predict PPIs, using an ensemble learning method for classification. We construct the matrix of Amino Acid Contact (AAC), based on the statistical analysis of residue-pairing frequencies in a database of 6323 protein-protein complexes. We first represent the protein sequence as a Substitution Matrix Representation (SMR) matrix. Then, the feature vector is extracted by applying algorithms of Histogram of Oriented Gradient (HOG) and Singular Value Decomposition (SVD) on the SMR matrix. Finally, we feed the feature vector into a Random Forest (RF) for judging interaction pairs and non-interaction pairs. Our method is applied to several PPI datasets to evaluate its performance. On the S . c e r e v i s i a e dataset, our method achieves 94 . 83 % accuracy and 92 . 40 % sensitivity. Compared with existing methods, and the accuracy of our method is increased by 0 . 11 percentage points. On the H . p y l o r i dataset, our method achieves 89 . 06 % accuracy and 88 . 15 % sensitivity, the accuracy of our method is increased by 0 . 76 % . On the H u m a n PPI dataset, our method achieves 97 . 60 % accuracy and 96 . 37 % sensitivity, and the accuracy of our method is increased by 1 . 30 % . In addition, we test our method on a very important PPI network, and it achieves 92 . 71 % accuracy. In the Wnt-related network, the accuracy of our method is increased by 16 . 67 % . The source code and all datasets are available

  12. 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.

  13. 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.

  14. 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.

  15. Compressed sensing SAR imaging based on sparse representation in fractional Fourier domain

    Institute of Scientific and Technical Information of China (English)

    BU HongXia; BAI Xia; TAO Ran

    2012-01-01

    Compressed sensing (CS) is a new technique of utilizing a priori knowledge on sparsity of data in a certain domain for minimizing necessary number of measurements.Based on this idea,this paper proposes a novel synthetic aperture radar (SAR) imaging approach by exploiting sparseness of echo data in the fractional Fourier domain.The effectiveness and robustness of the approach are assessed by some numerical experiments under various noisy conditions and different measurement matrices.Experimental results have shown that,the obtained images by using the CS technique depend on measurement matrix and have higher output signal to noise ratio than traditional pulse compression technique. Finally simulated and real data are also processed and the achieved results show that the proposed approach is capable of reconstructing the image of targets and effectively suppressing noise.

  16. 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.

  17. 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.

  18. 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.

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

    International Nuclear Information System (INIS)

    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.

  20. Online learning and generalization of parts-based image representations by non-negative sparse autoencoders.

    Science.gov (United States)

    Lemme, Andre; Reinhart, René Felix; Steil, Jochen Jakob

    2012-09-01

    We present an efficient online learning scheme for non-negative sparse coding in autoencoder neural networks. It comprises a novel synaptic decay rule that ensures non-negative weights in combination with an intrinsic self-adaptation rule that optimizes sparseness of the non-negative encoding. We show that non-negativity constrains the space of solutions such that overfitting is prevented and very similar encodings are found irrespective of the network initialization and size. We benchmark the novel method on real-world datasets of handwritten digits and faces. The autoencoder yields higher sparseness and lower reconstruction errors than related offline algorithms based on matrix factorization. It generalizes to new inputs both accurately and without costly computations, which is fundamentally different from the classical matrix factorization approaches. PMID:22706093