234,757 research outputs found

    Complex Event Processing (CEP)

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    Event-driven information systems demand a systematic and automatic processing of events. Complex Event Processing (CEP) encompasses methods, techniques, and tools for processing events while they occur, i.e., in a continuous and timely fashion. CEP derives valuable higher-level knowledge from lower-level events; this knowledge takes the form of so called complex events, that is, situations that can only be recognized as a combination of several events. 1 Application Areas Service Oriented Architecture (SOA), Event-Driven Architecture (EDA), cost-reductions in sensor technology and the monitoring of IT systems due to legal, contractual, or operational concerns have lead to a significantly increased generation of events in computer systems in recent years. This development is accompanied by a demand to manage and process these events in an automatic, systematic, and timely fashion. Important application areas for Complex Event Processing (CEP) are the following

    Complex Event Processing Modeling by Prioritized Colored Petri Nets

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    Complex event processing (CEP) is a technology that allows us to process and correlate large volumes of data by using event patterns, aiming at promptly detecting specific situations that could require special treatment. The event types and event patterns for a particular application domain are implemented by using an event processing language (EPL). Although some current model-driven tools allow end users to easily define these patterns, which are then transformed automatically into a particular EPL, the generated code is syntactically but not semantically validated. To deal with this problem, a prioritized colored Petri net (PCPN) model for CEP is proposed and conducted in this paper. This well-known graphical formalism together with CPNTools makes possible the modeling, simulation, analysis, and semantic validation of complex event-based systems. To illustrate this approach, a case study is presented, as well as a discussion on the benefits from using PCPN for modeling CEP-based systems.El procesamiento de eventos complejos (CEP) es una tecnología que nos permite procesar y correlacionar grandes volúmenes de datos utilizando patrones de eventos, con el objetivo de detectar rápidamente situaciones específicas que podrían requerir un tratamiento especial. Los tipos de eventos y patrones de eventos para un dominio de aplicación particular se implementan utilizando un lenguaje de procesamiento de eventos (EPL). Aunque algunas herramientas actuales impulsadas por modelos permiten a los usuarios finales definir fácilmente estos patrones, que luego se transforman automáticamente en un EPL particular, el código generado se valida sintácticamente pero no semánticamente. Para abordar este problema, en este documento se propone y lleva a cabo un modelo de red de Petri coloreada y priorizada (PCPN) para CEP. Este formalismo gráfico bien conocido junto con CPNTools hace posible la modelización, simulación, análisis y validación semántica de sistemas basados en eventos complejos. Para ilustrar este enfoque, se presenta un estudio de caso, así como una discusión sobre los beneficios de usar PCPN para modelar sistemas basados en CEP.This work was supported in part by the Spanish Ministry of Science and Innovation and the European Union FEDER Funds with the Project DArDOS entitled Formal development and analysis of complex systems in distributed contexts: foundations, tools and applications under Grant TIN2015-65845-C3, subprojects 2-R and 3-R, and the Research Network on Services Science and Engineering under Grant TIN2014-53986-REDT, and in part by the University of Cádiz under Project PR2016-032

    Folk Theory of Mind: Conceptual Foundations of Social Cognition

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    The human ability to represent, conceptualize, and reason about mind and behavior is one of the greatest achievements of human evolution and is made possible by a “folk theory of mind” — a sophisticated conceptual framework that relates different mental states to each other and connects them to behavior. This chapter examines the nature and elements of this framework and its central functions for social cognition. As a conceptual framework, the folk theory of mind operates prior to any particular conscious or unconscious cognition and provides the “framing” or interpretation of that cognition. Central to this framing is the concept of intentionality, which distinguishes intentional action (caused by the agent’s intention and decision) from unintentional behavior (caused by internal or external events without the intervention of the agent’s decision). A second important distinction separates publicly observable from publicly unobservable (i.e., mental) events. Together, the two distinctions define the kinds of events in social interaction that people attend to, wonder about, and try to explain. A special focus of this chapter is the powerful tool of behavior explanation, which relies on the folk theory of mind but is also intimately tied to social demands and to the perceiver’s social goals. A full understanding of social cognition must consider the folk theory of mind as the conceptual underpinning of all (conscious and unconscious) perception and thinking about the social world
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