179,363 research outputs found

    Errata corrige: “The matching problem for behavioral systems”

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    Preferences for systems of psychotherapy and beliefs about the causes of depression

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    Despite multiple treatments being equally effective in treating depression, individuals may have preferences for which intervention they receive. There has been evidence that psychotherapy is preferred over medication or other professional treatments. Psychotherapy, however, is a broad term that does not capture the reality of diverse systems of therapy available to consumers. Therefore, the current study hypothesized that if given the choice between conceptually different types of psychotherapy, individuals would express a preference for at least one treatment over the others. Results from 221 college students indicate that when offered descriptions of problem-solving, cognitive, interpersonal, or behavioral activation therapies, both cognitive and problem-solving therapy are preferred treatments. Additionally, the current work incorporated factors that may influence the preferences measured. Specifically, a person\u27s beliefs about the causes of depression may better explain preferences. Therefore, the current study hypothesized that scores on the Reasons for Depression questionnaire (RFD; Addis, Truax, & Jacobson, 1995) would be higher or lower across each of the treatment options. For those that preferred behavioral activation therapy, every reason for depression was elevated indicating that participants in this group may believe depression is caused by a complex variety of reasons. Implications for future research in treatment preferences and treatment matching are discussed

    Business Process Retrieval Based on Behavioral Semantics

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    This paper develops a framework for retrieving business processes considering search requirements based on behavioral semantics properties; it presents a framework called "BeMantics" for retrieving business processes based on structural, linguistics, and behavioral semantics properties. The relevance of the framework is evaluated retrieving business processes from a repository, and collecting a set of relevant business processes manually issued by human judges. The "BeMantics" framework scored high precision values (0.717) but low recall values (0.558), which implies that even when the framework avoided false negatives, it prone to false positives. The highest pre- cision value was scored in the linguistic criterion showing that using semantic inference in the tasks comparison allowed to reduce around 23.6 % the number of false positives. Using semantic inference to compare tasks of business processes can improve the precision; but if the ontologies are from narrow and specific domains, they limit the semantic expressiveness obtained with ontologies from more general domains. Regarding the perform- ance, it can be improved by using a filter phase which indexes business processes taking into account behavioral semantics propertie

    Toward a unified PNT, Part 1: Complexity and context: Key challenges of multisensor positioning

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    The next generation of navigation and positioning systems must provide greater accuracy and reliability in a range of challenging environments to meet the needs of a variety of mission-critical applications. No single navigation technology is robust enough to meet these requirements on its own, so a multisensor solution is required. Known environmental features, such as signs, buildings, terrain height variation, and magnetic anomalies, may or may not be available for positioning. The system could be stationary, carried by a pedestrian, or on any type of land, sea, or air vehicle. Furthermore, for many applications, the environment and host behavior are subject to change. A multi-sensor solution is thus required. The expert knowledge problem is compounded by the fact that different modules in an integrated navigation system are often supplied by different organizations, who may be reluctant to share necessary design information if this is considered to be intellectual property that must be protected

    Static and Dynamic Detection of Behavioral Conflicts Between Aspects

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    Aspects have been successfully promoted as a means to improve the modularization of software in the presence of crosscutting concerns. The so-called aspect interference problem is considered to be one of the remaining challenges of aspect-oriented software development: aspects may interfere with the behavior of the base code or other aspects. Especially interference between aspects is difficult to prevent, as this may be caused solely by the composition of aspects that behave correctly in isolation. A typical situation where this may occur is when multiple advices are applied at a shared, join point.\ud In [1] we explained the problem of behavioral conflicts between aspects at shared join points. We presented an approach for the detection of behavioral conflicts. This approach is based on a novel abstraction model for representing the behavior of advice. This model allows the expression of both primitive and complex behavior in a simple manner. This supports automatic conflict detection. The presented approach employs a set of conflict detection rules, which can be used to detect generic, domain specific and application specific conflicts. The approach is implemented in Compose*, which is an implementation of Composition Filters. This application shows that a declarative advice language can be exploited for aiding automated conflict detection.\ud This paper discusses the need for a runtime extension to the described static approach. It also presents a possible implementation approach of such an extension in Compose*. This allows us to reason efficiently about the behavior of aspects. It also enables us to detect these conflicts with minimal overhead at runtime

    Components Interoperability through Mediating Connector Patterns

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    A key objective for ubiquitous environments is to enable system interoperability between system's components that are highly heterogeneous. In particular, the challenge is to embed in the system architecture the necessary support to cope with behavioral diversity in order to allow components to coordinate and communicate. The continuously evolving environment further asks for an automated and on-the-fly approach. In this paper we present the design building blocks for the dynamic and on-the-fly interoperability between heterogeneous components. Specifically, we describe an Architectural Pattern called Mediating Connector, that is the key enabler for communication. In addition, we present a set of Basic Mediator Patterns, that describe the basic mismatches which can occur when components try to interact, and their corresponding solutions.Comment: In Proceedings WCSI 2010, arXiv:1010.233

    The Complementary Brain: From Brain Dynamics To Conscious Experiences

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    How do our brains so effectively achieve adaptive behavior in a changing world? Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within each stream and parallel interactions between streams create coherent behavioral representations that overcome the complementary deficiencies of each stream and support unitary conscious experiences. This perspective suggests how brain design reflects the organization of the physical world with which brains interact, and suggests an alternative to the computer metaphor suggesting that brains are organized into independent modules. Examples from perception, learning, cognition, and action are described, and theoretical concepts and mechanisms by which complementarity is accomplished are summarized.Defense Advanced Research Projects and the Office of Naval Research (N00014-95-1-0409); National Science Foundation (ITI-97-20333); Office of Naval Research (N00014-95-1-0657
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