3D semantic models for dental education

This paper explores the benefits of using immersive and interactive virtual reality environments to teach Dentistry. We present a tool for educators to manipulate and edit virtual models. One of the main contributions is that multimedia information can be semantically associated with parts of the model, through an ontology, enriching the experience; for example, videos can be linked to each tooth demonstrating how to extract them. The use of semantic information gives a greater flexibility to the models, since filters can be applied to create temporary models that show subsets of the original data in a human friendly way. We also explain how the software was written to run in arbitrary multi-projection environments. © 2011 Springer-Verlag.

Architecture for peer-to-peer databases with routing queries using ant colony algorithm and semantic support

In a peer-to-peer network, the nodes interact with each other by sharing resources, services and information. Many applications have been developed using such networks, being a class of such applications are peer-to-peer databases. The peer-to-peer databases systems allow the sharing of unstructured data, being able to integrate data from several sources, without the need of large investments, because they are used existing repositories. However, the high flexibility and dynamicity of networks the network, as well as the absence of a centralized management of information, becomes complex the process of locating information among various participants in the network. In this context, this paper presents original contributions by a proposed architecture for a routing system that uses the Ant Colony algorithm to optimize the search for desired information supported by ontologies to add semantics to shared data, enabling integration among heterogeneous databases and the while seeking to reduce the message traffic on the network without causing losses in the amount of responses, confirmed by the improve of 22.5% in this amount. © 2011 IEEE.

Pangea - Arquitetura semântica para a integração de dados e modelos geoespaciais na Web

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract Background The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heteregeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data. Results We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data. Conclusions The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

A Fuzzy Ontology-Driven Approach to Semantic Interoperability in e-Government Big Data

With the increasing production of information from e-government initiatives, there is also the need to transform a large volume of unstructured data into useful information for society. All this information should be easily accessible and made available in a meaningful and effective way in order to achieve semantic interoperability in electronic government services, which is a challenge to be pursued by governments round the world. Our aim is to discuss the context of e-Government Big Data and to present a framework to promote semantic interoperability through automatic generation of ontologies from unstructured information found in the Internet. We propose the use of fuzzy mechanisms to deal with natural language terms and present some related works found in this area. The results achieved in this study are based on the architectural definition and major components and requirements in order to compose the proposed framework. With this, it is possible to take advantage of the large volume of information generated from e-Government initiatives and use it to benefit society.

People semantic description and re-identification from point cloud geometry

The automatic extraction of biometric descriptors of anonymous people is a challenging scenario in camera networks. This task is typically accomplished making use of visual information. Calibrated RGBD sensors make possible the extraction of point cloud information. We present a novel approach for people semantic description and re-identification using the individual point cloud information. The proposal combines the use of simple geometric features with point cloud features based on surface normals.

Semantic-based middleware solutions to support context-aware service provisioning in pervasive environments

The dynamicity and heterogeneity that characterize pervasive environments raise new challenges in the design of mobile middleware. Pervasive environments are characterized by a significant degree of heterogeneity, variability, and dynamicity that conventional middleware solutions are not able to adequately manage. Originally designed for use in a relatively static context, such middleware systems tend to hide low-level details to provide applications with a transparent view on the underlying execution platform. In mobile environments, however, the context is extremely dynamic and cannot be managed by a priori assumptions. Novel middleware should therefore support mobile computing applications in the task of adapting their behavior to frequent changes in the execution context, that is, it should become context-aware. In particular, this thesis has identified the following key requirements for novel context-aware middleware that existing solutions do not fulfil yet. (i) Middleware solutions should support interoperability between possibly unknown entities by providing expressive representation models that allow to describe interacting entities, their operating conditions and the surrounding world, i.e., their context, according to an unambiguous semantics. (ii) Middleware solutions should support distributed applications in the task of reconfiguring and adapting their behavior/results to ongoing context changes. (iii) Context-aware middleware support should be deployed on heterogeneous devices under variable operating conditions, such as different user needs, application requirements, available connectivity and device computational capabilities, as well as changing environmental conditions. Our main claim is that the adoption of semantic metadata to represent context information and context-dependent adaptation strategies allows to build context-aware middleware suitable for all dynamically available portable devices. Semantic metadata provide powerful knowledge representation means to model even complex context information, and allow to perform automated reasoning to infer additional and/or more complex knowledge from available context data. In addition, we suggest that, by adopting proper configuration and deployment strategies, semantic support features can be provided to differentiated users and devices according to their specific needs and current context. This thesis has investigated novel design guidelines and implementation options for semantic-based context-aware middleware solutions targeted to pervasive environments. These guidelines have been applied to different application areas within pervasive computing that would particularly benefit from the exploitation of context. Common to all applications is the key role of context in enabling mobile users to personalize applications based on their needs and current situation. The main contributions of this thesis are (i) the definition of a metadata model to represent and reason about context, (ii) the definition of a model for the design and development of context-aware middleware based on semantic metadata, (iii) the design of three novel middleware architectures and the development of a prototypal implementation for each of these architectures, and (iv) the proposal of a viable approach to portability issues raised by the adoption of semantic support services in pervasive applications.

Semantic Service Architectures for Smart Environments

Many industries and academic institutions share the vision that an appropriate use of information originated from the environment may add value to services in multiple domains and may help humans in dealing with the growing information overload which often seems to jeopardize our life. It is also clear that information sharing and mutual understanding between software agents may impact complex processes where many actors (humans and machines) are involved, leading to relevant socioeconomic benefits. Starting from these two input, architectural and technological solutions to enable “environment-related cooperative digital services” are here explored. The proposed analysis starts from the consideration that our environment is physical space and here diversity is a major value. On the other side diversity is detrimental to common technological solutions, and it is an obstacle to mutual understanding. An appropriate environment abstraction and a shared information model are needed to provide the required levels of interoperability in our heterogeneous habitat. This thesis reviews several approaches to support environment related applications and intends to demonstrate that smart-space-based, ontology-driven, information-sharing platforms may become a flexible and powerful solution to support interoperable services in virtually any domain and even in cross-domain scenarios. It also shows that semantic technologies can be fruitfully applied not only to represent application domain knowledge. For example semantic modeling of Human-Computer Interaction may support interaction interoperability and transformation of interaction primitives into actions, and the thesis shows how smart-space-based platforms driven by an interaction ontology may enable natural ad flexible ways of accessing resources and services, e.g, with gestures. An ontology for computational flow execution has also been built to represent abstract computation, with the goal of exploring new ways of scheduling computation flows with smart-space-based semantic platforms.

Semantic under-determinacy, Content and Context

The aim of the thesis is to investigate the topic of semantic under-determinacy, i.e. the failure of the semantic content of certain expressions to determine a truth-evaluable utterance content. In the first part of the thesis, I engage with the problem of setting apart semantic under-determinacy as opposed to other phenomena such as ambiguity, vagueness, indexicality. As I will argue, the feature that distinguishes semantic under-determinacy from these phenomena is its being explainable solely in terms of under-articulation. In the second part of the thesis, I discuss the topic of how communication is possible, despite the semantic under-determinacy of language. I discuss a number of answers that have been offered: (i) the Radical Contextualist explanation which emphasises the role of pragmatic processes in utterance comprehension; (ii) the Indexicalist explanation in terms of hidden syntactic positions; (iii) the Relativist account, which regards sentences as true or false relative to extra coordinates in the circumstances of evaluation (besides possible worlds). In the final chapter, I propose an account of the comprehension of utterances of semantically under-determined sentences in terms of conceptual constraints, i.e. ways of organising information which regulate thought and discourse on certain matters. Conceptual constraints help the hearer to work out the truth-conditions of an utterance of a semantically under-determined sentence. Their role is clearly semantic, in that they contribute to “what is said” (rather than to “what is implied”); however, they do not respond to any syntactic constraint. The view I propose therefore differs, on the one hand, from Radical Contextualism, because it stresses the role of semantic-governed processes as opposed to pragmatics-governed processes; on the other hand, it differs from Indexicalism in its not endorsing any commitment as to hidden syntactic positions; and it differs from Relativism in that it maintains a monadic notion if truth.

A Semantic-based Framework for Digital Survey of Architectural Heritage

The research aims at developing a framework for semantic-based digital survey of architectural heritage. Rooted in knowledge-based modeling which extracts mathematical constraints of geometry from architectural treatises, as-built information of architecture obtained from image-based modeling is integrated with the ideal model in BIM platform. The knowledge-based modeling transforms the geometry and parametric relation of architectural components from 2D printings to 3D digital models, and create large amount variations based on shape grammar in real time thanks to parametric modeling. It also provides prior knowledge for semantically segmenting unorganized survey data. The emergence of SfM (Structure from Motion) provides access to reconstruct large complex architectural scenes with high flexibility, low cost and full automation, but low reliability of metric accuracy. We solve this problem by combing photogrammetric approaches which consists of camera configuration, image enhancement, and bundle adjustment, etc. Experiments show the accuracy of image-based modeling following our workflow is comparable to that from range-based modeling. We also demonstrate positive results of our optimized approach in digital reconstruction of portico where low-texture-vault and dramatical transition of illumination bring huge difficulties in the workflow without optimization. Once the as-built model is obtained, it is integrated with the ideal model in BIM platform which allows multiple data enrichment. In spite of its promising prospect in AEC industry, BIM is developed with limited consideration of reverse-engineering from survey data. Besides representing the architectural heritage in parallel ways (ideal model and as-built model) and comparing their difference, we concern how to create as-built model in BIM software which is still an open area to be addressed. The research is supposed to be fundamental for research of architectural history, documentation and conservation of architectural heritage, and renovation of existing buildings.

Learning Methods and Algorithms for Semantic Text Classification across Multiple Domains

Information is nowadays a key resource: machine learning and data mining techniques have been developed to extract high-level information from great amounts of data. As most data comes in form of unstructured text in natural languages, research on text mining is currently very active and dealing with practical problems. Among these, text categorization deals with the automatic organization of large quantities of documents in priorly defined taxonomies of topic categories, possibly arranged in large hierarchies. In commonly proposed machine learning approaches, classifiers are automatically trained from pre-labeled documents: they can perform very accurate classification, but often require a consistent training set and notable computational effort. Methods for cross-domain text categorization have been proposed, allowing to leverage a set of labeled documents of one domain to classify those of another one. Most methods use advanced statistical techniques, usually involving tuning of parameters. A first contribution presented here is a method based on nearest centroid classification, where profiles of categories are generated from the known domain and then iteratively adapted to the unknown one. Despite being conceptually simple and having easily tuned parameters, this method achieves state-of-the-art accuracy in most benchmark datasets with fast running times. A second, deeper contribution involves the design of a domain-independent model to distinguish the degree and type of relatedness between arbitrary documents and topics, inferred from the different types of semantic relationships between respective representative words, identified by specific search algorithms. The application of this model is tested on both flat and hierarchical text categorization, where it potentially allows the efficient addition of new categories during classification. Results show that classification accuracy still requires improvements, but models generated from one domain are shown to be effectively able to be reused in a different one.

Semantic Categorization of Unfamiliar Tunes in Older and Younger Adults

The process of learning the categories of new tunes in older and younger adults was examined for this study. Tunes were presented either one or three times along with a category name to see if multiple repetitions aid in category memory. Additionally, toexamine if an association may help some listeners, especially older ones, to better remember category information, some tunes were presented with a short associative fact; this fact was either neutral or emotional. Participants were tested on song recognition,fact recognition, and category memory. For all tasks, there was a benefit of three presentations. There were no age differences in fact recognition. For both song recognition and categorization, the memory burden of a neutral association was lessened when the association was emotional.

A Comparative Study of Two Semantic Systems: Body Russian and Russian Phraseology

Grigorij Kreidlin (Russia). A Comparative Study of Two Semantic Systems: Body Russian and Russian Phraseology. Mr. Kreidlin teaches in the Department of Theoretical and Applied Linguistics of the State University of Humanities in Moscow and worked on this project from August 1996 to July 1998. The classical approach to non-verbal and verbal oral communication is based on a traditional separation of body and mind. Linguists studied words and phrasemes, the products of mind activities, while gestures, facial expressions, postures and other forms of body language were left to anthropologists, psychologists, physiologists, and indeed to anyone but linguists. Only recently have linguists begun to turn their attention to gestures and semiotic and cognitive paradigms are now appearing that raise the question of designing an integral model for the unified description of non-verbal and verbal communicative behaviour. This project attempted to elaborate lexical and semantic fragments of such a model, producing a co-ordinated semantic description of the main Russian gestures (including gestures proper, postures and facial expressions) and their natural language analogues. The concept of emblematic gestures and gestural phrasemes and of their semantic links permitted an appropriate description of the transformation of a body as a purely physical substance into a body as a carrier of essential attributes of Russian culture - the semiotic process called the culturalisation of the human body. Here the human body embodies a system of cultural values and displays them in a text within the area of phraseology and some other important language domains. The goal of this research was to develop a theory that would account for the fundamental peculiarities of the process. The model proposed is based on the unified lexicographic representation of verbal and non-verbal units in the Dictionary of Russian Gestures, which the Mr. Kreidlin had earlier complied in collaboration with a group of his students. The Dictionary was originally oriented only towards reflecting how the lexical competence of Russian body language is represented in the Russian mind. Now a special type of phraseological zone has been designed to reflect explicitly semantic relationships between the gestures in the entries and phrasemes and to provide the necessary information for a detailed description of these. All the definitions, rules of usage and the established correlations are written in a semantic meta-language. Several classes of Russian gestural phrasemes were identified, including those phrasemes and idioms with semantic definitions close to those of the corresponding gestures, those phraseological units that have lost touch with the related gestures (although etymologically they are derived from gestures that have gone out of use), and phrasemes and idioms which have semantic traces or reflexes inherited from the meaning of the related gestures. The basic assumptions and practical considerations underlying the work were as follows. (1) To compare meanings one has to be able to state them. To state the meaning of a gesture or a phraseological expression, one needs a formal semantic meta-language of propositional character that represents the cognitive and mental aspects of the codes. (2) The semantic contrastive analysis of any semiotic codes used in person-to-person communication also requires a single semantic meta-language, i.e. a formal semantic language of description,. This language must be as linguistically and culturally independent as possible and yet must be open to interpretation through any culture and code. Another possible method of conducting comparative verbal-non-verbal semantic research is to work with different semantic meta-languages and semantic nets and to learn how to combine them, translate from one to another, etc. in order to reach a common basis for the subsequent comparison of units. (3) The practical work in defining phraseological units and organising the phraseological zone in the Dictionary of Russian Gestures unexpectedly showed that semantic links between gestures and gestural phrasemes are reflected not only in common semantic elements and syntactic structure of semantic propositions, but also in general and partial cognitive operations that are made over semantic definitions. (4) In comparative semantic analysis one should take into account different values and roles of inner form and image components in the semantic representation of non-verbal and verbal units. (5) For the most part, gestural phrasemes are direct semantic derivatives of gestures. The cognitive and formal techniques can be regarded as typological features for the future functional-semantic classification of gestural phrasemes: two phrasemes whose meaning can be obtained by the same cognitive or purely syntactic operations (or types of operations) over the meanings of the corresponding gestures, belong by definition to one and the same class. The nature of many cognitive operations has not been studied well so far, but the first steps towards its comprehension and description have been taken. The research identified 25 logically possible classes of relationships between a gesture and a gestural phraseme. The calculation is based on theoretically possible formal (set-theory) correlations between signifiers and signified of the non-verbal and verbal units. However, in order to examine which of them are realised in practice a complete semantic and lexicographic description of all (not only central) everyday emblems and gestural phrasemes is required and this unfortunately does not yet exist. Mr. Kreidlin suggests that the results of the comparative analysis of verbal and non-verbal units could also be used in other research areas such as the lexicography of emotions.

Sex Differences in Semantic Processing: Event-Related Brain Potentials Distinguish between Lower and Higher Order Semantic Analysis during Word Reading

Behavioral studies suggest that women and men differ in the strategic elaboration of verbally encoded information especially in the absence of external task demand. However, measuring such covert processing requires other than behavioral data. The present study used event-related potentials to compare sexes in lower and higher order semantic processing during the passive reading of semantically related and unrelated word pairs. Women and men showed the same early context effect in the P1-N1 transition period. This finding indicates that the initial lexical-semantic access is similar in men and women. In contrast, sexes differed in higher order semantic processing. Women showed an earlier and longer lasting context effect in the N400 accompanied by larger signal strength in temporal networks similarly recruited by men and women. The results suggest that women spontaneously conduct a deeper semantic analysis. This leads to faster processing of related words in the active neural networks as reflected in a shorter stability of the N400 map in women. Taken together, the findings demonstrate that there is a selective sex difference in the controlled semantic analysis during passive word reading that is not reflected in different functional organization but in the depth of processing.