925 resultados para 700103 Information processing services


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The Brazilian Network for Continuous Monitoring of GNSS - RBMC is a national network of continuously operating reference GNSS stations. Since its establishment in December of 1996, it has been playing an essential role for the maintenance and user access of the fundamental geodetic frame in the country. In order to provide better services for RBMC, the Brazilian Institute of Geography and Statistics - IBGE and the National Institute of Colonization and Land Reform - INCRA are both partners involved in the National Geospatial Framework Project - PIGN. This paper provides an overview of the recent modernization phases the RBMC network has undergone highlighting its future steps. These steps involve the installation of new equipment, provide real time data from a group of core stations and compute real-time DGPS corrections, based on CDGPS (The real-time Canada-Wide DGPS Service) (The Real-Time Canada-Wide DGPS Service. http://www.cdgps.com/ 2009a). In addition to this, a post-mission Precise Point Positioning (PPP) service has been established based on the current Geodetic Survey Division of NRCan (CSRS-PPP) service. This service is operational since April 2009 and is in large use in the country. All activities mentioned before are based on a cooperation signed at the end of 2004 with the University of New Brunswick, supported by the Canadian International Development Agency and the Brazilian Cooperation Agency. The Geodetic Survey Division of NRCan is also participating in this modernization effort under the same project. This infrastructure of 66 GNSS stations, the real time, post processing services and the potentiality of providing Wide Area DGPS corrections in the future show that the RBMC system is comparable to those available in USA and Europe. © Springer-Verlag Berlin Heidelberg 2012.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Abstract Background Recent medical and biological technology advances have stimulated the development of new testing systems that have been providing huge, varied amounts of molecular and clinical data. Growing data volumes pose significant challenges for information processing systems in research centers. Additionally, the routines of genomics laboratory are typically characterized by high parallelism in testing and constant procedure changes. Results This paper describes a formal approach to address this challenge through the implementation of a genetic testing management system applied to human genome laboratory. We introduced the Human Genome Research Center Information System (CEGH) in Brazil, a system that is able to support constant changes in human genome testing and can provide patients updated results based on the most recent and validated genetic knowledge. Our approach uses a common repository for process planning to ensure reusability, specification, instantiation, monitoring, and execution of processes, which are defined using a relational database and rigorous control flow specifications based on process algebra (ACP). The main difference between our approach and related works is that we were able to join two important aspects: 1) process scalability achieved through relational database implementation, and 2) correctness of processes using process algebra. Furthermore, the software allows end users to define genetic testing without requiring any knowledge about business process notation or process algebra. Conclusions This paper presents the CEGH information system that is a Laboratory Information Management System (LIMS) based on a formal framework to support genetic testing management for Mendelian disorder studies. We have proved the feasibility and showed usability benefits of a rigorous approach that is able to specify, validate, and perform genetic testing using easy end user interfaces.

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OBJECTIVE: To investigate whether autistic subjects show a different pattern of neural activity than healthy individuals during processing of faces and complex patterns. METHODS: Blood oxygen level-dependent (BOLD) signal changes accompanying visual processing of faces and complex patterns were analyzed in an autistic group (n = 7; 25.3 [6.9] years) and a control group (n = 7; 27.7 [7.8] years). RESULTS: Compared with unaffected subjects, autistic subjects demonstrated lower BOLD signals in the fusiform gyrus, most prominently during face processing, and higher signals in the more object-related medial occipital gyrus. Further signal increases in autistic subjects vs controls were found in regions highly important for visual search: the superior parietal lobule and the medial frontal gyrus, where the frontal eye fields are located. CONCLUSIONS: The cortical activation pattern during face processing indicates deficits in the face-specific regions, with higher activations in regions involved in visual search. These findings reflect different strategies for visual processing, supporting models that propose a predisposition to local rather than global modes of information processing in autism.

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Linking the physical world to the Internet, also known as the Internet of Things, has increased available information and services in everyday life and in the Enterprise world. In Enterprise IT an increasing number of communication is done between IT backend systems and small IoT devices, for example sensor networks or RFID readers. This introduces some challenges in terms of complexity and integration. We are working on the integration of IoT devices into Enterprise IT by leveraging SOA techniques and Semantic Web technologies. We present a SOA based integration platform for connecting WSNs and large enterprise business processes. For ensuring interoperability our platform is based on Linked Services. These are thoroughly described, machine-readable, machine-reasonable service descriptions.

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Strategies of cognitive control are helpful in reducing anxiety experienced during anticipation of unpleasant or potentially unpleasant events. We investigated the associated cerebral information processing underlying the use of a specific cognitive control strategy during the anticipation of affect-laden events. Using functional magnetic resonance imaging, we examined differential brain activity during anticipation of events of unknown and negative emotional valence in a group of eighteen healthy subjects that used a cognitive control strategy, similar to "reality checking" as used in psychotherapy, compared with a group of sixteen subjects that did not exert cognitive control. While expecting unpleasant stimuli, the "cognitive control" group showed higher activity in left medial and dorsolateral prefrontal cortex areas but reduced activity in the left extended amygdala, pulvinar/lateral geniculate nucleus and fusiform gyrus. Cognitive control during the "unknown" expectation was associated with reduced amygdalar activity as well and further with reduced insular and thalamic activity. The amygdala activations associated with cognitive control correlated negatively with the reappraisal scores of an emotion regulation questionnaire. The results indicate that cognitive control of particularly unpleasant emotions is associated with elevated prefrontal cortex activity that may serve to attenuate emotion processing in for instance amygdala, and, notably, in perception related brain areas.

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Individuals differ in their preference for processing information on the basis of taxonomic, feature-based similarity, or thematic, relation-based similarity. These differences, which have been investigated in a recently emerging research stream in cognitive psychology, affect innovative behavior and thus constitute an important antecedent of individual performance in research and development (R&D) that has been overlooked so far in the literature on innovation management. To fill this research gap, survey and test data from the employees of a multinational information technology services firm are used to examine the relationship between thematic thinking and R&D professionals' individual performance. A moderated mediation model is applied to investigate the proposed relationships of thematic thinking and individual-level performance indicators. Results show a positive relationship between thematic thinking and innovativeness, as well as individual job performance. While the results do not support the postulated moderation of the innovativeness–job performance relationship by employees' political skill, they show that the relationship between thematic thinking and job performance is fully mediated by R&D professionals' innovativeness. The present study is thus the first to reveal a positive relationship between thematic thinking and innovative performance.

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Background. Among Hispanics, the HPV vaccine has the potential to eliminate disparities in cervical cancer incidence and mortality but only if optimal rates of vaccination are achieved. Media can be an important information source for increasing HPV knowledge and awareness of the vaccine. Very little is known about how media use among Hispanics affects their HPV knowledge and vaccine awareness. Even less is known about what differences exist in media use and information processing among English- and Spanish-speaking Hispanics.^ Aims. Examine the relationships between three health communication variables (media exposure, HPV-specific information scanning and seeking) and three HPV outcomes (knowledge, vaccine awareness and initiation) among English- and Spanish-speaking Hispanics.^ Methods. Cross-sectional data from a survey administered to Hispanic mothers in Dallas, Texas was used for univariate and multivariate logistic regression analyses. Sample used for analysis included 288 mothers of females aged 8-22 recruited from clinics and community events. Dependent variables of interest were HPV knowledge, HPV vaccine awareness and initiation. Independent variables were media exposure, HPV-specific information scanning and seeking. Language was tested as an effect modifier on the relationship between health communication variables and HPV outcomes.^ Results. English-speaking mothers reported more media exposure, HPV-specific information scanning and seeking than Spanish-speakers. Scanning for HPV information was associated with more HPV knowledge (OR = 4.26, 95% CI = 2.41 - 7.51), vaccine awareness (OR = 10.01, 95% CI = 5.43 - 18.47) and vaccine initiation (OR = 2.54, 95% CI = 1.09 - 5.91). Seeking HPV-specific information was associated with more knowledge (OR = 2.27, 95% CI = 1.23 - 4.16), awareness (OR = 6.60, 95% CI = 2.74 - 15.91) and initiation (OR = 4.93, 95% CI = 2.64 - 9.20). Language moderated the effect of information scanning and seeking on vaccine awareness.^ Discussion. Differences in information scanning and seeking behaviors among Hispanic subgroups have the potential to lead to disparities in vaccine awareness.^ Conclusion. Findings from this study underscore health communication differences among Hispanics and emphasize the need to target Spanish language media as well as English language media aimed at Hispanics to improve knowledge and awareness.^

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Once admitted the advantages of object-based classification compared to pixel-based classification; the need of simple and affordable methods to define and characterize objects to be classified, appears. This paper presents a new methodology for the identification and characterization of objects at different scales, through the integration of spectral information provided by the multispectral image, and textural information from the corresponding panchromatic image. In this way, it has defined a set of objects that yields a simplified representation of the information contained in the two source images. These objects can be characterized by different attributes that allow discriminating between different spectral&textural patterns. This methodology facilitates information processing, from a conceptual and computational point of view. Thus the vectors of attributes defined can be used directly as training pattern input for certain classifiers, as for example artificial neural networks. Growing Cell Structures have been used to classify the merged information.

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Extracting opinions and emotions from text is becoming increasingly important, especially since the advent of micro-blogging and social networking. Opinion mining is particularly popular and now gathers many public services, datasets and lexical resources. Unfortunately, there are few available lexical and semantic resources for emotion recognition that could foster the development of new emotion aware services and applications. The diversity of theories of emotion and the absence of a common vocabulary are two of the main barriers to the development of such resources. This situation motivated the creation of Onyx, a semantic vocabulary of emotions with a focus on lexical resources and emotion analysis services. It follows a linguistic Linked Data approach, it is aligned with the Provenance Ontology, and it has been integrated with the Lexicon Model for Ontologies (lemon), a popular RDF model for representing lexical entries. This approach also means a new and interesting way to work with different theories of emotion. As part of this work, Onyx has been aligned with EmotionML and WordNet-Affect.

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A Administração Financeira surge no início do século XIX juntamente com o movimento de consolidação das grandes empresas e a formação dos mercados nacionais americano enquanto que no Brasil os primeiros estudos ocorrem a partir da segunda metade do século XX. Desde entãoo país conseguiu consolidar alguns centros de excelência em pesquisa, formar grupo significativo de pesquisadores seniores e expandir as áreas de pesquisa no campo, contudo, ainda são poucos os trabalhos que buscam retratar as características da produtividade científica em Finanças. Buscando contribuir para a melhor compreensão do comportamento produtivo dessa área a presente pesquisa estuda sua produção científica, materializada na forma de artigos digitais, publicados em 24 conceituados periódicos nacionais classificados nos estratos Qualis/CAPES A2, B1 e B2 da Área de Administração, Ciências Contábeis e Turismo. Para tanto são aplicadas a Lei de Bradford, Lei do Elitismo de Price e Lei de Lotka. Pela Lei de Bradford são identificadas três zonas de produtividade sendo o núcleo formado por três revistas, estando uma delas classificada no estrato Qualis/CAPES B2, o que evidencia a limitação de um recorte tendo como único critério a classificação Qualis/CAPES. Para a Lei do Elitismo de Price, seja pela contagem direta ou completa, não identificamos comportamento de uma elite semelhante ao apontado pela teoria e que conta com grande número de autores com apenas uma publicação.Aplicando-se o modelo do Poder Inverso Generalizado, calculado por Mínimos Quadrados Ordinários (MQO), verificamos que produtividade dos pesquisadores, quando feita pela contagem direta, se adequa àquela definida pela Lei de Lotka ao nível de α = 0,01 de significância, contudo, pela contagem completa não podemos confirmar a hipótese de homogeneidade das distribuições, além do fato de que nas duas contagens a produtividade analisada pelo parâmetro n é maior que 2 e, portanto, a produtividade do pesquisadores de finanças é menor que a defendida pela teoria.

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This paper addresses the problem of the automatic recognition and classification of temporal expressions and events in human language. Efficacy in these tasks is crucial if the broader task of temporal information processing is to be successfully performed. We analyze whether the application of semantic knowledge to these tasks improves the performance of current approaches. We therefore present and evaluate a data-driven approach as part of a system: TIPSem. Our approach uses lexical semantics and semantic roles as additional information to extend classical approaches which are principally based on morphosyntax. The results obtained for English show that semantic knowledge aids in temporal expression and event recognition, achieving an error reduction of 59% and 21%, while in classification the contribution is limited. From the analysis of the results it may be concluded that the application of semantic knowledge leads to more general models and aids in the recognition of temporal entities that are ambiguous at shallower language analysis levels. We also discovered that lexical semantics and semantic roles have complementary advantages, and that it is useful to combine them. Finally, we carried out the same analysis for Spanish. The results obtained show comparable advantages. This supports the hypothesis that applying the proposed semantic knowledge may be useful for different languages.

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With the quick advance of web service technologies, end-users can conduct various on-line tasks, such as shopping on-line. Usually, end-users compose a set of services to accomplish a task, and need to enter values to services to invoke the composite services. Quite often, users re-visit websites and use services to perform re-occurring tasks. The users are required to enter the same information into various web services to accomplish such re-occurring tasks. However, repetitively typing the same information into services is a tedious job for end-users. It can negatively impact user experience when an end-user needs to type the re-occurring information repetitively into web services. Recent studies have proposed several approaches to help users fill in values to services automatically. However, prior studies mainly suffer the following drawbacks: (1) limited support of collecting and analyzing user inputs; (2) poor accuracy of filling values to services; (3) not designed for service composition. To overcome the aforementioned drawbacks, we need maximize the reuse of previous user inputs across services and end-users. In this thesis, we introduce our approaches that prevent end-users from entering the same information into repetitive on-line tasks. More specifically, we improve the process of filling out services in the following 4 aspects: First, we investigate the characteristics of input parameters. We propose an ontology-based approach to automatically categorize parameters and fill values to the categorized input parameters. Second, we propose a comprehensive framework that leverages user contexts and usage patterns into the process of filling values to services. Third, we propose an approach for maximizing the value propagation among services and end-users by linking a set of semantically related parameters together and similar end-users. Last, we propose a ranking-based framework that ranks a list of previous user inputs for an input parameter to save a user from unnecessary data entries. Our framework learns and analyzes interactions of user inputs and input parameters to rank user inputs for input parameters under different contexts.