WorldWideScience

Sample records for based action representation

  1. Primitive Based Action Representation and Recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker

    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 present...

  2. Primitive Based Action Representation and recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan

    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......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...... primitives automatically. These primitives are to be used to generate actions based on certain rules for combining. These rules are expressed as a stochastic context free grammar. A model merging approach is adopted to learn a Hidden Markov Model to t the observed data sequences. The states of the HMM...

  3. Action simulation: Time course and representational mechanisms

    Directory of Open Access Journals (Sweden)

    AnneSpringer

    2013-07-01

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

  4. Action recognition in video using a spatial-temporal graph-based feature representation

    OpenAIRE

    Jargalsaikhan, Iveel; Little, Suzanne; Trichet, Remi; O'Connor, Noel E.

    2015-01-01

    We propose a video graph based human action recognition framework. Given an input video sequence, we extract spatio-temporal local features and construct a video graph to incorporate appearance and motion constraints to reflect the spatio-temporal dependencies among features. them. In particular, we extend a popular dbscan density-based clustering algorithm to form an intuitive video graph. During training, we estimate a linear SVM classifier using the standard Bag-of-words method. Duri...

  5. Efficient Interaction Recognition through Positive Action Representation

    Directory of Open Access Journals (Sweden)

    Tao Hu

    2013-01-01

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

  6. 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. 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.

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. Local torus actions modeled on the standard representation

    OpenAIRE

    Yoshida, Takahiko

    2007-01-01

    We introduce the notion of a local torus action modeled on the standard representation (for simplicity, we call it a local torus action). It is a generalization of a locally standard torus action and also an underlying structure of a locally toric Lagrangian fibration. For a local torus action, we define two invariants called a characteristic pair and an Euler class of the orbit map, and prove that local torus actions are classified topologically by them. As a corollary, we obtain a topologic...

  14. 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...

  15. Action Representation in Patients with Bilateral Vestibular Impairments

    Science.gov (United States)

    Demougeot, Laurent; Toupet, Michel; Van Nechel, Christian; Papaxanthis, Charalambos

    2011-01-01

    During mental actions subjects feel themselves performing a movement without any corresponding motor output. Although broad information is available regarding the influence of central lesions on action representation, little is known about how peripheral damages affect mental events. In the current study, we investigated whether lack of vestibular information influences action representation. Twelve healthy adults and twelve patients with bilateral vestibular damage actually performed and mentally simulated walking and drawing. The locomotor paths implied one (first walking task) and four (second walking task) changes in the walking direction. In the drawing task, participants drew on a sheet of paper a path that was similar to that of the second walking task. We recorded and compared between the two groups the timing of actual and mental movements. We found significant temporal discrepancies between actual and mental walking movements in the group of patients. Conversely, drawing actual and drawing mental durations were similar. For the control group, an isochrony between mental and actual movements was observed for the three tasks. This result denotes an inconsistency between action representation and action execution following vestibular damage, which is specific to walking movements, and emphasizes the role of the vestibular system upon mental states of actions. This observation may have important clinical implications. During action planning vestibular patients may overestimate the capacity of their motor system (imaging faster, executing slower) with harmful consequences for their health. PMID:22039548

  16. 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...

  17. Linking language with embodied and teleological representations of action for humanoid cognition

    Directory of Open Access Journals (Sweden)

    Michel Hoen

    2010-06-01

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

  18. A Knowledge Representation Model for Video—Based Animation

    Institute of Scientific and Technical Information of China (English)

    劳志强; 潘云鹤

    1998-01-01

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

  19. 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...

  20. 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

  1. 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.

  2. 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.

  3. Representation of synchronous, asynchronous, and polychronous components by clocked guarded actions

    OpenAIRE

    Brandt, Jens; Gemünde, Mike; Schneider, Klaus; Shukla, Sandeep; Talpin, Jean-Pierre

    2012-01-01

    For the design of embedded systems, many languages are in use, which are based on different models of computation such as event-, data-, and clock-driven paradigms as well as paradigms without a clear notion of time. Systems composed of such heterogeneous components are hard to analyze so that mainly co-simulation by coupling different simulators has been considered so-far. In this article, we propose clocked guarded actions as a unique intermediate representation that can be used as a common...

  4. 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.

  5. 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

  6. 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 ...

  7. Emotional actions are coded via two mechanisms: with and without identity representation

    OpenAIRE

    Wincenciak, Joanna; Ingham, Jennie; Jellema, Tjeerd; Barraclough, Nicholas Edward

    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 emot...

  8. 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...

  9. 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.

  10. 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

  11. 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

  12. 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

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

    Directory of Open Access Journals (Sweden)

    Amoruso, Lucía

    2011-05-01

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

  14. Co-occurrence Feature Learning for Skeleton based Action Recognition using Regularized Deep LSTM Networks

    OpenAIRE

    Zhu, Wentao; Lan, Cuiling; Xing, Junliang; Zeng, Wenjun; Li, Yanghao; Shen, Li; Xie, Xiaohui

    2016-01-01

    Skeleton based action recognition distinguishes human actions using the trajectories of skeleton joints, which provide a very good representation for describing actions. Considering that recurrent neural networks (RNNs) with Long Short-Term Memory (LSTM) can learn feature representations and model long-term temporal dependencies automatically, we propose an end-to-end fully connected deep LSTM network for skeleton based action recognition. Inspired by the observation that the co-occurrences o...

  15. 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...

  16. 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...

  17. 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.

  18. 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

  19. 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...

  20. 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

  1. 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. ...

  2. 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.

  3. 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

  4. 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...

  5. 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...

  6. An fMRI study of imitation: action representation and body schema

    OpenAIRE

    Chaminade, Thierry; Meltzoff, Andrew N.; Decety, Jean

    2005-01-01

    Recent neuropsychological investigations of apraxia have led to new hypotheses about the representational defects associated with imitation impairments in neurological patients. This fMRI experiment investigated the relation between imitation and the body schema in healthy subjects. Experimental conditions were derived from a factorial plan, and participants were asked to watch a human model performing bodily gestures and then to execute either an identical or a different action, with the sam...

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

    DEFF Research Database (Denmark)

    Petrick, Ronald; Kraft, Dirk; Mourao, Kira; Geib, Christopher; Pugeault, Nicolas; Krüger, Norbert; Steedman, Mark

    We describe an approach to integrated robot control, high-level planning, and action effect learning that attempts to overcome the representational difficulties that exist between these diverse areas. Our approach combines ideas from robot vision, knowledgelevel planning, and connectionist machine......-level action specifications, suitable for planning, from a robot’s interactions with the world. We present a detailed overview of our approach and show how it supports the learning of certain aspects of a high-level lepresentation from low-level world state information....

  8. 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

  9. 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

  10. 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.

  11. 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.

  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. Representation of spatial relations and structures in object-based knowledge representation systems

    OpenAIRE

    Le Ber, Florence; Napoli, Amedeo

    2000-01-01

    This paper is concerned with representing spatial structures in object-based knowledge representation systems (OKR systems). Spatial structures are defined as sets of objects related with qualitative spatial relations. We focus on topological relations from the RCC-8 theory, their recognition on raster images, and their reification in an OKR system. Spatial structures and relations have been implemented and used in a knowledge-based system for satellite image interpretation

  14. Document clustering using graph based document representation with constraints

    OpenAIRE

    Rafi, Muhammad; Amin, Farnaz; Shaikh, Mohammad Shahid

    2014-01-01

    Document clustering is an unsupervised approach in which a large collection of documents (corpus) is subdivided into smaller, meaningful, identifiable, and verifiable sub-groups (clusters). Meaningful representation of documents and implicitly identifying the patterns, on which this separation is performed, is the challenging part of document clustering. We have proposed a document clustering technique using graph based document representation with constraints. A graph data structure can easi...

  15. 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...

  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. 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

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. DNA Sequence Representation and Comparison Based on Quaternion Number System

    Directory of Open Access Journals (Sweden)

    Hsuan-T. Chang

    2012-12-01

    Full Text Available Conventional schemes for DNA sequence representation, storage, and processing areusually developed based on the character-based formats.We propose the quaternion number system for numerical representation and further processing on DNA sequences.In the proposed method, the quaternion cross-correlation operation can be used to obtain both the global and local matching/mismatching information between two DNA sequences from the depicted one-dimensional curve and two-dimensional pattern, respectively.Simulation results on various DNA sequences and the comparison result with the wellknown BLAST method are obtained to verify the effectiveness of the proposed method.

  3. 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.

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

    Directory of Open Access Journals (Sweden)

    Baoxian Wang

    2015-10-01

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

  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. 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)

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. Survey of image-based representations and compression techniques

    OpenAIRE

    Shum, HY; Kang, SB; Chan, SC

    2003-01-01

    In this paper, we survey the techniques for image-based rendering (IBR) and for compressing image-based representations. Unlike traditional three-dimensional (3-D) computer graphics, in which 3-D geometry of the scene is known, IBR techniques render novel views directly from input images. IBR techniques can be classified into three categories according to how much geometric information is used: rendering without geometry, rendering with implicit geometry (i.e., correspondence), and rendering ...

  13. 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

  14. 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

  15. 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

  16. 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

  17. Action-Research and Food and Nutrition Security: A School Experience Mediated by Conceptual Graphic Representation Tool

    Science.gov (United States)

    Graebner, Ivete Teresinha; de Souza, Elizabeth Maria Tala; Saito, Carlos Hiroo

    2009-01-01

    This study deals with the development of a graphic representation tool as a way to support educational planning in an elementary school in the rural area of Brasilia (Brazil's capital), aiming at the implementation of an integrated action-research project focusing on hunger and nutrition. The graphic tool made it possible to promote…

  18. 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

  19. 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...

  20. 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...

  1. 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...

  2. Classification problems in object-based representation systems

    OpenAIRE

    Napoli, Amedeo

    1999-01-01

    Classification is a process that consists in two dual operations: generating a set of classes and then classifying given objects into the created classes. The class generation may be understood as a learning process and object classification as a problem-solving process. The goal of this position paper is to introduce and to make precise the notion of a classification problem in object-based representation systems, e.g. a query against a class hierarchy, to define a subsumption relation betwe...

  3. 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...

  4. Ontology-based topological representation of remote-sensing images

    OpenAIRE

    Oliva Santos, Rafael; Maciá Pérez, Francisco; Garea Llano, Eduardo

    2013-01-01

    This article proposes an ontology-based topological representation of remote-sensing images. Semantics, especially related to the topological relationships between the objects represented, are not explicit in remote-sensing images and this fact limits spatial analysis. Our aim is to provide an explicit ontological definition of the topological relations between objects in the image using the Quadtree data structure for spatial indexing. This structure is explicitly defined in an ontology allo...

  5. 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...

  6. 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.

  7. P-CNN: Pose-based CNN Features for Action Recognition

    OpenAIRE

    Chéron, Guilhem; Laptev, Ivan; Schmid, Cordelia

    2015-01-01

    This work targets human action recognition in video. While recent methods typically represent actions by statistics of local video features, here we argue for the importance of a representation derived from human pose. To this end we propose a new Pose-based Convolutional Neural Network descriptor (P-CNN) for action recognition. The descriptor aggregates motion and appearance information along tracks of human body parts. We investigate different schemes of temporal aggregation and experiment ...

  8. 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.

  9. 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.

  10. 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…

  11. 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.

  12. Loosely coupled web representations: a REST service and JavaScript wrapper for sharing web-based visual representations

    OpenAIRE

    Collins, Trevor; Quick, Kevin; Joiner, Richard; Littleton, Karen

    2013-01-01

    This paper presents the design and application of a web service architecture for providing shared access to web-based visual representations, such as dynamic models, simulations and visualizations. The Shared Representations (SR) system was created to facilitate the development of collaborative and co-operative learning activities over the web, and has been applied to provide shared group access to: a high-resolution image viewer, a virtual petrological microscope, and a forces and motion spr...

  13. 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

  14. Colour Texture Representation Based on Multivariate Bernoulli Mixtures

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Havlíček, Vojtěch; Grim, Jiří

    Los Alamitos : IEEE, 2010, s. 578-581. ISBN 978-1-4244-7166-9. [10th International Conference on Information Sciences, Signal Processing and their Applications. Kuala Lumpur (MY), 10.05.2010-13.05.2010] R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant ostatní: GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Texture modeling * Bernoulli mixture * EM algorithm Subject RIV: BD - Theory of Information http://library.utia.cas.cz/separaty/2010/RO/haindl-colour texture representation based on multivariate bernoulli mixtures.pdf

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    HangZhang

    2012-01-01

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

  17. Towards a Collection-Based Knowledge Representation: the Example of Geopolitical Crisis Management

    OpenAIRE

    Rousseaux, Pr. Francis; Lhoste, Kevin

    2010-01-01

    In this chapter we demonstrated that the concept of collection can be used as a knowledge representation and its implementation in IT can improve tools that were very difficult to implement in object-based knowledge representation. It appeared to be a good alternative to classical object-based knowledge representation.

  18. 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

  19. 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).

  20. 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.

  1. Grip Force Is Part of the Semantic Representation of Manual Action Verbs

    OpenAIRE

    Frak, Victor; Nazir, Tatjana,; Goyette, Michel; Cohen, Henri; Jeannerod, Marc

    2010-01-01

    Motor actions and action verbs activate similar cortical brain regions. A functional interference can be taken as evidence that there is a parallel treatment of these two types of information and would argue for the biological grounding of language in action. A novel approach examining the relationship between language and grip force is presented. With eyes closed and arm extended, subjects listened to words relating (verbs) or not relating (nouns) to a manual action while holding a cylinder ...

  2. 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…

  3. 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.

  4. 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

  5. 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.

  6. 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...

  7. Sparse representation based face recognition using weighted regions

    Science.gov (United States)

    Bilgazyev, Emil; Yeniaras, E.; Uyanik, I.; Unan, Mahmut; Leiss, E. L.

    2013-12-01

    Face recognition is a challenging research topic, especially when the training (gallery) and recognition (probe) images are acquired using different cameras under varying conditions. Even a small noise or occlusion in the images can compromise the accuracy of recognition. Lately, sparse encoding based classification algorithms gave promising results for such uncontrollable scenarios. In this paper, we introduce a novel methodology by modeling the sparse encoding with weighted patches to increase the robustness of face recognition even further. In the training phase, we define a mask (i.e., weight matrix) using a sparse representation selecting the facial regions, and in the recognition phase, we perform comparison on selected facial regions. The algorithm was evaluated both quantitatively and qualitatively using two comprehensive surveillance facial image databases, i.e., SCfaceandMFPV, with the results clearly superior to common state-of-the-art methodologies in different scenarios.

  8. 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...

  9. 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.

  10. 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...

  11. 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.

  12. Action-effect bindings and ideomotor learning in intention- and stimulus-based actions

    Directory of Open Access Journals (Sweden)

    ArvidHerwig

    2012-10-01

    Full Text Available According to ideomotor theory, action-effect associations are crucial for voluntary action control. Recently, a number of studies started to investigate the conditions that mediate the acquisition and application of action-effect associations by comparing actions carried out in response to exogenous stimuli (stimulus-based with actions selected endogenously (intention-based. There is evidence that the acquisition and/or application of action-effect associations is boosted when acting in an intention-based action mode. For instance, bidirectional action-effect associations were diagnosed in a forced choice test phase if participants previously experienced action-effect couplings in an intention-based but not in a stimulus-based action mode. The present study aims at investigating effects of the action mode on action-effect associations in more detail. In a series of experiments, we compared the strength and durability of short-term action-effect associations (binding immediately following intention- as well as stimulus-based actions. Moreover, long-term action-effect associations (learning were assessed in a subsequent test phase. Our results show short-term action-effect associations of equal strength and durability for both action modes. However, replicating previous results, long-term associations were observed only following intention-based actions. These findings indicate that the effect of the action mode on long-term associations cannot merely be a result of accumulated short-term action-effect bindings. Instead, only those episodic bindings are selectively perpetuated or retrieved that integrate action-relevant aspects of the processing event, i.e., in case of intention-based actions, the link between action and ensuing effect.

  13. 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...

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

    OpenAIRE

    Benioff, Paul

    2007-01-01

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

  15. 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.

  16. 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...

  17. 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

  18. 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.

  19. Agent-based conceptual model representation using BPMN

    OpenAIRE

    Onggo, Stephan; Karpat, Onder

    2011-01-01

    In a simulation project, a good conceptual model representation is critical for communicating conceptual models between stakeholders. A conceptual model describes the problem domain and model specifications. The description of the problem domain includes the objectives, inputs, outputs, content, assumptions and simplifications made in the model. The model specifications are used to specify the model’s behavior. This article focuses on the representation of the model content (structure, bounda...

  20. 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

  1. 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.

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

    Institute of Scientific and Technical Information of China (English)

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

    2008-01-01

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

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

    Science.gov (United States)

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

    1994-01-01

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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

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

    DEFF Research Database (Denmark)

    Srivastava, Shashank; Hovy, Dirk

    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....

  10. Half-quadratic-based iterative minimization for robust sparse representation.

    Science.gov (United States)

    He, Ran; Zheng, Wei-Shi; Tan, Tieniu; Sun, Zhenan

    2014-02-01

    Robust sparse representation has shown significant potential in solving challenging problems in computer vision such as biometrics and visual surveillance. Although several robust sparse models have been proposed and promising results have been obtained, they are either for error correction or for error detection, and learning a general framework that systematically unifies these two aspects and explores their relation is still an open problem. In this paper, we develop a half-quadratic (HQ) framework to solve the robust sparse representation problem. By defining different kinds of half-quadratic functions, the proposed HQ framework is applicable to performing both error correction and error detection. More specifically, by using the additive form of HQ, we propose an ℓ1-regularized error correction method by iteratively recovering corrupted data from errors incurred by noises and outliers; by using the multiplicative form of HQ, we propose an ℓ1-regularized error detection method by learning from uncorrupted data iteratively. We also show that the ℓ1-regularization solved by soft-thresholding function has a dual relationship to Huber M-estimator, which theoretically guarantees the performance of robust sparse representation in terms of M-estimation. Experiments on robust face recognition under severe occlusion and corruption validate our framework and findings. PMID:24356348

  11. Griwes: Generic Model and Preliminary Specifications for a Graph-Based Knowledge Representation Toolkit

    OpenAIRE

    Baget, Jean-François; Corby, Olivier; Dieng-Kuntz, Rose; Faron Zucker, Catherine; Gandon, Fabien; Giboin, Alain; Gutierrez, Alain; Leclère, Michel; Mugnier, Marie-Laure; Thomopoulos, Rallou

    2008-01-01

    Griwes is an initiative to develop a common model and an open-source freeware platform shared by different graph-based frameworks. We provide an overview of its objectives, architecture and specifications. We detail some of the basic mathematical structures that are used to characterize the primitives for graph-based knowledge representation. We then propose to factorize recurrent knowledge representation primitives that can be shared across specific graph-based languages and we provide a pro...

  12. Property-based sequence representations do not adequately encode local protein folding information.

    Science.gov (United States)

    Solis, A D; Rackovsky, S

    2007-06-01

    We examine the informatic characteristics of amino acid representations based on physical properties. We demonstrate that sequences rewritten using contracted alphabets based on physical properties do not encode local folding information well. The best four-character alphabet can only encode approximately 57% of the maximum possible amount of structural information. This result suggests that property-based representations that operate on a local length scale are not likely to be useful in homology searches and fold-recognition exercises. PMID:17387739

  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. A Study of Representations for Pen based Handwriting Recognition of Tamil Characters

    OpenAIRE

    Sundaresan, CS; Keerthi, SS

    1999-01-01

    In this paper we study the important issue of choosing representations that are suitable for recognizing pen based handwriting of characters in Tamil, a language of India. Four different choices, based on the following set of features are considered: (1) a sequence of directions and curvature; (2) a sequence of angles; (3) Fourier transform coefficients; and (4) wavelet features. We provide arguments in support of the representation using wavelet features. A neural network designed using thes...

  18. 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.

  19. 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.

  20. Action-Based Learning of Multistate Objects in the Medial Temporal Lobe.

    Science.gov (United States)

    Hindy, Nicholas C; Turk-Browne, Nicholas B

    2016-05-01

    Actions constrain perception by changing the appearance of objects in the environment. As such, they provide an interactive basis for learning the structure of visual input. If an action systematically transforms one stimulus into another, then these stimuli are more likely to reflect different states of the same persisting object over time. Here we show that such multistate objects are represented in the human medial temporal lobe-the result of a mechanism in which actions influence associative learning of how objects transition between states. We further demonstrate that greater recruitment of these action-based representations during object perception is accompanied by attenuated activity in stimulus-selective visual cortex. In this way, our interactions with the environment help build visual knowledge that predictively facilitates perceptual processing. PMID:25754517

  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. 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...

  4. Object-based Representation and Classification of Spatial Structures and Relations

    OpenAIRE

    Le Ber, Florence; Napoli, Amedeo

    2002-01-01

    This paper is concerned with the representation and the classification of spatial relations and structures in an object-based knowledge representation system. In this system, spatial structures are defined as sets of spatial entities connected with topological relations. Relations are represented by objects with their own properties. We propose to define two types of properties: the first ones are concerned with relations as concepts while the second are concerned with relations as links betw...

  5. Knowledge Representation meets DataBases for the sake of ontology-based data management

    OpenAIRE

    Goasdoué, François

    2012-01-01

    This Habilitation thesis outlines my research activities carried out as an Associate Professor at Univ. Paris-Sud and Inria Saclay Île-de-France. During this period, from 2003 to early 2012, my work was - and still is - at the interface between Knowledge Representation and Databases. I have mainly focused on ontology-based data management using the Semantic Web data models promoted by W3C: the Resource Description Framework (RDF) and the Web Ontology Language (OWL). In particular, my work has...

  6. ECA-RuleML: An Approach combining ECA Rules with temporal interval-based KR Event/Action Logics and Transactional Update Logics

    OpenAIRE

    Paschke, Adrian

    2006-01-01

    An important problem to be addressed within Event-Driven Architecture (EDA) is how to correctly and efficiently capture and process the event/action-based logic. This paper endeavors to bridge the gap between the Knowledge Representation (KR) approaches based on durable events/actions and such formalisms as event calculus, on one hand, and event-condition-action (ECA) reaction rules extending the approach of active databases that view events as instantaneous occurrences and/or sequences of ev...

  7. 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.

  8. 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.

  9. 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

  10. 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...

  11. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian; Paulson, Olaf B

    2002-01-01

    utilization (action knowledge). Here we show that the left ventral premotor cortex is activated during categorization of "both" fruit/vegetables and articles of clothing, relative to animals and nonmanipulable man-made objects. This observation suggests that action knowledge may not be important for the...... processing of man-made objects per se, but rather for the processing of manipulable objects in general, whether natural or man-made. These findings both support psycholinguistic theories suggesting that certain lexical categories may evolve from, and the act of categorization rely upon, motor-based knowledge...... of action equivalency, and have important implications for theories of category specificity. Thus, the finding that the processing of vegetables/fruit and articles of clothing give rise to similar activation is difficult to account for should knowledge representations in the brain be truly...

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

    DEFF Research Database (Denmark)

    Endelt, Line Ørtoft

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

  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. 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.

  15. 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

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

    DEFF Research Database (Denmark)

    Galle, Per

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

  17. 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...

  18. Classification of objects in images based on various object representations

    OpenAIRE

    Cichocki, Radoslaw

    2006-01-01

    Object recognition is a hugely researched domain that employs methods derived from mathematics, physics and biology. This thesis combines the approaches for object classification that base on two features – color and shape. Color is represented by color histograms and shape by skeletal graphs. Four hybrids are proposed which combine those approaches in different manners and the hybrids are then tested to find out which of them gives best results.

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

    Science.gov (United States)

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

    2015-05-01

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

  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. 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.

  3. 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.

  4. 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.

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

    Science.gov (United States)

    Koparan, Timur; Güven, Bülent

    2015-01-01

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

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

    OpenAIRE

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

    2007-01-01

    Miao, Y., Burgos, D., Griffiths, D., & Koper, R. (2008). Representation of Coordination Mechanisms in IMS Learning Design to Support Group-based Learning. In L. Lockyer, S. Bennet, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design and Learning Objects: Issues, Applications and Technologies (pp. 330-351). IDEA group.

  7. 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

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

    Energy Technology Data Exchange (ETDEWEB)

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Di Fonzo, F. [Rome Univ. `La Sapienza` (Italy). Dipt. Ingegneria; Burrascano, P. [Rome Univ. `La Sapienza` (Italy). Ist. di Elettronica

    1997-03-01

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

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

    Science.gov (United States)

    Ronda, Erlina

    2015-01-01

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

  10. 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...

  11. 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.

  12. 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...

  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. 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.

  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. 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

  18. 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.

  19. 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...

  20. Three knowledge representation formalisms for content-based manipulation of documents

    OpenAIRE

    Al Hulou, Rim; Corby, Olivier; Dieng-Kuntz, Rose; Euzenat, Jérôme; Ramirez, Carolina; Napoli, Amedeo; Troncy, Raphael

    2002-01-01

    Documents accessible from the web or from any document base constitute a significant source of knowledge as soon as the document contents can be represented in an appropriate form. This paper presents the ESCRIRE project, whose objective is to compare three knowledge representation (KR) formalisms, namely conceptual graphs, description logics and objects, for representing and manipulating document contents. The comparison relies on the definition of a pivot language based on XML, allowing the...

  1. 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

  2. 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.

  3. 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

  4. Registration-based Compensation using Sparse Representation in Conformal-array STAP

    CERN Document Server

    Sun, Ke; Wang, Xiqin

    2010-01-01

    Space-time adaptive processing (STAP) is a well-suited technique to detect slow-moving targets in the presence of a clutter-spreading environment. When considering the STAP system deployed with conformal radar array (CFA), the training data is range-dependent, which results in poor detection performance of statistical-based algorithms. In this paper, we propose registration-based compensation using sparse representation (SR-RBC) to generate stationary training data. This method first converts the estimation of both the unknown configuration parameters and clutter power distribution into an ill-posed problem with the constraint of sparsity, and then utilizes the technique of sparse representation like iterative reweighted least squares (IRLS) to solve it. Based on this, the transform matrix is designed so that the processed training data behaves nearly stationary with the test cell. Since the configuration parameters as well as the clutter spectral response is obtained with full-snapshot using sparse represent...

  5. 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

  6. 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.

  7. 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.

  8. Separated representations and PGD-based model reduction fundamentals and applications

    CERN Document Server

    Ladevèze, Pierre

    2014-01-01

    The papers in this volume start with a description of  the construction of reduced models through a review of Proper Orthogonal Decomposition (POD) and reduced basis models, including their mathematical foundations and some challenging applications, then followed by a description of a  new generation of simulation strategies based on the use of separated representations (space-parameters, space-time, space-time-parameters, space-space,…), which have led to what is known as Proper Generalized Decomposition (PGD) techniques. The models can be enriched by treating parameters as additional coordinates, leading to fast and inexpensive online calculations based on richer offline parametric solutions. Separated representations are analyzed in detail in the course, from their mathematical foundations to their most spectacular applications. It is also shown how such an approximation could evolve into a new paradigm in computational science, enabling one to circumvent various computational issues in a vast array of...

  9. 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.

  10. 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...

  11. 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...

  12. Building Viewpoints in an Object-Based Representation System for Knowledge Discovery in Databases

    OpenAIRE

    Simon, Arnaud; Napoli, Amedeo

    1999-01-01

    In this paper, we present an approach to knowledge discovery in databases in the context of object-based representation systems. The goal of this approach is to extract viewpoints and association rules from data represented by objects. A viewpoint is a hierarchy of classes (a kind of partial lattice) and an association rule can be defined within a viewpoint or between two classes lying in different viewpoints. The viewpoints construction algorithm allows to manipulate objects which are indiff...

  13. 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...

  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. Object-based representation and analysis of light and electron microscopic volume data using Blender

    OpenAIRE

    Asadulina, Albina; Conzelmann, Markus; Williams, Elizabeth A; Panzera, Aurora; Jékely, Gáspár

    2015-01-01

    Background Rapid improvements in light and electron microscopy imaging techniques and the development of 3D anatomical atlases necessitate new approaches for the visualization and analysis of image data. Pixel-based representations of raw light microscopy data suffer from limitations in the number of channels that can be visualized simultaneously. Complex electron microscopic reconstructions from large tissue volumes are also challenging to visualize and analyze. Results Here we exploit the a...

  16. 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.

  17. Quantum algebra uq(3). Transformation brackets, connecting the canonical T, U and V bases of the irreducible representation

    International Nuclear Information System (INIS)

    General analytical expression for the transformation brackets, connecting three canonical T, U and V bases of the uq(3) irreducible representation are derived. As an illustration these transformation brackets are calculated for the case of the irreducible representation with Young scheme (f)=(200). 16 refs

  18. 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...

  19. 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.

  20. Verification of Inconsistency-Aware Knowledge and Action Bases

    OpenAIRE

    Diego Calvanese; Evgeny Kharlamov; Marco Montali; Ario Santoso; Dmitriy Zheleznyakov

    2013-01-01

    Description Logic Knowledge and Action Bases (KABs) have been recently introduced as a mech- anism that provides a semantically rich represen- tation of the information on the domain of inter- est in terms of a DL KB and a set of actions to change such information over time, possibly intro- ducing new objects. In this setting, decidability of verification of sophisticated temporal properties over KABs, expressed in a variant of first-order μ- calculus, has been shown. However, the established...

  1. 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.

  2. Ontology-based time information representation of vaccine adverse events in VAERS for temporal analysis

    Directory of Open Access Journals (Sweden)

    Tao Cui

    2012-12-01

    Full Text Available Abstract Background The U.S. FDA/CDC Vaccine Adverse Event Reporting System (VAERS provides a valuable data source for post-vaccination adverse event analyses. The structured data in the system has been widely used, but the information in the write-up narratives is rarely included in these kinds of analyses. In fact, the unstructured nature of the narratives makes the data embedded in them difficult to be used for any further studies. Results We developed an ontology-based approach to represent the data in the narratives in a “machine-understandable” way, so that it can be easily queried and further analyzed. Our focus is the time aspect in the data for time trending analysis. The Time Event Ontology (TEO, Ontology of Adverse Events (OAE, and Vaccine Ontology (VO are leveraged for the semantic representation of this purpose. A VAERS case report is presented as a use case for the ontological representations. The advantages of using our ontology-based Semantic web representation and data analysis are emphasized. Conclusions We believe that representing both the structured data and the data from write-up narratives in an integrated, unified, and “machine-understandable” way can improve research for vaccine safety analyses, causality assessments, and retrospective studies.

  3. 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.

  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. 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.

  6. 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.

  7. Constructing visual representations

    DEFF Research Database (Denmark)

    Huron, Samuel; Jansen, Yvonne; Carpendale, Sheelagh

    2014-01-01

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

  8. Sorting of Single Biomolecules based on Fourier Polar Representation of Surface Enhanced Raman Spectra

    Science.gov (United States)

    Leray, Aymeric; Brulé, Thibault; Buret, Mickael; Colas Des Francs, Gérard; Bouhelier, Alexandre; Dereux, Alain; Finot, Eric

    2016-02-01

    Surface enhanced Raman scattering (SERS) spectroscopy becomes increasingly used in biosensors for its capacity to detect and identify single molecules. In practice, a large number of SERS spectra are acquired and reliable ranking methods are thus essential for analysing all these data. Supervised classification strategies, which are the most effective methods, are usually applied but they require pre-determined models or classes. In this work, we propose to sort SERS spectra in unknown groups with an alternative strategy called Fourier polar representation. This non-fitting method based on simple Fourier sine and cosine transforms produces a fast and graphical representation for sorting SERS spectra with quantitative information. The reliability of this method was first investigated theoretically and numerically. Then, its performances were tested on two concrete biological examples: first with single amino-acid molecule (cysteine) and then with a mixture of three distinct odorous molecules. The benefits of this Fourier polar representation were highlighted and compared to the well-established statistical principal component analysis method.

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

    International Nuclear Information System (INIS)

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

  10. 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

  11. 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.

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

    Science.gov (United States)

    Howarth, Caroline; Foster, Juliet; Dorrer, Nike

    2004-03-01

    This article seeks to demonstrate the importance of developing a dialogue between social representations theory and community approaches to researching issues of health. We show how we have used the theory within our own research to ground our findings at the level of community. The article is divided into three sections: the recognition of competing systems of knowledge; the role of representations in maintaining stigmatizing practices; and the impact of representations on identities. Each section is illustrated with material drawn from Foster's research on mental illness and Dorrer's research on women's representations of healthy eating. We conclude by arguing that, while social representations theory is a valuable tool for community-based health research, the theory would benefit from developing a more participatory methodology. PMID:15018725

  13. A framework for knowledge acquisition, representation and problem-solving in knowledge-based planning

    Science.gov (United States)

    Martinez-Bermudez, Iliana

    This research addresses the problem of developing planning knowledge-based applications. In particular, it is concerned with the problems of knowledge acquisition and representation---the issues that remain an impediment to the development of large-scale, knowledge-based planning applications. This work aims to develop a model of planning problem solving that facilitates expert knowledge elicitation and also supports effective problem solving. Achieving this goal requires determining the types of knowledge used by planning experts, the structure of this knowledge, and the problem-solving process that results in the plan. While answering these questions it became clear that the knowledge structure, as well as the process of problem solving, largely depends on the knowledge available to the expert. This dissertation proposes classification of planning problems based on their use of expert knowledge. Such classification can help in the selection of the appropriate planning method when dealing with a specific planning problem. The research concentrates on one of the identified classes of planning problems that can be characterized by well-defined and well-structured problem-solving knowledge. To achieve a more complete knowledge representation architecture for such problems, this work employs the task-specific approach to problem solving. The result of this endeavor is a task-specific methodology that allows the representation and use of planning knowledge in a structural, consistent manner specific to the domain of the application. The shell for building a knowledge-based planning application was created as a proof of concept for the methodology described in this dissertation. This shell enabled the development of a system for manufacturing planning---COMPLAN. COMPLAN encompasses knowledge related to four generic techniques used in composite material manufacturing and, given the description of the composite part, creates a family of plans capable of producing it.

  14. 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

  15. Method for 3D Rendering Based on Intersection Image Display Which Allows Representation of Internal Structure of 3D objects

    OpenAIRE

    Kohei Arai

    2013-01-01

    Method for 3D rendering based on intersection image display which allows representation of internal structure is proposed. The proposed method is essentially different from the conventional volume rendering based on solid model which allows representation of just surface of the 3D objects. By using afterimage, internal structure can be displayed through exchanging the intersection images with internal structure for the proposed method. Through experiments with CT scan images, the proposed met...

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Antoni Ligeza

    2001-01-01

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

  18. 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.

  19. 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...

  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.

    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

  2. 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.

  3. 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.

  4. 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...

  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. 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...

  7. 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…

  8. 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

  9. 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.

  10. 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.

  11. [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

  12. 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

  13. 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.

  14. 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...

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

    International Nuclear Information System (INIS)

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

  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. 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...

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Action recognition based on a selective sampling strategy for real-time video surveillance

    Science.gov (United States)

    Zhang, Bo; Zhang, Hong; Yuan, Ding

    2015-12-01

    Action recognition is a very challenging task in the field of real-time video surveillance. The traditional models on action recognition are constructed of Spatial-temporal features and Bag-of-Feature representations. Based on this model, current research work tends to introduce dense sampling to achieve better performance. However, such approaches are computationally intractable when dealing with large video dataset. Hence, there are some recent works focused on feature reduction to speed up the algorithm without reducing accuracy. In this paper, we proposed a novel selective feature sampling strategy on action recognition. Firstly, the optical flow field is estimated throughout the input video. And then the sparse FAST (Features from Accelerated Segment Test) points are selected within the motion regions detected by using the optical flows on the temporally down-sampled image sequences. The selective features, sparse FAST points, are the seeds to generate the 3D patches. Consequently, the simplified LPM (Local Part Model) which greatly speeds up the model is formed via 3D patches. Moreover, MBHs (Motion Boundary Histograms) calculated by optical flows are also adopted in the framework to further improve the efficiency. Experimental results on UCF50 dataset and our artificial dataset show that our method could reach more real-time effect and achieve a higher accuracy compared with the other competitive methods published recently.

  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. 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

  5. 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

  6. 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.

  7. COM3/369: Knowledge-based Information Systems: A new approach for the representation and retrieval of medical information

    OpenAIRE

    Mann, G.; Birkmann, C; Schmidt, T; Schaeffler, V

    1999-01-01

    Introduction Present solutions for the representation and retrieval of medical information from online sources are not very satisfying. Either the retrieval process lacks of precision and completeness the representation does not support the update and maintenance of the represented information. Most efforts are currently put into improving the combination of search engines and HTML based documents. However, due to the current shortcomings of methods for natural language understanding there ar...

  8. 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.

  9. 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.

  10. 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

  11. 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)

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

    International Nuclear Information System (INIS)

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

  13. 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.

  14. 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.

  15. Wavelet-based multifractal analysis of DNA sequences by using chaos-game representation

    International Nuclear Information System (INIS)

    Chaos game representation (CGR) is proposed as a scale-independent representation for DNA sequences and provides information about the statistical distribution of oligonucleotides in a DNA sequence. CGR images of DNA sequences represent some kinds of fractal patterns, but the common multifractal analysis based on the box counting method cannot deal with CGR images perfectly. Here, the wavelet transform modulus maxima (WTMM) method is applied to the multifractal analysis of CGR images. The results show that the scale-invariance range of CGR edge images can be extended to three orders of magnitude, and complete singularity spectra can be calculated. Spectrum parameters such as the singularity spectrum span are extracted to describe the statistical character of DNA sequences. Compared with the singularity spectrum span, exon sequences with a minimal spectrum span have the most uniform fractal structure. Also, the singularity spectrum parameters are related to oligonucleotide length, sequence component and species, thereby providing a method of studying the length polymorphism of repeat oligonucleotides. (general)

  16. 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

  17. Improving low-dose cardiac CT images using 3D sparse representation based processing

    Science.gov (United States)

    Shi, Luyao; Chen, Yang; Luo, Limin

    2015-03-01

    Cardiac computed tomography (CCT) has been widely used in diagnoses of coronary artery diseases due to the continuously improving temporal and spatial resolution. When helical CT with a lower pitch scanning mode is used, the effective radiation dose can be significant when compared to other radiological exams. Many methods have been developed to reduce radiation dose in coronary CT exams including high pitch scans using dual source CT scanners and step-and-shot scanning mode for both single source and dual source CT scanners. Additionally, software methods have also been proposed to reduce noise in the reconstructed CT images and thus offering the opportunity to reduce radiation dose while maintaining the desired diagnostic performance of a certain imaging task. In this paper, we propose that low-dose scans should be considered in order to avoid the harm from accumulating unnecessary X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. Accordingly, in this paper, a 3D dictionary representation based image processing method is proposed to reduce CT image noise. Information on both spatial and temporal structure continuity is utilized in sparse representation to improve the performance of the image processing method. Clinical cases were used to validate the proposed method.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. Gestalt-Based Action Segmentation for Robot Task Learning

    OpenAIRE

    Pardowitz, Michael; Haschke, Robert; Steil, Jochen J.; Ritter, Helge

    2008-01-01

    In Programming by Demonstration (PbD) systems, the problem of task segmentation and task decomposition has not been addressed with satisfactory attention. In this article we propose a method relying on psychological gestalt theories originally developed for visual perception and apply it to the domain of action segmentation. We propose a computational model for gestalt-based segmentation called Competitive Layer Model (CLM). The CLM relies on features mutually supporting or inhibiting each ot...

  3. 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

  4. 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.

  5. 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

  6. 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...

  7. Comparative analysis of bacterial essential and nonessential genes with Hurst exponent based on chaos game representation

    International Nuclear Information System (INIS)

    Essential genes are indispensable for the survival of an organism. Investigating features associated with gene essentiality is fundamental to the prediction and identification of essential genes with computational techniques. We use fractal theory approach to make comparative analysis of essential and nonessential genes in bacteria. The Hurst exponents of essential genes and nonessential genes available in the DEG database for 27 bacteria are calculated based on their gene chaos game representations. It is found that for most analyzed bacteria, weak negative correlation exists between Hurst exponent and gene length. Moreover, essential genes generally differ from nonessential genes in their Hurst exponent. For genes of similar length, the average Hurst exponent of essential genes is smaller than that of nonessential genes. The results of our work reveal that gene Hurst exponent is very probably useful gene feature for the algorithm predicting essential genes

  8. 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.

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

    Science.gov (United States)

    Li, Kang; Yu, Juebang; Li, Jian

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

  10. 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

  11. 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.

  12. Random laser action from flexible biocellulose-based device

    Science.gov (United States)

    dos Santos, Molíria V.; Dominguez, Christian T.; Schiavon, João V.; Barud, Hernane S.; de Melo, Luciana S. A.; Ribeiro, Sidney J. L.; Gomes, Anderson S. L.; de Araújo, Cid B.

    2014-02-01

    We demonstrate random lasing action in flexible bacterial cellulose (BC) membrane containing a laser-dye and either dielectric or metallic nanoparticles (NPs). The novel random laser system consists of BC nanofibers attached with Rhodamine 6G molecules and having incorporated either silica or silver NPs. The laser action was obtained by excitation of the samples with a 6 ns pulsed laser at 532 nm. Minimum laser threshold of ≈0.7 mJ/pulse was measured for the samples with silica NPs, whereas a laser threshold of 2.5 mJ/pulse for a system based on silver NPs was obtained. In both cases a linewidth narrowing from ≈50 to ≈4 nm was observed. Potential applications in biophotonics and life sciences are discussed for this proof-of-concept device.

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

    Science.gov (United States)

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

    2014-01-01

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

  14. 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.

  15. 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.

  16. Poetic representation

    DEFF Research Database (Denmark)

    Wulf-Andersen, Trine Østergaard

    2012-01-01

    This article is based on a Danish research project with young people in vulnerable positions. Young people are involved throughout the research process, including the interpretation of material produced through interviews, and discussions on how reflections and conclusions from the research should...... 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...... participative social work research. The article moves to ‘trouble’ understandings of participative research as egalitarian and consensus-driven, and proposes a focus on the tensions and positioning of knowledge production....

  17. 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.

  18. 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

  19. 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

  20. 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…

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    Radovanović Bojana

    2014-01-01

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

  3. 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.

  4. 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.

  5. Building the knowledge base for environmental action and sustainability

    DEFF Research Database (Denmark)

    2015-01-01

    was “Building the knowledge base for environmental action and sustainability”. The joint conference was designed to facilitate ‘within‐the‐domain’, as well as to create a space for developing synergies between the two communities. Altogether 125 research and applied papers (including extended abstracts) from 42......‐Packard Joseph Kava, Vice President ‐ Data Centers, Google, California   Special thanks to Tania Nielsen who has acted as key person for all organisational matters, including contact point for speakers and participants and for the publication of the Conference Proceedings and Adjunct Proceedings. Thanks...

  6. 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...

  7. 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...

  8. 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.

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

    Science.gov (United States)

    Liu, Bin; Wang, Shanyi; Wang, Xiaolong

    2015-10-01

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

  10. 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

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

    Directory of Open Access Journals (Sweden)

    Pasi Nieminen

    2010-08-01

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

  12. A ranklet-based image representation for mass classification in digital mammograms

    International Nuclear Information System (INIS)

    Regions of interest (ROIs) found on breast radiographic images are classified as either tumoral mass or normal tissue by means of a support vector machine classifier. Classification features are the coefficients resulting from the specific image representation used to encode each ROI. Pixel and wavelet image representations have already been discussed in one of our previous works. To investigate the possibility of improving classification performances, a novel nonparametric, orientation-selective, and multiresolution image representation is developed and evaluated, namely a ranklet image representation. A dataset consisting of 1000 ROIs representing biopsy-proven tumoral masses (either benign or malignant) and 5000 ROIs representing normal breast tissue is used. ROIs are extracted from the digital database for screening mammography collected by the University of South Florida. Classification performances are evaluated using the area Az under the receiver operating characteristic curve. By achieving Az values of 0.978±0.003 and 90% sensitivity with a false positive fraction value of 4.5%, experiments demonstrate classification results higher than those reached by the previous image representations. In particular, the improvement on the Az value over that achieved by the wavelet image representation is statistically relevant with the two-tailed p value <0.0001. Besides, owing to the tolerance that the ranklet image representation reveals to variations in the ROIs' gray-level intensity histogram, this approach discloses to be robust also when tested on radiographic images having gray-level intensity histogram remarkably different from that used for training

  13. 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.

  14. 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.

  15. Hydrologic effects of evapotranspiration representation in a Richards equation based distributed hydrologic model at the catchment scale

    Science.gov (United States)

    Cristea, N. C.; Burges, S. J.

    2013-12-01

    Evapotranspiration (ET) is a key water budget term that is rarely evaluated in hydrologic modeling due to the scarcity of observed actual ET fluxes. However, the ET process representation within a hydrologic model is important as it affects the simulated hydrologic response. Here we illustrate how different ET representations affect both the hydrograph and the soil moisture states within MODHMS, a Richards' equation based distributed hydrologic model at the catchment scale. MODHMS, a MODFLOW based model, has a flexible modular structure that allowed testing of 4 different base case ET scenarios: two MODFLOW ET representations (linear and piece-wise linear) and one physically based ET model in two configurations. These 4 ET sub-models were applied sequentially for the case of the well-studied 10.5 ha - Tarrawarra catchment in Australia keeping the soil parameterization constant. The hydrologic response sensitivity to each of the ET sub-models parameterization was evaluated. The ET process representation chosen for use in MODHMS is important for adequately representing soil saturation areas, lateral flow and drying of the upslope areas of the catchment as well as the outflow hydrograph.

  16. 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…

  17. 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…

  18. Map-based model of the cardiac action potential

    International Nuclear Information System (INIS)

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

  19. 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...

  20. Few group cross section representation based on sparse grid methods / Danniëll Botes

    OpenAIRE

    Botes, Danniëll

    2012-01-01

    This thesis addresses the problem of representing few group, homogenised neutron cross sections as a function of state parameters (e.g. burn-up, fuel and moderator temperature, etc.) that describe the conditions in the reactor. The problem is multi-dimensional and the cross section samples, required for building the representation, are the result of expensive transport calculations. At the same time, practical applications require high accuracy. The representation method must therefore be eff...

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

    International Nuclear Information System (INIS)

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

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

    International Nuclear Information System (INIS)

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

  3. 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.

  4. 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.

  5. Signal representation on the angular Poincaré sphere, based on second-order moments.

    Science.gov (United States)

    Bastiaans, Martin J; Alieva, Tatiana

    2010-04-01

    Based on the analysis of second-order moments, a generalized canonical representation of a two-dimensional optical signal is proposed, which is associated with the angular Poincaré sphere. Vortex-free (or zero-twist) optical beams arise on the equator of this sphere, while beams with a maximum vorticity (or maximum twist) are located at the poles. An easy way is shown how the latitude on the sphere, which is a measure for the degree of vorticity, can be derived from the second-order moments. The latitude is invariant when the beam propagates through a first-order optical system between conjugate planes. To change the vorticity of a beam, a system that does not operate between conjugate planes is needed, with the gyrator as the prime representative of such a system. A direct way is derived to find an optical system (consisting of a lens, a magnifier, a rotator, and a gyrator) that transforms a beam with an arbitrary moment matrix into its canonical form. PMID:20360834

  6. Robust classification for occluded ear via Gabor scale feature-based non-negative sparse representation

    Science.gov (United States)

    Zhang, Baoqing; Mu, Zhichun; Li, Chen; Zeng, Hui

    2014-06-01

    The Gabor wavelets have been experimentally verified to be a good approximation to the response of cortical neurons. A new feature extraction approach is investigated for ear recognition by using scale information of Gabor wavelets. The proposed Gabor scale feature conforms to human visual perception of objects from far to near. It can not only avoid too much redundancy in Gabor features but also tends to extract more precise structural information that is robust to image variations. Then, Gabor scale feature-based non-negative sparse representation classification (G-NSRC) is proposed for ear recognition under occlusion. Compared with SRC in which the sparse coding coefficients can be negative, the non-negativity of G-NSRC conforms to the intuitive notion of combing parts to form a whole and therefore is more consistent with the biological modeling of visual data. Additionally, the use of Gabor scale features increases the discriminative power of G-NSRC. Finally, the proposed classification paradigm is applied to occluded ear recognition. Experimental results demonstrate the effectiveness of our proposed algorithm. Especially when the ear is occluded, the proposed algorithm exhibits great robustness and achieves state-of-the-art recognition performance.

  7. 3D face recognition based on multiple keypoint descriptors and sparse representation.

    Science.gov (United States)

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

    2014-01-01

    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. PMID:24940876

  8. 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.

  9. 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...

  10. 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.

  11. 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

  12. 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...

  13. 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.

  14. 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

  15. 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

  16. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-01-01

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

  18. A method of SRS representation based on the finite state machine

    International Nuclear Information System (INIS)

    If a finite number of states and transitions between the states are figured out from a system, the system can be represented with the finite state machine so that is behavior can be interpreted more consistently than the representation with natural language. The software requirement specification for alarm display of the information processing system for SMART represented with the finite state machine is presented in this paper. The specification was easily understood by a software programmer than that of natural language. Even if the requriements of the alarm display are extended more, to show that the representation method of software requirement specification is still useful is remained in further study

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

    OpenAIRE

    Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman; Anbarjafari, Gholamreza; Baro, Xavier; J. Escalante, Hugo; Moeslund, Thomas B.

    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 and cameras, people are pictured very small and hence challenge action recognition algorithms. Simple upsampling methods, like bicubic interpolation, cannot retrieve all the detailed information that...

  20. 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.

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

    OpenAIRE

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

    2016-01-01

    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 (...

  2. Method for 3D Rendering Based on Intersection Image Display Which Allows Representation of Internal Structure of 3D objects

    Directory of Open Access Journals (Sweden)

    Kohei Arai

    2013-06-01

    Full Text Available Method for 3D rendering based on intersection image display which allows representation of internal structure is proposed. The proposed method is essentially different from the conventional volume rendering based on solid model which allows representation of just surface of the 3D objects. By using afterimage, internal structure can be displayed through exchanging the intersection images with internal structure for the proposed method. Through experiments with CT scan images, the proposed method is validated. Also one of other applicable areas of the proposed for design of 3D pattern of Large Scale Integrated Circuit: LSI is introduced. Layered patterns of LSI can be displayed and switched by using human eyes only. It is confirmed that the time required for displaying layer pattern and switching the pattern to the other layer by using human eyes only is much faster than that using hands and fingers.

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

    Science.gov (United States)

    Ziegler, Benjamin; Rauhut, Guntram

    2016-03-01

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

  4. 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.

  5. 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…

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

    Directory of Open Access Journals (Sweden)

    Fei Yan

    2014-10-01

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

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

    Science.gov (United States)

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

    2010-01-01

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

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

    NARCIS (Netherlands)

    Psyllidis, A.

    2015-01-01

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

  9. 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.

  10. 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

  11. 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...

  12. 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...

  13. 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)

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

    Science.gov (United States)

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

    1998-01-01

    Medicine is increasingly image-intensive. The central importance of imaging technologies such as computerized tomography and magnetic resonance imaging in clinical decision making, combined with the trend to store many "traditional" clinical images such as conventional radiographs, microscopic pathology and dermatology images in digital format present both challenges and an opportunities for the designers of clinical information systems. The emergence of Multimedia Electronic Medical Record Systems (MEMRS), architectures that integrate medical images with text-based clinical data, will further hasten this trend. The development of these systems, storing a large and diverse set of medical images, suggests that in the future MEMRS will become important digital libraries supporting patient care, research and education. The representation and retrieval of clinical images within these systems is problematic as conventional database architectures and information retrieval models have, until recently, focused largely on text-based data. Medical imaging data differs in many ways from text-based medical data but perhaps the most important difference is that the information contained within imaging data is fundamentally knowledge-based. New representational and retrieval models for clinical images will be required to address this issue. Within the Image Engine multimedia medical record system project at the University of Pittsburgh we are evolving an approach to representation and retrieval of medical images which combines semantic indexing using the UMLS Metathesuarus, image content-based representation and knowledge-based image analysis. PMID:9929345

  15. 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

  16. Evaluating a problem based learning course: an action research study.

    Science.gov (United States)

    Walker, J; Bailey, S; Brasell-Brian, R; Gould, S

    2001-03-01

    Problem based learning (PBL) has been widely used in the United States, United Kingdom and Australasia in undergraduate nursing education to develop critical thinking and problem solving skills. PBL has been used since 1996 in a Bachelor of Nursing course at a New Zealand tertiary institution, and several modifications have been made to foster effective learning. The 'pure' PBL process has been adapted to move students gradually from teacher direction to taking responsibility for their learning. This has provided the opportunity for students to develop critical thinking, problem solving, information retrieval and evaluation skills, and group process skills over an 18-week period. Because rigorous evaluation of these changes had not been formally undertaken, the purpose of this study was to evaluate how the current format was developing students' understanding and integration of knowledge. Two cycles of the action research method (Cardno and Piggot-Irvine, 1994) were used, involving 4 lecturers and 17 students. Data was collected both quantitatively and qualitatively over a 16-week period. Findings indicated the importance of: explaining the purpose and process of PBL; communicating in detail the role of both students and lecturers; keeping communication lines open; addressing timetabling issues and valuing this method of learning for nursing practice. Implications for nursing education are addressed. PMID:11855017

  17. Representational Thickness

    DEFF Research Database (Denmark)

    Mullins, Michael

    be implemented to improve design conditions for architects, thereby increasing the “thickness of representation”. The study commences from a broader theoretical enquiry, a review of previous research and examples of relevant context in which virtual reality has been used in practice. It develops from......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...

  18. 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…

  19. 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

  20. 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.

  1. 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.

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

    International Nuclear Information System (INIS)

    This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group GNC, which is the three fold central extension of the Abelian group of ℝ4. These representations have been exhaustively studied in earlier papers. The group GNC is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only

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

    Science.gov (United States)

    Chowdhury, S. Hasibul Hassan; Ali, S. Twareque

    2015-12-01

    This paper is devoted to the construction and analysis of the Wigner functions for noncommutative quantum mechanics, their marginal distributions, and star-products, following a technique developed earlier, viz, using the unitary irreducible representations of the group GNC, which is the three fold central extension of the Abelian group of ℝ4. These representations have been exhaustively studied in earlier papers. The group GNC is identified with the kinematical symmetry group of noncommutative quantum mechanics of a system with two degrees of freedom. The Wigner functions studied here reflect different levels of non-commutativity—both the operators of position and those of momentum not commuting, the position operators not commuting and finally, the case of standard quantum mechanics, obeying the canonical commutation relations only.

  4. 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...

  5. 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...

  6. 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.

  7. 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

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

    OpenAIRE

    Hossien Pourghassem; Hassan Ghasemian

    2011-01-01

    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 feedba...

  9. 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.

  10. 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

  11. 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...

  12. 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...

  13. 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.

  14. 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

  15. Weakly Supervised Fine-Grained Categorization With Part-Based Image Representation

    Science.gov (United States)

    Zhang, Yu; Wei, Xiu-Shen; Wu, Jianxin; Cai, Jianfei; Lu, Jiangbo; Nguyen, Viet-Anh; Do, Minh N.

    2016-04-01

    In this paper, we categorize fine-grained images without using any object / part annotation neither in the training nor in the testing stage, a step towards making it suitable for deployments. Fine-grained image categorization aims to classify objects with subtle distinctions. Most existing works heavily rely on object / part detectors to build the correspondence between object parts by using object or object part annotations inside training images. The need for expensive object annotations prevents the wide usage of these methods. Instead, we propose to select useful parts from multi-scale part proposals in objects, and use them to compute a global image representation for categorization. This is specially designed for the annotation-free fine-grained categorization task, because useful parts have shown to play an important role in existing annotation-dependent works but accurate part detectors can be hardly acquired. With the proposed image representation, we can further detect and visualize the key (most discriminative) parts in objects of different classes. In the experiment, the proposed annotation-free method achieves better accuracy than that of state-of-the-art annotation-free and most existing annotation-dependent methods on two challenging datasets, which shows that it is not always necessary to use accurate object / part annotations in fine-grained image categorization.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-10-14

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

  17. 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.

  18. 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.

  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. 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,…

  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. 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

  3. A unified approach to constitutive equations of inelasticity based on tensor function representations

    International Nuclear Information System (INIS)

    The applicability of the tensor function theory to the development of elaborate and rational constitutive equations of inelasticity is discussed to facilitate the description of the complicated inelastic response of structural components. After a brief review of the representation theory of scalar-valued as well as tensor-valued functions of a set of vector and tensor variables, previous results in this line of approach are first presented. Then, the formulation of some non-classical constitutive equations of inelasticity is discussed in some detail to elucidate the utility and the practical procedures of this theory; a yield criterion and a non-associated flow law of prestrained plastic materials, those of transversely isotropic materials, isotropic and anisotropic hardening theories of creep, and a constitutive equation of anisotropic creep damage in metals. It is shown that the present approach provides the general framework to materialize accurate constitutive equations of inelasticity. (orig.)

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. Rethinking actions: implementation and association.

    Science.gov (United States)

    Quandt, Lorna C; Chatterjee, Anjan

    2015-01-01

    Action processing allows us to move through and interact with the world, as well as understand the movements performed by other people. In recent years, there has been increasing interest in the semantics of actions as differentiated from the semantics of objects. However, as the understanding of action semantics has evolved, it is evident that the existing literature conflates two senses of the word 'action'-one that stems from studies of tool use and the other from event representation. In this paper, we suggest that this issue can be clarified by closely examining differences in how the human parietal and temporal cortices of the brain process action-related stimuli. By contrasting the posterior parietal cortex to the posterolateral temporal cortex, we characterize two complementary action systems in the human brain, each with its own specialization of function. We suggest that these two systems be referred to as the parietal Action Implementation System, and the posterolateral temporal Action Association System. While the frontoparietal system is concerned primarily with how we perform actions, and simulate others' actions, the temporal action system is more involved with processing actions from a third-person, conceptual standpoint. Recent work in cognitive neuroscience of perception and language, as well as the neuroanatomical organization of these brain regions support this distinction. We will discuss the implications of this work for cognition-, language-, and neuroscience-based action research. PMID:26352170

  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. 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...

  12. 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...

  13. 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.

  14. 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...

  15. Community based intervention on adolescent risk taking: using research for community action

    OpenAIRE

    Coggan, C.; Disley, B.; P Patterson

    1998-01-01

    Design—Case study, based on a community action model and formative evaluation. This involved: a community profile on adolescent risk taking behaviour; interviews with service providers; dissemination of research findings to local policy makers; development and implementation of a community action plan to address adolescent risk taking; and assessment of its impact.

  16. 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.

  17. Representation of Stormflow and a More Responsive Water Table in a TOPMODEL-Based Hydrology Model

    Science.gov (United States)

    Shaman, Jeffrey; Stieglitz, Marc; Engel, Victor; Koster, Randal; Stark, Colin; Houser, Paul R. (Technical Monitor)

    2001-01-01

    This study presents two new modeling strategies. First, a methodology for representing the physical process of stormflow within a TOPMODEL framework is developed. In using this approach, discharge at quickflow time scales is simulated and a fuller depiction of hydrologic activity is brought about. Discharge of water from the vadose zone is permitted in a physically realistic manner without a priori assumption of the level within the soil column at which stormflow saturation can take place. Determination of the stormflow contribution to discharge is made using the equation for groundwater flow. No new parameters are needed. Instead, regions of near saturation that develop during storm events, producing vertical recharge, are allowed to contribute to soil column discharge. These stormflow contributions to river runoff, as for groundwater flow contributions, are a function of catchment topography and local hydraulic conductivity at the depth of these regions of near saturation. The second approach improves groundwater flow response through a reduction of porosity and field capacity with depth in the soil column. Large storm events are better captured and a more dynamic water table develops with application of this modified soil column profile (MSCP). The MSCP predominantly reflects soil depth differences in upland and lowland regions of a watershed. Combined, these two approaches - stormflow and the MSCP - provide a more accurate representation of the time scales at which soil column discharge responds and a more complete depiction of hydrologic activity. Storm events large and small are better simulated, and some of the biases previously evident in TOPMODEL simulations are reduced.

  18. 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.

  19. 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

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    Zutao Zhang

    2016-02-01

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

  2. Group representations

    CERN Document Server

    Karpilovsky, G

    1994-01-01

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

  3. 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

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

    DEFF Research Database (Denmark)

    Harmsen, Hanne

    In studies of new product development it has often been concluded that to a large extent new product suc-cess is tunder the influence of companies and long lists of direct norma-tive guide-lines have been formulated. Nevertheless descriptive studi that deve-lopment practice is still far from the ...... change processes, and it is particularly the advantages and disadvantages of this - traditionally not very popular - research approach that is in focus in this paper....... widely published normative advice. While there may be several reasons for discrepancies between research results and prac-tice this paper focuses on problems of implementation of the identified success factors. Within the research area of NPD-management there has been numerous surveys as well as case...... studies both purely descriptive and studies identifying success and failure factors, but almost no studies of how companies actually undertake improve-ments, which problems they encounter,, and how/whether they overcome these problems. Action research is proposed as a suitable method for studying these...

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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)

  11. 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...

  12. Social representations of climate change

    International Nuclear Information System (INIS)

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

  13. 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…

  14. 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.

  15. 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

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Kotnik Bojan

    2007-01-01

    Full Text Available 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.

  18. 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......, technical, and institutional mechanisms. Geographically, bodily, and geometrically, the camera has positioned its subjects in social structures and hierarchies, in recognizable localities, and in iconic depth constructions which, although they show remarkable variation, nevertheless belong specifically 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...

  19. 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.

  20. 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...

  1. 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...

  2. 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.

  3. 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...

  4. 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.

  5. 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

  6. Friends reunited? Evolutionary robotics and representational explanation.

    Science.gov (United States)

    Wheeler, Michael

    2005-01-01

    Robotics as practiced within the artificial life community is no longer the bitter enemy of representational explanation in the way that it sometimes seemed to be in the heady, revolutionary days of the 1990s. This rapprochement is, however, fragile, because the field of evolutionary robotics continues to pose two important challenges to the idea that real-time intelligent action must or should be explained by appeal to inner representations. The first of these challenges, the threat from nontrivial causal spread, occurs when extra-neural factors account for the kind of adaptive richness and flexibility normally associated with representation-based control. The second, the threat from continuous reciprocal causation, occurs when the causal contributions made by the systemic components collectively responsible for behavior generation are massively context-sensitive and variable over time. I argue that while the threat from nontrivial causal spread can be resisted, the threat from continuous reciprocal causation provides a stern test for our representational intuitions. PMID:15811228

  7. 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

  8. 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...

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

    Science.gov (United States)

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

    2013-01-01

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

  10. 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.…

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

    DEFF Research Database (Denmark)

    Olsen, Jesper V; Mann, Matthias

    2011-01-01

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

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

    OpenAIRE

    Adonay Antonio Montes; Laurie Schroeder

    2011-01-01

    The requirement to complete field work hours as “action based pedagogy” allowed candidates in a school counseling program to broaden their cultural perceptions of diverse groups by engaging in action research projects of their own choosing, led by their interest in and commitment to becoming familiar with diverse populations of K-12 students. This assignment allowed candidates to immerse themselves in culturally rich schools as researchers to understand better the experiences of diverse stud...

  13. 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...

  14. 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.

  15. 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.

  16. 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...

  17. Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

    OpenAIRE

    Kamsu-Foguem, Bernard; Diallo, Gayo; Foguem, Clovis

    2013-01-01

    Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of med...

  18. 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...

  19. Covariance-Based Direction-of-Arrival Estimation of Wideband Coherent Chirp Signals via Sparse Representation

    OpenAIRE

    Yiyu Zhou; Zhitao Huang; Zhengmeng Liu; Zhichao Sha

    2013-01-01

    This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during the hyper-processes. Moreover, the a priori information of signal number is no longer a necessity f...

  20. A knowledge representation semantic network for a natural language syntactic analyzer based on the UML

    OpenAIRE

    Silva, Alberto Tavares da; Carvalho, Luis Alfredo V.

    2006-01-01

    The need for improving software processes approximated the software engineering and artificial intelligence areas. Artificial intelligence techniques have been used as a support to software development processes, particularly through intelligent assistants that offer a knowledge-based support to software process’ activities. The context of the present work is a project for an intelligent assistant that implements a linguistic technique with the purpose of extracting object-oriented elements f...

  1. 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...

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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

  8. 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…

  9. A similarity-based community detection method with multiple prototype representation

    Science.gov (United States)

    Zhou, Kuang; Martin, Arnaud; Pan, Quan

    2015-11-01

    Communities are of great importance for understanding graph structures in social networks. Some existing community detection algorithms use a single prototype to represent each group. In real applications, this may not adequately model the different types of communities and hence limits the clustering performance on social networks. To address this problem, a Similarity-based Multi-Prototype (SMP) community detection approach is proposed in this paper. In SMP, vertices in each community carry various weights to describe their degree of representativeness. This mechanism enables each community to be represented by more than one node. The centrality of nodes is used to calculate prototype weights, while similarity is utilized to guide us to partitioning the graph. Experimental results on computer generated and real-world networks clearly show that SMP performs well for detecting communities. Moreover, the method could provide richer information for the inner structure of the detected communities with the help of prototype weights compared with the existing community detection models.

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

    CERN Document Server

    Alessandretti, Laura; Gauvin, Laetitia

    2015-01-01

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

  11. 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

  12. 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.

  13. 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.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    NickBouskill

    2012-10-01

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

  16. 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.

  17. 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....

  18. 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

  19. QR CODE BASED ENCRYPTED MATRIX REPRESENTATION FOR ERADICATING HARDWARE AND SOFTWARE KEYLOGGING

    Directory of Open Access Journals (Sweden)

    R.Sangeetha

    2015-04-01

    Full Text Available The design of secure authentication protocols is quite challenging. Involving human authentication protocols is not easy because of their limited capability of computation and memorization. Keylogging is a major problem faced in internet banking. Keylogger is a software designed to capture all a users keyboard strokes and then make use of them to impersonate a user in financial transaction, also relying on users to enhance security necessary degrades the usability. In order to enhance security as well as usability here we use RSA algorithm which avoid some problems in e-banking such as session hijacking , monitoring using video sensor etc. By providing unique key to the users after scanning the QR code available in screen. According to the unique key,the user will be given a specific 4*4 matrix keyboard in user’s smart phone which reposition the keys every time inorder to avoid hacking. To that end, there are two visual authentication protocols: one is a one-time-password protocol, and the other is a password-based authentication protocol. Through rigorous analysis, we verify that our protocols are immune to many of the challenging authentication attacks applicable in the literature.

  20. DNS of thermocapillary flows based on two-scalar temperature representation

    Science.gov (United States)

    Bothe, Dieter; Ma, Chen

    2011-11-01

    The direct numerical simulation (DNS) of thermocapillary two-phase flow with free deformable interface requires the solution of the two-phase Navier-Stokes equations in 3D together with the energy balance. We employ the sharp interface model which is solved using an extended volume of fluid method, where the discretization is based on Finite Volumes. The energy equation is given in temperature form, where the temperature field is represented by two scalars, one for each phase. This way the averaging over grid cells is confined to the individual phases and, hence, a smearing of the temperature gradient jump is avoided. Interpolation of the temperature within interfacial cells, exploiting the energy transmission condition, yields accurate temperatures at the interface, which is of utmost importance for the calculation of thermocapillary forces. Here the position and orientation of the interface is approximated by piecewise linear interface construction (PLIC). This method is applied to investigate liquid films on locally heated planar, respectively heated structured substrates. The approach allows for the numerical simulation of evaporating flows coupled with thermal Marangoni effects.

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

    Science.gov (United States)

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

    2015-10-01

    It was found in previous studies that two types of objects (rectangles formed according to the Gestalt principle and Chinese words formed in a top-down fashion) can both induce an object-based effect. The aim of the present study was to investigate how the strength of an object representation affects the result of the competition between these two types of objects based on research carried out by Liu, Wang and Zhou [(2011) Acta Psychologica, 138(3), 397-404]. In Experiment 1, the rectangles were filled with two different colors to increase the strength of Gestalt object representation, and we found that the object effect changed significantly for the different stimulus types. Experiment 2 used Chinese words with various familiarities to manipulate the strength of the top-down object representation. As a result, the object-based effect induced by rectangles was observed only when the Chinese word familiarity was low. These results suggest that the strength of object representation determines the result of competition between different types of objects. PMID:26041271

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

    Directory of Open Access Journals (Sweden)

    Konrad Graf

    2011-08-01

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

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

    Directory of Open Access Journals (Sweden)

    J Michael Pearson

    2008-09-01

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

  4. The neural substrates of drawing: a voxel-based morphometry analysis of constructional, hierarchical, and spatial representation deficits.

    Science.gov (United States)

    Chechlacz, Magdalena; Novick, Abigail; Rotshtein, Pia; Bickerton, Wai-Ling; Humphreys, Glyn W; Demeyere, Nele

    2014-12-01

    Deficits in the ability to draw objects, despite apparently intact perception and motor abilities, are defined as constructional apraxia. Constructional deficits, often diagnosed based on performance on copying complex figures, have been reported in a range of pathologies, perhaps reflecting the contribution of several underlying factors to poor figure drawing. The current study provides a comprehensive analysis of brain-behavior relationships in drawing disorders based on data from a large cohort of subacute stroke patients (n = 358) using whole-brain voxel-wise statistical analyses linked to behavioral measures from a complex figure copy task. We found that (i) overall poor performance on figure copying was associated with subcortical lesions (BG and thalamus), (ii) lateralized deficits with respect to the midline of the viewer were associated with lesions within the posterior parietal lobule, and (iii) spatial positioning errors across the entire figure were associated with lesions within visual processing areas (lingual gyrus and calcarine) and the insula. Furthermore, deficits in reproducing global aspects of form were associated with damage to the right middle temporal gyrus, whereas deficits in representing local features were linked to the left hemisphere lesions within calcarine cortex (extending into the cuneus and precuneus), the insula, and the TPJ. The current study provides strong evidence that impairments in separate cognitive mechanisms (e.g., spatial coding, attention, motor execution, and planning) linked to different brain lesions contribute to poor performance on complex figure copying tasks. The data support the argument that drawing depends on several cognitive processes operating via discrete neuronal networks and that constructional problems as well as hierarchical and spatial representation deficits contribute to poor figure copying. PMID:24893744

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

    Science.gov (United States)

    Strambler, Michael J.; McKown, Clark

    2013-01-01

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

  6. Implementation of evidence-based practice in nursing using action research: a review

    NARCIS (Netherlands)

    Munten, Guus; Bogaard, Joop van den; Cox, Karen; Garretsen, Henk; Bongers, Inge

    2010-01-01

    As is often reported in the literature exploring the research-practice gap, applying the principles of evidence-based practice is easier said than done. Action research is a methodology with an explicit intent of linking the worlds of research and practice. This review attempts to answer the questio

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

    Science.gov (United States)

    Ballard, Susan D.

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  9. Design and analysis of direct action solenoid valve based on computational intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Liu Qianfeng, E-mail: liuqianfeng@gmail.co [Institute of Nuclear and New Energy Technology, Tsinghua University, Key Laboratory of Advanced Reactor Engineering and Safety of the Ministry of Education, Beijing 100084 (China); Bo Hanliang; Qin Benke [Institute of Nuclear and New Energy Technology, Tsinghua University, Key Laboratory of Advanced Reactor Engineering and Safety of the Ministry of Education, Beijing 100084 (China)

    2010-10-15

    Control Rod Hydraulic Drive Mechanism (CRHDM) is a newly invented patent of the Institute of Nuclear and New Energy Technology Tsinghua University which owns CRHDM's independent intellectual property rights while the integrated valve made up of three direct action solenoid valves is the key part of this mechanism. Therefore, the performance of the solenoid valve affects the integrated valve and the CRHDM directly. In this paper, we present a method to design the parameters of the direct action solenoid valve based on orthogonal experiment design, back propagation (BP) neural network and particle swarm optimization (PSO). The result proves that the method is feasible and accurate to design the parameters in order to obtain the biggest electromagnetic force. Besides, the result also shows that it is the current which influences the electromagnetic force of the direct action solenoid valve most.

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

    Directory of Open Access Journals (Sweden)

    Levi Gimenez

    2013-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Rafaela Vivian Valcarenghi

    2014-06-01

    Full Text Available This study aimed to propose institutional actions based on nursing diagnoses for the prevention of falls in the elderly. Qualitative, exploratory and descriptive research, with 30 institutionalized senior citizens from Rio Grande, RS, Brazil. During data collection five instruments were applied from March to July 2009. One presents the elderly’s profile; aspects that favored the falls; nursing diagnoses; proposals for institutional actions to prevent falls. The nursing diagnoses were identified: impaired physical mobility, decreased ability to transfer, shower self-care deficit, dressing self-care deficit, impaired environmental interpretation syndrome, chronic confusion, impaired memory; syndrome of stress due to changes; risk of falls, risk of trauma. Through the identification of nursing diagnoses it was possible to make a proposal for institutional actions aimed at preventing falls in the elderly who reside in long-stay institutions.

  12. Design and analysis of direct action solenoid valve based on computational intelligence

    International Nuclear Information System (INIS)

    Control Rod Hydraulic Drive Mechanism (CRHDM) is a newly invented patent of the Institute of Nuclear and New Energy Technology Tsinghua University which owns CRHDM's independent intellectual property rights while the integrated valve made up of three direct action solenoid valves is the key part of this mechanism. Therefore, the performance of the solenoid valve affects the integrated valve and the CRHDM directly. In this paper, we present a method to design the parameters of the direct action solenoid valve based on orthogonal experiment design, back propagation (BP) neural network and particle swarm optimization (PSO). The result proves that the method is feasible and accurate to design the parameters in order to obtain the biggest electromagnetic force. Besides, the result also shows that it is the current which influences the electromagnetic force of the direct action solenoid valve most.

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

    Directory of Open Access Journals (Sweden)

    Marko Mladineo

    2014-12-01

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

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

    Science.gov (United States)

    Chisholm, Joseph D; Kingstone, Alan

    2015-10-01

    Research has demonstrated that experience with action video games is associated with improvements in a host of cognitive tasks. Evidence from paradigms that assess aspects of attention has suggested that action video game players (AVGPs) possess greater control over the allocation of attentional resources than do non-video-game players (NVGPs). Using a compound search task that teased apart selection- and response-based processes (Duncan, 1985), we required participants to perform an oculomotor capture task in which they made saccades to a uniquely colored target (selection-based process) and then produced a manual directional response based on information within the target (response-based process). We replicated the finding that AVGPs are less susceptible to attentional distraction and, critically, revealed that AVGPs outperform NVGPs on both selection-based and response-based processes. These results not only are consistent with the improved-attentional-control account of AVGP benefits, but they suggest that the benefit of action video game playing extends across the full breadth of attention-mediated stimulus-response processes that impact human performance. PMID:25772554

  15. On knowledge representation for high energy physics control systems

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2016-06-01

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

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

    Science.gov (United States)

    White, Scott R.

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

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

    Science.gov (United States)

    Agrawal, Jugnu; Morin, Lisa L.

    2016-01-01

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

  19. Identifying relevant feature-action associations for grasping unmodelled objects

    DEFF Research Database (Denmark)

    Thomsen, Mikkel Tang; Kraft, Dirk; Krüger, Norbert

    2015-01-01

    Action affordance learning based on visual sensory information is a crucial problem within the development of cognitive agents. In this paper, we present a method for learning action affordances based on basic visual features, which can vary in their granularity, order of combination and semantic...... improvement by increasing the complexity of the perceptual representation. By that, we present important insights in how the design of the feature space influences the actual learning problem....

  20. Applying the risk-based corrective action process to ecological assessment of contaminated sites

    International Nuclear Information System (INIS)

    Risk-Based Corrective Action (RBCA) is a process in which site investigation and corrective action are focused on the goals of minimizing human health and environmental risk. A basic framework for the RBCA process is outlined in the American Society for Testing and Materials (ASTM) Emergency Standard Guide ES 38-94, Risk-Based Corrective Action Applied at Petroleum Release Sites . This presentation will include discussion of the critical features and, framework of the RBCA process, and will introduce a propose or RBCA which is specifically tailored to the problem of evaluating and responding to environmental risks. The RBCA process includes a number of useful features which expedite and streamline the site assessment and corrective action selection process. Of particular interest, with respect to environmental risk, is a tiered approach to site investigation. This new proposal includes a tiered methodology for investigating environmental risk which begins with a simple, generic analysis and progresses to a more detailed, site-specific analysis, if warranted. The discussion will also cover an example RBCA assessment of a site contaminated with weathered crude oil, and will include results from a laboratory investigation of the ecological toxicity of the contaminated site soils

  1. Repositories with Direct Representation

    OpenAIRE

    Allen, Robert Burnell

    2015-01-01

    A new generation of digital repositories could be based on direct representation of the contents with rich semantics and models rather than be collections of documents. The contents of such repositories would be highly structured which should help users to focus on meaningful relationships of the contents. These repositories would implement earlier proposals for model-oriented information organization by extending current work on ontologies to cover state changes, instances, and scenarios. Th...

  2. Factorizations and Physical Representations

    OpenAIRE

    Revzen, M.; F. C. Khanna(Edmonton, Canada); Mann, A.; Zak, J.

    2005-01-01

    A Hilbert space in M dimensions is shown explicitly to accommodate representations that reflect the prime numbers decomposition of M. Representations that exhibit the factorization of M into two relatively prime numbers: the kq representation (J. Zak, Phys. Today, {\\bf 23} (2), 51 (1970)), and related representations termed $q_{1}q_{2}$ representations (together with their conjugates) are analysed, as well as a representation that exhibits the complete factorization of M. In this latter repre...

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

    Science.gov (United States)

    Morita, Kenji; Jitsev, Jenia; Morrison, Abigail

    2016-09-15

    Value-based action selection has been suggested to be realized in the corticostriatal local circuits through competition among neural populations. In this article, we review theoretical and experimental studies that have constructed and verified this notion, and provide new perspectives on how the local-circuit selection mechanisms implement reinforcement learning (RL) algorithms and computations beyond them. The striatal neurons are mostly inhibitory, and lateral inhibition among them has been classically proposed to realize "Winner-Take-All (WTA)" selection of the maximum-valued action (i.e., 'max' operation). Although this view has been challenged by the revealed weakness, sparseness, and asymmetry of lateral inhibition, which suggest more complex dynamics, WTA-like competition could still occur on short time scales. Unlike the striatal circuit, the cortical circuit contains recurrent excitation, which may enable retention or temporal integration of information and probabilistic "soft-max" selection. The striatal "max" circuit and the cortical "soft-max" circuit might co-implement an RL algorithm called Q-learning; the cortical circuit might also similarly serve for other algorithms such as SARSA. In these implementations, the cortical circuit presumably sustains activity representing the executed action, which negatively impacts dopamine neurons so that they can calculate reward-prediction-error. Regarding the suggested more complex dynamics of striatal, as well as cortical, circuits on long time scales, which could be viewed as a sequence of short WTA fragments, computational roles remain open: such a sequence might represent (1) sequential state-action-state transitions, constituting replay or simulation of the internal model, (2) a single state/action by the whole trajectory, or (3) probabilistic sampling of state/action. PMID:27173430

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

    International Nuclear Information System (INIS)

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

  5. Representation of superoperators in double phase space

    International Nuclear Information System (INIS)

    Operators in quantum mechanics—either observables, density or evolution operators, unitary or not—can be represented by c-numbers in operator bases. The position and momentum bases are in one-to-one correspondence with lagrangian planes in double phase space, but this is also true for the well known Wigner–Weyl correspondence based on translation and reflection operators. These phase space methods are here extended to the representation of superoperators. We show that the Choi–Jamiolkowsky isomorphism between the dynamical matrix and the linear action of the superoperator constitutes a ‘double’ Wigner or chord transform when represented in double phase space. As a byproduct several previously unknown integral relationships between products of Wigner and chord distributions for pure states are derived. (paper)

  6. Representation of superoperators in double phase space

    Science.gov (United States)

    Saraceno, Marcos; Ozorio de Almeida, Alfredo M.

    2016-04-01

    Operators in quantum mechanics—either observables, density or evolution operators, unitary or not—can be represented by c-numbers in operator bases. The position and momentum bases are in one-to-one correspondence with lagrangian planes in double phase space, but this is also true for the well known Wigner-Weyl correspondence based on translation and reflection operators. These phase space methods are here extended to the representation of superoperators. We show that the Choi-Jamiolkowsky isomorphism between the dynamical matrix and the linear action of the superoperator constitutes a ‘double’ Wigner or chord transform when represented in double phase space. As a byproduct several previously unknown integral relationships between products of Wigner and chord distributions for pure states are derived.

  7. Using wellness recovery action plan and sensory-based intervention: a case example.

    Science.gov (United States)

    Gardner, Jennifer; Dong-Olson, Valerie; Castronovo, Anthony; Hess, Megan; Lawless, Kelly

    2012-01-01

    ABSTRACT The Wellness Recovery Action Plan (WRAP) is a tool used by persons living with psychiatric disabilities, which guides the development of an individualized plan of action to help achieve and/or maintain wellness and recovery. Through use of sensory-based treatment, the clients are able to explore sensory preferences and use this information when developing their plan. The WRAP and sensory-based treatment are complementary in nature and can be successfully blended to promote wellness and recovery for this population. As the occupational therapists are equipped to educate the clients on the link between sensory preferences and obtainment of wellness and recovery, this paper describes how the occupational therapy practitioners developed a program that used both for implementation of services. PMID:23899140

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

    Science.gov (United States)

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

    2016-07-01

    The aim of this study was to specify the role of action representations in thematic and functional similarity relations between manipulable artifact objects. Recent behavioral and neurophysiological evidence indicates that while they are all relevant for manipulable artifact concepts, semantic relations based on thematic (e.g., saw-wood), specific function similarity (e.g., saw-axe), and general function similarity (e.g., saw-knife) are differently processed, and may relate to different levels of action representation. Point-light displays of object-related actions previously encoded at the gesture level (e.g., "sawing") or at the higher level of action representation (e.g., "cutting") were used as primes before participants identified target objects (e.g., saw) among semantically related and unrelated distractors (e.g., wood, feather, piano). Analysis of eye movements on the different objects during target identification informed about the amplitude and the timing of implicit activation of the different semantic relations. Results showed that action prime encoding impacted the processing of thematic relations, but not that of functional similarity relations. Semantic competition with thematic distractors was greater and earlier following action primes encoded at the gesture level compared to action primes encoded at higher level. As a whole, these findings highlight the direct influence of action representations on thematic relation processing, and suggest that thematic relations involve gesture-level representations rather than intention-level representations. PMID:26077343

  9. Children as activist artists: Constructing citizenship through social justice arts-based participatory action research

    OpenAIRE

    Kohfeldt, Danielle Marie

    2014-01-01

    This dissertation investigates the creation of social justice art as a context for children's critical citizenship education and community empowerment. Drawing on data from an arts-based, after-school, youth participatory action research program with 4th and 5th grade low-income Latina/o children, this ethnographic case study investigates the creation process of a school mural depicting the histories, strengths, and struggles of community members. Data for this research include ethnographic...

  10. Human-Nature for Climate Action: Nature-Based Solutions for Urban Sustainability

    OpenAIRE

    Helen Santiago Fink

    2016-01-01

    The global climate change agenda proceeds at an incremental pace while the Earth is approaching critical tipping points in its development trajectory. Climate action at this pinnacle juncture needs to be greatly accelerated and rooted in the fundamentals of the problem—human beings’ disconnection from nature. This paper underscores the valuable role nature and nature-based solutions can play in addressing climate change at the city scale and its implications for broader sustainability. Urban ...

  11. Sensorless action-reaction-based residual vibration suppression for multi-degree-of-freedom flexible systems

    OpenAIRE

    Khalil, Islam Shoukry Mohammed; Sabanovic, Asif

    2010-01-01

    This paper demonstrates the feasibility of controlling motion and vibration of a class of flexible systems with inaccessible or unknown outputs through measurements taken from their actuators which are used as single platforms for measurements, whereas flexible dynamical systems are kept free from any attached sensors. Based on the action reaction law of dynamics, the well-known disturbance observer is used to determine the incident reaction forces from these dynamical systems on the inter...

  12. Evidence-Based Robust Design of Deflection Actions for Near Earth Objects

    OpenAIRE

    Zuiani, Federico; Vasile, Massimiliano; Gibbings, Alison

    2012-01-01

    This paper presents a novel approach to the robust design of deflection actions for Near Earth Objects (NEO). In particular, the case of deflection by means of Solar-pumped Laser ablation is studied here in detail. The basic idea behind Laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the Space-based Laser system a...

  13. Organizational Challenges of Multinational Corporations at the Base of the Pyramid: An Action-research Inquiry

    OpenAIRE

    Perrot, François

    2013-01-01

    To what extent and how does a multinational corporation adapt its strategy and organizational capabilities in order to address markets at the Base of the Pyramid? This paper builds on the results of a three-year action-research program conducted with Lafarge, a global building materials company and introduces a strategic framework which opposes two types of approaches of such markets: a licence-to-operate approach, and a business opportunityseeking approach. The article analyzes how the compa...

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

    DEFF Research Database (Denmark)

    Purushothaman, Aparna

    2012-01-01

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

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

    OpenAIRE

    Nicolas, J.A.Y.

    2015-01-01

    Innovative mode of action based in vitro assays for detection of marine neurotoxins J. Nicolas, P.J.M. Hendriksen, T.F.H. Bovee, I.M.C.M. Rietjens Marine biotoxins are naturally occurring compounds produced by particular phytoplankton species. These toxins often accumulate in seafood and thereby represent a threat to consumers. Regulatory limits have been set for lipophilic marine biotoxins (diarrhetic shellfish poisons (DSPs) and azaspiracids (AZPs)) and for most marine neurotoxins (amnesic ...

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

    OpenAIRE

    Marko Mladineo; Nenad Mladineo; Nikša Jajac

    2014-01-01

    In this paper, a Web-based Decision Support System (Web DSS), that supports humanitarian demining operations and restoration of mine-contaminated areas, is presented. The financial shortage usually triggers a need for priority setting in Project Management in Mine actions. As part of the FP7 Project TIRAMISU, a specialized Web DSS has been developed to achieve a fully transparent priority setting process. It allows stakeholders and donors to actively join the decision making process using a u...

  17. Forecast-based financing: an approach for catalyzing humanitarian action based on extreme weather and climate forecasts

    Science.gov (United States)

    Coughlan de Perez, E.; van den Hurk, B.; van Aalst, M. K.; Jongman, B.; Klose, T.; Suarez, P.

    2015-04-01

    Disaster risk reduction efforts traditionally focus on long-term preventative measures or post-disaster response. Outside of these, there are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce the risk of impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which can indicate heightened risk of disaster but are rarely used to initiate preventative action. Barriers range from the protracted debate over the best strategy for intervention to the inherent uncomfortableness on the part of donors to invest in a situation that will likely arise but is not certain. In general, it is unclear what levels of forecast probability and magnitude are "worth" reacting to. Here, we propose a novel forecast-based financing system to automatically trigger action based on climate forecasts or observations. The system matches threshold forecast probabilities with appropriate actions, disburses required funding when threshold forecasts are issued, and develops standard operating procedures that contain the mandate to act when these threshold forecasts are issued. We detail the methods that can be used to establish such a system, and provide illustrations from several pilot cases. Ultimately, such a system can be scaled up in disaster-prone areas worldwide to improve effectiveness at reducing the risk of disaster.

  18. Forecast-based financing: an approach for catalyzing humanitarian action based on extreme weather and climate forecasts

    Directory of Open Access Journals (Sweden)

    E. Coughlan de Perez

    2014-05-01

    Full Text Available Disaster risk reduction efforts traditionally focus on long-term preventative measures or post-disaster response. Outside of these, there are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce the risk of impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which can indicate heightened risk of disaster but are rarely used to initiate preventative action. Barriers range from the protracted debate over the best strategy for intervention to the inherent uncomfortableness on the part of donors to invest in a situation that will "likely" arrive but is not certain. In general, it is unclear what levels of forecast probability and magnitude are "worth" reacting to. Here, we propose a novel forecast-based financing system to automatically trigger action based on climate forecasts or observations. The system matches threshold forecast probabilities with appropriate actions, disburses required funding when threshold forecasts are issued, and develops Standard Operating Procedures that contain the mandate to act when these threshold forecasts are issued. We detail the methods that can be used to establish such a system, and provide illustrations from several pilot cases. Ultimately, such as system can be scaled up in disaster-prone areas worldwide to improve effectiveness at reducing the risk of disaster.

  19. A unified framework for activity recognition-based behavior analysis and action prediction in smart homes.

    Science.gov (United States)

    Fatima, Iram; Fahim, Muhammad; Lee, Young-Koo; Lee, Sungyoung

    2013-01-01

    In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users" actions to gain knowledge about their habits and preferences. PMID:23435057

  20. A Unified Framework for Activity Recognition-Based Behavior Analysis and Action Prediction in Smart Homes

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2013-02-01

    Full Text Available In recent years, activity recognition in smart homes is an active research area due to its applicability in many applications, such as assistive living and healthcare. Besides activity recognition, the information collected from smart homes has great potential for other application domains like lifestyle analysis, security and surveillance, and interaction monitoring. Therefore, discovery of users common behaviors and prediction of future actions from past behaviors become an important step towards allowing an environment to provide personalized service. In this paper, we develop a unified framework for activity recognition-based behavior analysis and action prediction. For this purpose, first we propose kernel fusion method for accurate activity recognition and then identify the significant sequential behaviors of inhabitants from recognized activities of their daily routines. Moreover, behaviors patterns are further utilized to predict the future actions from past activities. To evaluate the proposed framework, we performed experiments on two real datasets. The results show a remarkable improvement of 13.82% in the accuracy on average of recognized activities along with the extraction of significant behavioral patterns and precise activity predictions with 6.76% increase in F-measure. All this collectively help in understanding the users” actions to gain knowledge about their habits and preferences.

  1. Representations from the past

    DEFF Research Database (Denmark)

    Sammut, Gordon; Tsirogianni, Stavroula; Wagoner, Brady

    2012-01-01

    propose an epidemiological time-series framework for social representations, that are conceptualised as evolving over time and that are subject to a ‘ratchet effect’ that perpetuates meaning in a collective. We argue that understanding forms of social behaviour that draw on lay explanations of social......Psychological life is subject to the influence of a constructed and potentially reconstituted past, as well as to future anticipated outcomes and expectations. Human behaviour occurs along a temporal trajectory that marks the projects individuals adopt in their quests of human action. Explanations...... of social behaviour are limited insofar as they exclude a historical concern with human purpose. In this paper, we draw on Bartlett’s notion of collective remembering to argue that manifest social relations are rooted in past events that give present behaviours meaning and justification. We further...

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

    OpenAIRE

    Noël, Marie-Pascale; Rousselle, Laurence

    2011-01-01

    Studies on developmental dyscalculia (DD) have tried to identify a basic numerical deficit that could account for this specific learning disability. The first proposition was that the number magnitude representation of these children was impaired. However, Rousselle and Noël (2007) brought data showing that this was not the case but rather that these children were impaired when processing the magnitude of symbolic numbers only. Since then, incongruent results have been published. In this pape...

  3. Decoherence under many-body system-environment interactions: a stroboscopic representation based on a fictitiously homogenized interaction rate

    OpenAIRE

    Alvarez, Gonzalo A.; Danieli, Ernesto P.; Levstein, Patricia R.; Pastawski, Horacio M.

    2007-01-01

    An environment interacting with portions of a system leads to multiexponential interaction rates. Within the Keldysh formalism, we fictitiously homogenize the system-environment interaction yielding a uniform decay rate facilitating the evaluation of the propagators. Through an injection procedure we neutralize the fictitious interactions. This technique justifies a stroboscopic representation of the system-environment interaction which is useful for numerical implementation and converges to ...

  4. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  5. The neuroscience of social relations. A comparative-based approach to empathy and to the capacity of evaluating others' action value.

    Science.gov (United States)

    Ferrari, Pier F

    2014-02-01

    One of the key questions in understanding human morality is how central are emotions in influencing our decisions and in our moral judgments. Theoretical work has proposed that empathy could play an important role in guiding our tendencies to behave altruistically or selfishly. Neurosciences suggest that one of the core elements of empathic behavior in human and nonhuman primates is the capacity to internally mimic the behavior of others, through the activation of shared motor representations. Part of the neural circuits involves parietal and premotor cortical regions (mirror system), in conjunction with other areas, such as the insula and the anterior cingulate cortex. Together with this embodied neural mechanism, there is a cognitive route in which individuals can evaluate the social situation without necessary sharing the emotional state of others. For example, several brain areas of the prefrontal cortex track the effects of one's own behavior and of the value of one's own actions in social contexts. It is here proposed that, moral cognition could emerge as the consequence of the activity of emotional processing brain networks, probably involving mirror mechanisms, and of brain regions that, through abstract-inferential processing, evaluate the social context and the value of actions in terms of abstract representations. A comparative-based approach to the neurobiology of social relations and decision-making may explain how complex mental faculties, such as moral judgments, have their foundations in brain networks endowed with functions related to emotional and abstract-evaluation processing of goods. It is proposed that in primate evolution these brain circuits have been coopted in the social domain to integrate mechanisms of self-reward, estimation of negative outcomes, with emotional engagement. PMID:25258451

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

    International Nuclear Information System (INIS)

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

  7. Word Representations via Gaussian Embedding

    OpenAIRE

    Vilnis, Luke; McCallum, Andrew

    2014-01-01

    Current work in lexical distributed representations maps each word to a point vector in low-dimensional space. Mapping instead to a density provides many interesting advantages, including better capturing uncertainty about a representation and its relationships, expressing asymmetries more naturally than dot product or cosine similarity, and enabling more expressive parameterization of decision boundaries. This paper advocates for density-based distributed embeddings and presents a method for...

  8. Vertical cavity surface emitting laser action of an all monolithic ZnO-based microcavity

    OpenAIRE

    Kalusniak, S.; Sadofev, S.; Halm, S.; Henneberger, F.

    2010-01-01

    We report on room temperature laser action of an all monolithic ZnO-based vertical cavity surface emitting laser (VCSEL) under optical pumping. The VCSEL structure consists of a 2{\\lambda} microcavity containing 8 ZnO/Zn(0.92)Mg(0.08)O quantum wells embedded in epitaxially grown Zn(0.92)Mg(0.08)O/Zn(0.65)Mg(0.35)O distributed Bragg reflectors (DBRs). As a prerequisite, design and growth of high reflectivity DBRs based on ZnO and (Zn,Mg)O for optical devices operating in the ultraviolet and bl...

  9. The Modeling Method of Forces Action Based on COADL%基于COADL兵力行动建模方法

    Institute of Scientific and Technical Information of China (English)

    张磊; 朱琳

    2011-01-01

    According to the desire of forces action modeling,designing a series of modeling language for forces action- COADL (Course Of Action Description Language), from the description of forces action modeling language,giving the outcome of forces action strategy. And as a basis, discussing the method of forces action modeling which based on COADL, concretely including : forces action basic modeling, phase action modeling, course of action modeling and forces action dynamic model.%根据兵力行动建模的需要,设计了一套兵力行动建模语言--COADL (Course Of Action Description Language),通过对兵力行动建模语言的描述,得到了兵力行动策略的产生,并以此为基础,讨论了基于COADL兵力行动的建模方法,具体包括:基本兵力行动建模,阶段行动方案建模,行动过程建模和兵力行动动态模型的构建.

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

    Directory of Open Access Journals (Sweden)

    Adonay Antonio Montes

    2011-12-01

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

  11. Ultra-precision rotating reference based on self-acting external-pressure complex action principle

    International Nuclear Information System (INIS)

    In order to increase the loading capacity and stiffness of a gas lubricated rotating reference and its anti-disturbance capability, and further improve the rotating precision, this paper puts forward a kind of ultra-precision rotating reference based on a self-acting external pressure complex action principle. First two important parameters were defined, the external pressurized bearing number, and the pressure ratio of the complex action gas bearing. On this basis, the analytical model of this rotating reference was set up completely. This model shows that the loading capacity function of the rotating reference is composed of six items. According to this analytical model, ignoring the self-acting effect, the loading capacity and stiffness increased to 30% higher than the usual in an external pressurized gas lubricated reference

  12. Spatial representation of soundscape

    Science.gov (United States)

    Boubezari, Mohammed; Bento Coelho, Jos-Luis

    2001-05-01

    For the last 30 years the concept of soundscape has been largely adopted in many scientific disciplines and by the urban experts for the benefit of a better comprehension and management of the sound environment. However, the spatial representation of the soundscape as a simple tool for the description, management or composition of sound environment is always needed. In this article a method is presented for the spatial sound representation with differentiated sources. The first results are shown. This method gives an account of the soundscape as close as possible to the way it can be perceived by the listener in each location. This method generates qualitative sound maps in a reduced urban scale, based on in situ measurements and on the implication of the measuring subject perception. The maps are sufficient enough to isolate many sound sources of the overall sound field. In this manner, sound quality refers to the sound attribute of a perceived object. It is neither an aesthetic judgment nor traditional psychoacoustics criteria. Concrete examples of application to squares in the city of Lisbon will be shown and discussed. The limits and the prospects of such a qualitative representation will also be presented and discussed.

  13. Multiple Sparse Representations Classification.

    Science.gov (United States)

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

    2015-01-01

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

  14. [Time perceptions and representations].

    Science.gov (United States)

    Tordjman, S

    2015-09-01

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

  15. Analytic derivation of gluons and monopoles from SU(2) lattice Yang-Mills theory. I. BF Yang-Mills representation

    CERN Document Server

    Conrady, F

    2006-01-01

    In this series of three papers, we generalize the derivation of photons and monopoles by Polyakov and Banks, Myerson and Kogut, to obtain gluon-monpole representations of SU(2) lattice gauge theory. The papers take three different representations as their starting points: the representation as a BF Yang-Mills theory, the spin foam representation and the plaquette representation. The subsequent derivations are based on semiclassical expansions. In this first article, we cast d-dimensional SU(2) lattice gauge theory in the form of a lattice BF Yang-Mills theory. In several steps, the expectation value of a Wilson loop is transformed into a path integral over a gluon field and monopole-like degrees of freedom. The action contains the tree-level Coulomb interaction and a nonlinear coupling between gluons, monopoles and current. At the end, we compare the results from all three papers.

  16. Texture Representations Using Subspace Embeddings.

    Science.gov (United States)

    Yang, Xiaodong; Tian, Yingli

    2013-07-15

    In this paper, we propose a texture representation framework to map local texture patches into a low-dimensional texture subspace. In natural texture images, textons are entangled with multiple factors, such as rotation, scaling, viewpoint variation, illumination change, and non-rigid surface deformation. Mapping local texture patches into a low-dimensional subspace can alleviate or eliminate these undesired variation factors resulting from both geometric and photometric transformations. We observe that texture representations based on subspace embeddings have strong resistance to image deformations, meanwhile, are more distinctive and more compact than traditional representations. We investigate both linear and non-linear embedding methods including Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Locality Preserving Projections (LPP) to compute the essential texture subspace. The experiments in the context of texture classification on benchmark datasets demonstrate that the proposed subspace embedding representations achieve the state-of-the-art results while with much fewer feature dimensions. PMID:23710105

  17. (Self)-representations on youtube

    DEFF Research Database (Denmark)

    Simonsen, Thomas Mosebo

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

  18. Dissonance-Based Eating Disorder Prevention Program Reduces Reward Region Response to Thin Models; How Actions Shape Valuation

    OpenAIRE

    Eric Stice; Sonja Yokum; Allison Waters

    2015-01-01

    Research supports the effectiveness of a dissonance-based eating disorder prevention program wherein high-risk young women with body dissatisfaction critique the thin ideal, which reduces pursuit of this ideal, and the theory that dissonance induction contributes to these effects. Based on evidence that dissonance produces attitudinal change by altering neural representation of valuation, we tested whether completing the Body Project would reduce response of brain regions implicated in reward...

  19. Decoherence under many-body system-environment interactions: A stroboscopic representation based on a fictitiously homogenized interaction rate

    International Nuclear Information System (INIS)

    An environment interacting with portions of a system leads to multiexponential interaction rates. Within the Keldysh formalism, we fictitiously homogenize the system-environment interaction yielding a uniform decay rate facilitating the evaluation of the propagators. Through an injection procedure we neutralize the fictitious interactions. This technique justifies a stroboscopic representation of the system-environment interaction which is useful for numerical implementation and converges to the natural continuous process. We apply this procedure to a fermionic two-level system and use the Jordan-Wigner transformation to solve a two-spin swapping gate in the presence of a spin environment

  20. Decoherence under many-body system-environment interactions: A stroboscopic representation based on a fictitiously homogenized interaction rate

    Science.gov (United States)

    Álvarez, Gonzalo A.; Danieli, Ernesto P.; Levstein, Patricia R.; Pastawski, Horacio M.

    2007-06-01

    An environment interacting with portions of a system leads to multiexponential interaction rates. Within the Keldysh formalism, we fictitiously homogenize the system-environment interaction yielding a uniform decay rate facilitating the evaluation of the propagators. Through an injection procedure we neutralize the fictitious interactions. This technique justifies a stroboscopic representation of the system-environment interaction which is useful for numerical implementation and converges to the natural continuous process. We apply this procedure to a fermionic two-level system and use the Jordan-Wigner transformation to solve a two-spin swapping gate in the presence of a spin environment.