931 resultados para Impaired Self-awareness


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Variabilities associated with CMOS evolution affect the yield and performance of current digital designs. FPGAs, which are widely used for fast prototyping and implementation of digital circuits, also suffer from these issues. Proactive approaches start to appear to achieve self-awareness and dynamic adaptation of these devices. To support these techniques we propose the employment of a multi-purpose sensor network. This infrastructure, through adequate use of configuration and automation tools, is able to obtain relevant data along the life cycle of an FPGA. This is realised at a very reduced cost, not only in terms of area or other limited resources, but also regarding the design effort required to define and deploy the measuring infrastructure. Our proposal has been validated by measuring inter-die and intra-die variability in different FPGA families.

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Los sistemas técnicos son cada vez más complejos, incorporan funciones más avanzadas, están más integrados con otros sistemas y trabajan en entornos menos controlados. Todo esto supone unas condiciones más exigentes y con mayor incertidumbre para los sistemas de control, a los que además se demanda un comportamiento más autónomo y fiable. La adaptabilidad de manera autónoma es un reto para tecnologías de control actualmente. El proyecto de investigación ASys propone abordarlo trasladando la responsabilidad de la capacidad de adaptación del sistema de los ingenieros en tiempo de diseño al propio sistema en operación. Esta tesis pretende avanzar en la formulación y materialización técnica de los principios de ASys de cognición y auto-consciencia basadas en modelos y autogestión de los sistemas en tiempo de operación para una autonomía robusta. Para ello el trabajo se ha centrado en la capacidad de auto-conciencia, inspirada en los sistemas biológicos, y se ha explorado la posibilidad de integrarla en la arquitectura de los sistemas de control. Además de la auto-consciencia, se han explorado otros temas relevantes: modelado funcional, modelado de software, tecnología de los patrones, tecnología de componentes, tolerancia a fallos. Se ha analizado el estado de la técnica en los ámbitos pertinentes para las cuestiones de la auto-consciencia y la adaptabilidad en sistemas técnicos: arquitecturas cognitivas, control tolerante a fallos, y arquitecturas software dinámicas y computación autonómica. El marco teórico de ASys existente de sistemas autónomos cognitivos ha sido adaptado para servir de base para este análisis de autoconsciencia y adaptación y para dar sustento conceptual al posterior desarrollo de la solución. La tesis propone una solución general de diseño para la construcción de sistemas autónomos auto-conscientes. La idea central es la integración de un meta-controlador en la arquitectura de control del sistema autónomo, capaz de percibir la estado funcional del sistema de control y, si es necesario, reconfigurarlo en tiempo de operación. Esta solución de metacontrol se ha formalizado en cuatro patrones de diseño: i) el Patrón Metacontrol, que define la integración de un subsistema de metacontrol, responsable de controlar al propio sistema de control a través de la interfaz proporcionada por su plataforma de componentes, ii) el patrón Bucle de Control Epistémico, que define un bucle de control cognitivo basado en el modelos y que se puede aplicar al diseño del metacontrol, iii) el patrón de Reflexión basada en Modelo Profundo propone una solución para construir el modelo ejecutable utilizado por el meta-controlador mediante una transformación de modelo a modelo a partir del modelo de ingeniería del sistema, y, finalmente, iv) el Patrón Metacontrol Funcional, que estructura el meta-controlador en dos bucles, uno para el control de la configuración de los componentes del sistema de control, y otro sobre éste, controlando las funciones que realiza dicha configuración de componentes; de esta manera las consideraciones funcionales y estructurales se desacoplan. La Arquitectura OM y el metamodelo TOMASys son las piezas centrales del marco arquitectónico desarrollado para materializar la solución compuesta de los patrones anteriores. El metamodelo TOMASys ha sido desarrollado para la representación de la estructura y su relación con los requisitos funcionales de cualquier sistema autónomo. La Arquitectura OM es un patrón de referencia para la construcción de una metacontrolador integrando los patrones de diseño propuestos. Este meta-controlador se puede integrar en la arquitectura de cualquier sistema control basado en componentes. El elemento clave de su funcionamiento es un modelo TOMASys del sistema decontrol, que el meta-controlador usa para monitorizarlo y calcular las acciones de reconfiguración necesarias para adaptarlo a las circunstancias en cada momento. Un proceso de ingeniería, complementado con otros recursos, ha sido elaborado para guiar la aplicación del marco arquitectónico OM. Dicho Proceso de Ingeniería OM define la metodología a seguir para construir el subsistema de metacontrol para un sistema autónomo a partir del modelo funcional del mismo. La librería OMJava proporciona una implementación del meta-controlador OM que se puede integrar en el control de cualquier sistema autónomo, independientemente del dominio de la aplicación o de su tecnología de implementación. Para concluir, la solución completa ha sido validada con el desarrollo de un robot móvil autónomo que incorpora un meta-controlador con la Arquitectura OM. Las propiedades de auto-consciencia y adaptación proporcionadas por el meta-controlador han sido validadas en diferentes escenarios de operación del robot, en los que el sistema era capaz de sobreponerse a fallos en el sistema de control mediante reconfiguraciones orquestadas por el metacontrolador. ABSTRACT Technical systems are becoming more complex, they incorporate more advanced functionalities, they are more integrated with other systems and they are deployed in less controlled environments. All this supposes a more demanding and uncertain scenario for control systems, which are also required to be more autonomous and dependable. Autonomous adaptivity is a current challenge for extant control technologies. The ASys research project proposes to address it by moving the responsibility for adaptivity from the engineers at design time to the system at run-time. This thesis has intended to advance in the formulation and technical reification of ASys principles of model-based self-cognition and having systems self-handle at runtime for robust autonomy. For that it has focused on the biologically inspired capability of self-awareness, and explored the possibilities to embed it into the very architecture of control systems. Besides self-awareness, other themes related to the envisioned solution have been explored: functional modeling, software modeling, patterns technology, components technology, fault tolerance. The state of the art in fields relevant for the issues of self-awareness and adaptivity has been analysed: cognitive architectures, fault-tolerant control, and software architectural reflection and autonomic computing. The extant and evolving ASys Theoretical Framework for cognitive autonomous systems has been adapted to provide a basement for this selfhood-centred analysis and to conceptually support the subsequent development of our solution. The thesis proposes a general design solution for building self-aware autonomous systems. Its central idea is the integration of a metacontroller in the control architecture of the autonomous system, capable of perceiving the functional state of the control system and reconfiguring it if necessary at run-time. This metacontrol solution has been formalised into four design patterns: i) the Metacontrol Pattern, which defines the integration of a metacontrol subsystem, controlling the domain control system through an interface provided by its implementation component platform, ii) the Epistemic Control Loop pattern, which defines a modelbased cognitive control loop that can be applied to the design of such a metacontroller, iii) the Deep Model Reflection pattern proposes a solution to produce the online executable model used by the metacontroller by model-to-model transformation from the engineering model, and, finally, iv) the Functional Metacontrol pattern, which proposes to structure the metacontroller in two loops, one for controlling the configuration of components of the controller, and another one on top of the former, controlling the functions being realised by that configuration; this way the functional and structural concerns become decoupled. The OM Architecture and the TOMASys metamodel are the core pieces of the architectural framework developed to reify this patterned solution. The TOMASys metamodel has been developed for representing the structure and its relation to the functional requirements of any autonomous system. The OM architecture is a blueprint for building a metacontroller according to the patterns. This metacontroller can be integrated on top of any component-based control architecture. At the core of its operation lies a TOMASys model of the control system. An engineering process and accompanying assets have been constructed to complete and exploit the architectural framework. The OM Engineering Process defines the process to follow to develop the metacontrol subsystem from the functional model of the controller of the autonomous system. The OMJava library provides a domain and application-independent implementation of an OM Metacontroller than can be used in the implementation phase of OMEP. Finally, the complete solution has been validated in the development of an autonomous mobile robot that incorporates an OM metacontroller. The functional selfawareness and adaptivity properties achieved thanks to the metacontrol system have been validated in different scenarios. In these scenarios the robot was able to overcome failures in the control system thanks to reconfigurations performed by the metacontroller.

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Accurate self-awareness in clients who have had an acquired brain injury (ABI) has been associated with positive outcomes. However, providing intervention that improves clients' self-awareness is a challenging task for occupational therapists. The present paper provides an overview of the literature regarding models to guide intervention, intervention considerations, descriptions of interventions, and research evidence for interventions. Professionals can draw upon cognitive rehabilitation models and specific models of self-awareness. Facilitatory interventions, such as education, feedback, behaviour therapy and psychotherapy have been recommended to a greater extent than compensatory interventions. The development of interventions for improving self-awareness is at an early stage, and research on the effectiveness of interventions is limited. Future research is required into the effectiveness of interventions to improve clients' self-awareness before structured intervention guidelines can be developed.

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Unawareness related to brain injury has implications for participation in rehabilitation, functional outcomes, and the emotional well-being of clients. Addressing disorders of awareness is an integral component of many rehabilitation programmes, and a review of the literature identified a range of awareness interventions that include holistic milieu-oriented neuropsychological programmes, psychotherapy, compensatory and facilitatory approaches, structured experiences, direct feedback, videotaped feedback, confrontational techniques, cognitive therapy, group therapy, game formats and behavioural intervention. These approaches are examined in terms of their theoretical bases and research evidence. A distinction is made between intervention approaches for unawareness due to neurocognitive factors and approaches for unawareness due to psychological factors. The socio-cultural context of unawareness is a third factor presented in a biopsychosocial framework to guide clinical decisions about awareness interventions. The ethical and methodological concerns associated with research on awareness interventions are discussed. The main considerations relate to the embedded nature of awareness interventions within rehabilitation programmes, the need for individually tailored interventions, differing responses according to the nature of unawareness, and the risk of eliciting emotional distress in some clients.

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Individuals seeking compensation following traumatic brain injury (TBI) are often found to report a disproportionately high level of symptoms relative to objective indicators of impairment. Previous studies highlight that level of symptom reporting is also related to self-awareness, causal attribution, and emotional wellbeing. Therefore, the reasons for high symptom reporting in the context of compensation are generally unclear. This study aimed to identify whether self-awareness, causal attribution, and emotional wellbeing are significantly associated with level of symptom reporting after controlling for compensation status. A sample of 54 participants with TBI comprised two groups, namely, claimants (n = 27) and non-claimants (n = 27), who were similar in terms of demographic and neuro-cognitive variables. Participants completed the Symptom Expectancy Checklist, Hospital Anxiety Depression Scale, Awareness Questionnaire and a causal attribution scale. A series of independent t tests and Pearson's correlations identified that a higher level of symptom reporting was associated with the following: seeking compensation, less severe TBI, increased age, greater self-awareness, increased post-injury changes reported by relatives, a higher level of mood symptoms, and a tendency to blame other people. Multivariate analysis identified that after controlling for demographic, injury, and compensation status variables, level of mood symptoms and self-awareness were significantly associated with level of symptom reporting. The findings suggest that mood symptoms and heightened self-awareness are significantly related to high symptom reporting independent of compensation status, thus supporting the need for clinicians to interpret symptom reporting within a biopsychosocial context.

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Considerable emphasis has been placed upon cognitive neuropsychological explanations of awareness disorders in brain injury and Alzheimer's disease (AD), with relatively few models acknowledging the role of psychosocial factors. The present paper explores clinical presentations of unawareness in brain injury and AD, reviews the evidence for the influence of psychosocial factors alongside neuropsychological changes, and considers a number of key issues that theoretical models need to address, before going on to discuss some recently-developed models that offer the potential for developing a comprehensive biopsychosocial account. Building on these developments, we present a framework designed to assist clinicians to identify the specific factors contributing to an individual's presentation of unawareness, and illustrate its application with a case example.

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Visual perception is dependent not only on low-level sensory input but also on high-level cognitive factors such as attention. In this paper, we sought to determine whether attentional processes can be internally monitored for the purpose of enhancing behavioural performance. To do so, we developed a novel paradigm involving an orientation discrimination task in which observers had the freedom to delay target presentation--by any amount required--until they judged their attentional focus to be complete. Our results show that discrimination performance is significantly improved when individuals self-monitor their level of visual attention and respond only when they perceive it to be maximal. Although target delay times varied widely from trial-to-trial (range 860 ms-12.84 s), we show that their distribution is Gaussian when plotted on a reciprocal latency scale. We further show that the neural basis of the delay times for judging attentional status is well explained by a linear rise-to-threshold model. We conclude that attentional mechanisms can be self-monitored for the purpose of enhancing human decision-making processes, and that the neural basis of such processes can be understood in terms of a simple, yet broadly applicable, linear rise-to-threshold model.

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High-level cognitive factors, including self-awareness, are believed to play an important role in human visual perception. The principal aim of this study was to determine whether oscillatory brain rhythms play a role in the neural processes involved in self-monitoring attentional status. To do so we measured cortical activity using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) while participants were asked to self-monitor their internal status, only initiating the presentation of a stimulus when they perceived their attentional focus to be maximal. We employed a hierarchical Bayesian method that uses fMRI results as soft-constrained spatial information to solve the MEG inverse problem, allowing us to estimate cortical currents in the order of millimeters and milliseconds. Our results show that, during self-monitoring of internal status, there was a sustained decrease in power within the 7-13 Hz (alpha) range in the rostral cingulate motor area (rCMA) on the human medial wall, beginning approximately 430 msec after the trial start (p < 0.05, FDR corrected). We also show that gamma-band power (41-47 Hz) within this area was positively correlated with task performance from 40-640 msec after the trial start (r = 0.71, p < 0.05). We conclude: (1) the rCMA is involved in processes governing self-monitoring of internal status; and (2) the qualitative differences between alpha and gamma activity are reflective of their different roles in self-monitoring internal states. We suggest that alpha suppression may reflect a strengthening of top-down interareal connections, while a positive correlation between gamma activity and task performance indicates that gamma may play an important role in guiding visuomotor behavior. © 2013 Yamagishi et al.

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Novel computing systems are increasingly being composed of large numbers of heterogeneous components, each with potentially different goals or local perspectives, and connected in networks which change over time. Management of such systems quickly becomes infeasible for humans. As such, future computing systems should be able to achieve advanced levels of autonomous behaviour. In this context, the system's ability to be self-aware and be able to self-express becomes important. This paper surveys definitions and current understanding of self-awareness and self-expression in biology and cognitive science. Subsequently, previous efforts to apply these concepts to computing systems are described. This has enabled the development of novel working definitions for self-awareness and self-expression within the context of computing systems.

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The psychosis phenotype is thought to exist on a continuum, such that the same symptoms experienced by individuals diagnosed with psychotic disorders can also manifest in the general population to a less severe degree. The subclinical psychotic-like experiences reported by healthy individuals share a number of risk factors with psychotic disorders and confer greater risk of developing a psychotic disorder. Thus, healthy individuals with psychotic-like experiences comprise a valid population in which to study the underlying mechanisms of clinically significant psychotic symptoms. In this thesis, we aimed to further our understanding of psychotic-like experiences and the individuals who report them. We explored the relationships between tasks measuring different aspects of self-awareness and self-reported psychotic-like experiences using data obtained from 30 university students. We found that greater sensitivity to the difference between one’s own voice and another person’s voice predicted fewer symptoms of persecutory ideation. Additionally, we found that greater tendency to misattribute one’s own voice to an external source predicted greater symptoms of persecutory ideation.