Scalable semantic aware context storage

The number of connected devices collecting and distributing real-world information through various systems, is expected to soar in the coming years. As the number of such connected devices grows, it becomes increasingly difficult to store and share all these new sources of information. Several context representation schemes try to standardize this information, but none of them have been widely adopted. In previous work we addressed this challenge, however our solution had some drawbacks: poor semantic extraction and scalability. In this paper we discuss ways to efficiently deal with representation schemes' diversity and propose a novel d-dimension organization model. Our evaluation shows that d-dimension model improves scalability and semantic extraction.

Análise dos conteúdos termodinâmicos em livros de Química e Física do ensino médio

PNLEM came out in 2004 and modified the view about schoolbook in Brazil. New perspectives pointed towards constitution of a more critical citizen as of an interdisciplinary and more contextualized teaching, made schoolbook understand these changes.But not always these alterations are checked up on by all means,because what we notice are adaptation of works have already known on market, where texts that are placed reveal environmental, socioeconomic, historical facts or daily phenomenon, or then scientific relevancy examples.We thus offer to analyse contents of chemical thermodynamics and physics for high school which are shown on schoolbook of chemistry and physics validated by PNLEM 2012, now called PNLD, studying the facts if these works bring these scientific sociocultural standpoint as well as their historical context,considering as analysis categories the following criteria: presentation of introduction, content contextualizing,presentation of concepts, thermodynamics historical context, representation in microscopic level and proposal of experiments.Eleven books were analysed,being five of chemistry and six of physics.So was applied a questionnaire with physics and chemistry teachers of high school to have an impression of their opinion about their teaching strategies and about schoolbook.This work grounded in orientations of legal documents about high school in Brazil (LDB,PCN,PCN+,OCEM) and in research on science teaching that regards specifically schoolbook and physics and chemical thermodynamics teaching.Were eleven books in number, only four denoted much coherence with new perspectives for high school, being two of chemistry and two of physics,whose concern about contextualizing and with a much integrated view of science to student s reality,indicating much social and critical character.The rest, when don t overlook,regard cultural and historical,socioeconomic contexts in isolated manner from presented concepts,aside from content

Dialogue in the crisis of representation : realism and antirealism in the context of the conversation between theologians and quantum physicists in Göttingen 1949-1961

The aim of this study is to analyse the content of the interdisciplinary conversations in Göttingen between 1949 and 1961. The task is to compare models for describing reality presented by quantum physicists and theologians. Descriptions of reality indifferent disciplines are conditioned by the development of the concept of reality in philosophy, physics and theology. Our basic problem is stated in the question: How is it possible for the intramental image to match the external object?Cartesian knowledge presupposes clear and distinct ideas in the mind prior to observation resulting in a true correspondence between the observed object and the cogitative observing subject. The Kantian synthesis between rationalism and empiricism emphasises an extended character of representation. The human mind is not a passive receiver of external information, but is actively construing intramental representations of external reality in the epistemological process. Heidegger's aim was to reach a more primordial mode of understanding reality than what is possible in the Cartesian Subject-Object distinction. In Heidegger's philosophy, ontology as being-in-the-world is prior to knowledge concerning being. Ontology can be grasped only in the totality of being (Dasein), not only as an object of reflection and perception. According to Bohr, quantum mechanics introduces an irreducible loss in representation, which classically understood is a deficiency in knowledge. The conflicting aspects (particle and wave pictures) in our comprehension of physical reality, cannot be completely accommodated into an entire and coherent model of reality. What Bohr rejects is not realism, but the classical Einsteinian version of it. By the use of complementary descriptions, Bohr tries to save a fundamentally realistic position. The fundamental question in Barthian theology is the problem of God as an object of theological discourse. Dialectics is Barth¿s way to express knowledge of God avoiding a speculative theology and a human-centred religious self-consciousness. In Barthian theology, the human capacity for knowledge, independently of revelation, is insufficient to comprehend the being of God. Our knowledge of God is real knowledge in revelation and our words are made to correspond with the divine reality in an analogy of faith. The point of the Bultmannian demythologising programme was to claim the real existence of God beyond our faculties. We cannot simply define God as a human ideal of existence or a focus of values. The theological programme of Bultmann emphasised the notion that we can talk meaningfully of God only insofar as we have existential experience of his intervention. Common to all these twentieth century philosophical, physical and theological positions, is a form of anti-Cartesianism. Consequently, in regard to their epistemology, they can be labelled antirealist. This common insight also made it possible to find a common meeting point between the different disciplines. In this study, the different standpoints from all three areas and the conversations in Göttingen are analysed in the frameworkof realism/antirealism. One of the first tasks in the Göttingen conversations was to analyse the nature of the likeness between the complementary structures inquantum physics introduced by Niels Bohr and the dialectical forms in the Barthian doctrine of God. The reaction against epistemological Cartesianism, metaphysics of substance and deterministic description of reality was the common point of departure for theologians and physicists in the Göttingen discussions. In his complementarity, Bohr anticipated the crossing of traditional epistemic boundaries and the generalisation of epistemological strategies by introducing interpretative procedures across various disciplines.

Children's representation of family mealtime in the context of maternal eating disorders

Background Recent research provides evidence for specific disturbance in feeding and growth in children of mothers with eating disorders. Aim To investigate the impact of maternal eating disorders during the post-natal year on the internal world of children, as expressed in children's representations of self and their mother in pretend mealtime play at 5 years of age. Methods Children of mothers with eating disorders (n = 33) and a comparison group (n = 24) were videotaped enacting a family mealtime in pretend play. Specific classes of children's play representations were coded blind to group membership. Univariate analyses compared the groups on representations of mother and self. Logistic regression explored factors predicting pretend play representations. Results Positive representations of the mother expressed as feeding, eating or body shape themes were more frequent in the index group. There were no other significant group differences in representations. In a logistic regression analysis, current maternal eating psychopathology was the principal predictor of these positive maternal representations. Marital criticism was associated with negative representations of the mother. Conclusions These findings suggest that maternal eating disorders may influence the development of a child's internal world, such that they are more preoccupied with maternal eating concerns. However, more extensive research on larger samples is required to replicate these preliminary findings.

Semi-automatic knowledge extraction, representation and context-sensitive intelligent retrieval of video content using collateral context modelling with scalable ontological networks

Automatic indexing and retrieval of digital data poses major challenges. The main problem arises from the ever increasing mass of digital media and the lack of efficient methods for indexing and retrieval of such data based on the semantic content rather than keywords. To enable intelligent web interactions, or even web filtering, we need to be capable of interpreting the information base in an intelligent manner. For a number of years research has been ongoing in the field of ontological engineering with the aim of using ontologies to add such (meta) knowledge to information. In this paper, we describe the architecture of a system (Dynamic REtrieval Analysis and semantic metadata Management (DREAM)) designed to automatically and intelligently index huge repositories of special effects video clips, based on their semantic content, using a network of scalable ontologies to enable intelligent retrieval. The DREAM Demonstrator has been evaluated as deployed in the film post-production phase to support the process of storage, indexing and retrieval of large data sets of special effects video clips as an exemplar application domain. This paper provides its performance and usability results and highlights the scope for future enhancements of the DREAM architecture which has proven successful in its first and possibly most challenging proving ground, namely film production, where it is already in routine use within our test bed Partners' creative processes. (C) 2009 Published by Elsevier B.V.

Social Context and Economic Biases in Representation

This article explores the role of political context in shaping economic biases in representation-the degree to which wealthy citizens' views are more strongly represented than poorer citizens' views in the choices of policymakers. I develop a general model that explains why poorer citizens will be better represented relative to the rich in certain political contexts than others, arguing that the relative representation of the poor will be stronger in contexts that make the views of the poor relevant and accessible to policymakers. I then derive several specific hypotheses that flow from this model and test these hypotheses through a study of the dyadic relationships between citizens and their representatives in the U.S. Congress. The results show that poorer citizens are better represented relative to the rich in Congressional districts that are electorally competitive, have low median incomes, have relatively equal distributions of incomes, have a significant organized labor presence, and are represented by Democrats.

The impact of context on pattern category learning and representation

Context traditionally has been regarded in vision research as a determinant for the interpretation of sensory information on the basis of previously acquired knowledge. Here we propose a novel, complementary perspective by showing that context also specifically affects visual category learning. In two experiments involving sets of Compound Gabor patterns we explored how context, as given by the stimulus set to be learned, affects the internal representation of pattern categories. In Experiment 1, we changed the (local) context of the individual signal classes by changing the configuration of the learning set. In Experiment 2, we varied the (global) context of a fixed class configuration by changing the degree of signal accentuation. Generalization performance was assessed in terms of the ability to recognize contrast-inverted versions of the learning patterns. Both contextual variations yielded distinct effects on learning and generalization thus indicating a change in internal category representation. Computer simulations suggest that the latter is related to changes in the set of attributes underlying the production rules of the categories. The implications of these findings for phenomena of contrast (in)variance in visual perception are discussed.

Improving distributed representation of word sense via WordNet Gloss composition and context clustering

In recent years, there has been an increas-ing interest in learning a distributed rep-resentation of word sense. Traditional context clustering based models usually require careful tuning of model parame-ters, and typically perform worse on infre-quent word senses. This paper presents a novel approach which addresses these lim-itations 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 represen-tations outperform the publicly available embeddings on 2 out of 4 metrics in the word similarity task, and 6 out of 13 sub tasks in the analogical reasoning task.

A gloss composition and context clustering based distributed word sense representation model

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.

On learning context-free and context-sensitive languages

The long short-term memory (LSTM) is not the only neural network which learns a context sensitive language. Second-order sequential cascaded networks (SCNs) are able to induce means from a finite fragment of a context-sensitive language for processing strings outside the training set. The dynamical behavior of the SCN is qualitatively distinct from that observed in LSTM networks. Differences in performance and dynamics are discussed.

Eigenvalue computations in the context of data-sparse approximations of integral operators

In this work, we consider the numerical solution of a large eigenvalue problem resulting from a finite rank discretization of an integral operator. We are interested in computing a few eigenpairs, with an iterative method, so a matrix representation that allows for fast matrix-vector products is required. Hierarchical matrices are appropriate for this setting, and also provide cheap LU decompositions required in the spectral transformation technique. We illustrate the use of freely available software tools to address the problem, in particular SLEPc for the eigensolvers and HLib for the construction of H-matrices. The numerical tests are performed using an astrophysics application. Results show the benefits of the data-sparse representation compared to standard storage schemes, in terms of computational cost as well as memory requirements.

An emotional and context-aware model for adapting RSS news to users and groups

The exhibition of information does not always attend to the preferences and characteristics of the users, nor the context that involves the user. With the aim of overcoming this gap, we propose an emotional context-aware model for adapting information contents to users and groups. The proposed model is based on OCC and Big Five models to handle emotion and personality respectively. The idea is to adapt the representation of the information in order to maximize the positive emotional valences and minimize the negatives. To evaluate the proposed model it was developed a prototype for adapting RSS news to users and group of users.

On lattices from combinatorial game theory modularity and a representation theorem: finite case

We show that a self-generated set of combinatorial games, S. may not be hereditarily closed but, strong self-generation and hereditary closure are equivalent in the universe of short games. In [13], the question "Is there a set which will give a non-distributive but modular lattice?" appears. A useful necessary condition for the existence of a finite non-distributive modular L(S) is proved. We show the existence of S such that L(S) is modular and not distributive, exhibiting the first known example. More, we prove a Representation Theorem with Games that allows the generation of all finite lattices in game context. Finally, a computational tool for drawing lattices of games is presented. (C) 2014 Elsevier B.V. All rights reserved.

Consistency and Context Management in a Multi Agent Belief Revision Testbed

Multi-agent architectures are well suited for complex inherently distributed problem solving domains. From the many challenging aspects that arise within this framework, a crucial one emerges: how to incorporate dynamic and conflicting agent beliefs? While the belief revision activity in a single agent scenario is concentrated on incorporating new information while preserving consistency, in a multi-agent system it also has to deal with possible conflicts between the agents perspectives. To provide an adequate framework, each agent, built as a combination of an assumption based belief revision system and a cooperation layer, was enriched with additional features: a distributed search control mechanism allowing dynamic context management, and a set of different distributed consistency methodologies. As a result, a Distributed Belief Revision Testbed (DiBeRT) was developed. This paper is a preliminary report presenting some of DiBeRT contributions: a concise representation of external beliefs; a simple and innovative methodology to achieve distributed context management; and a reduced inter-agent data exchange format.

Creation and extension of ontologies for describing communications in the context of organizations

Thesis submitted to Faculdade de Ciências e Tecnologia of the Universidade Nova de Lisboa, in partial fulfillment of the requirements for the degree of Master in Computer Science