Intelligent flight control systems

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms

Reconceptualizing major policy change in the advocacy coalition framework: a discourse network analysis of German pension politics

How does major policy change come about? This article identifies and rectifies weaknesses in the conceptualization of innovative policy change in the Advocacy Coalition Framework. In a case study of policy belief change preceding an innovative reform in the German subsystem of old-age security, important new aspects of major policy change are carved out. In particular, the analysis traces a transition from one single hegemonic advocacy coalition to another stable coalition, with a transition phase between the two equilibria. The transition phase is characterized (i) by a bipolarization of policy beliefs in the subsystem and (ii) by state actors with shifting coalition memberships due to policy learning across coalitions or due to executive turnover. Apparently, there are subsystems with specific characteristics (presumably redistributive rather than regulative subsystems) in which one hegemonic coalition is the default, or the "normal state." In these subsystems, polarization and shifting coalition memberships seem to interact to produce coalition turnover and major policy change. The case study is based on discourse network analysis, a combination of qualitative content analysis and social network analysis, which provides an intertemporal measurement of advocacy coalition realignment at the level of policy beliefs in a subsystem

Development of a Computational Model to Predict the In Vivo Contact Mechanics of Modern Total Knee Arthroplasty

This dissertation focuses on the development of a computationally efficient and fast method that incorporates the kinematics obtained from fluoroscopy and extends it to the prediction of the in-vivo contact mechanics at the femoro-tibial articulation in modern knee implants for the deep knee bend activity. In this endeavor, this dissertation deals with the use of an inverse dynamic rigid body model characterizing the slip and roll behavior observed in the femoro-polyethylene articulation and a coupled deformation model where the polyethylene in knee implants are modeled as hexahedral discrete element networks. The performance of this method is tested by comparing force predictions from a telemetric knee and finite element analysis. Finally, the method is applied to study the in vivo contact mechanics and mechanics of the quadriceps mechanism in six popular knee designs. During the deep knee bend activity, the contact force generally increased with flexion. However, the medial lateral forces were not equally distributed and the medial lateral force distribution generally varied from 60%- 40% at full extension to as high as 75%-25% at full flexion in some patients. Also, the magnitude of axial force in the superior-inferior direction was the highest and was found to contribute around 98%-99% of the total load acting at the femorotibial joint. The forces in the medio-lateral and antero-posterior directions were low and the maximum magnitude observed was around 0.5BW. The contact areas and contact pressures were much more sensitive to the geometries involved and the in vivo kinematics. Though no definite pattern was observed for the variation of the contact areas throughout flexion, the contact pressures increased in both condyles with increasing flexion. Also, the contact pressures on the medial condyle were higher than the contact pressures observed in the lateral condyle. The patellofemoral and the quadriceps force ratio increased with the increase in flexion while the patellar ligament and the quadriceps force ratio decreased with increasing flexion. In some patients at high flexion, the quadriceps force and as a result the patellofemoral, patellar ligament and the knee contact forces were found to decrease due to the wrapping of the quadriceps coupled with posterior movement of the femoral condyles leading to the increase in the quadriceps moment arm

An Unsupervised Neural Network for Real-Time Low-Level Control of a Mobile Robot: Noise Resistance, Stability, and Hardware Implementation

We have recently introduced a neural network mobile robot controller (NETMORC). The controller is based on earlier neural network models of biological sensory-motor control. We have shown that NETMORC is able to guide a differential drive mobile robot to an arbitrary stationary or moving target while compensating for noise and other forms of disturbance, such as wheel slippage or changes in the robot's plant. Furthermore, NETMORC is able to adapt in response to long-term changes in the robot's plant, such as a change in the radius of the wheels. In this article we first review the NETMORC architecture, and then we prove that NETMORC is asymptotically stable. After presenting a series of simulations results showing robustness to disturbances, we compare NETMORC performance on a trajectory-following task with the performance of an alternative controller. Finally, we describe preliminary results on the hardware implementation of NETMORC with the mobile robot ROBUTER.Sloan Fellowship (BR-3122), Air Force Office of Scientific Research (F49620-92-J-0499

Dynamic reconfiguration of human brain networks during learning

Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior. These two attributes -- flexibility and selection -- must operate over multiple temporal scales as performance of a skill changes from being slow and challenging to being fast and automatic. Such selective adaptability is naturally provided by modular structure, which plays a critical role in evolution, development, and optimal network function. Using functional connectivity measurements of brain activity acquired from initial training through mastery of a simple motor skill, we explore the role of modularity in human learning by identifying dynamic changes of modular organization spanning multiple temporal scales. Our results indicate that flexibility, which we measure by the allegiance of nodes to modules, in one experimental session predicts the relative amount of learning in a future session. We also develop a general statistical framework for the identification of modular architectures in evolving systems, which is broadly applicable to disciplines where network adaptability is crucial to the understanding of system performance.Comment: Main Text: 19 pages, 4 figures Supplementary Materials: 34 pages, 4 figures, 3 table

Deficits in sound pattern sequencing in children with specific language impairment: A networks approach

Children with specific language impairment (SLI) demonstrate primary deficits in morphosyntax, which has served as the central theme in theoretical and clinical approaches. However, a striking number of children with SLI also exhibit speech sound deficits, characterized both by increased error patterns and by high levels of variability. These speech sound deficits have been under-studied and are not explicitly tied to accounts of SLI. In the present study, theoretical approaches drawn from dynamical systems and sequence learning are used to address speech production learning in children with SLI. Standard approaches to sound accuracy and variability and articulatory variability are integrated with novel applications of network science to assess sound learning trajectories over time. ^ The purpose of the present study was to examine how measures of accuracy and variability are related when assessing nonword production over three sessions. A networks approach is proposed that highlights quantitative and qualitative relationships of sound sequences. Results demonstrate that children with SLI are less accurate and more variable, yet there is a dissociation between these two indices. Examination of movement trajectories reveals that group differences in performance cannot be accounted for solely by articulatory ability. There is a strong correlation between segmental variability and the networks measures, and the information provided by this novel methodology demonstrates gaps in classic approaches to error analysis. Results suggest that children with SLI have difficulty with sound sequencing, and that network science may capture error patterns that classic approaches do not

Enhancing infotainment applications quality of service in vehicular ad hoc networks

Les réseaux ad hoc de véhicules accueillent une multitude d’applications intéressantes. Parmi celles-ci, les applications d’info-divertissement visent à améliorer l’expérience des passagers. Ces applications ont des exigences rigides en termes de délai de livraison et de débit. De nombreuses approches ont été proposées pour assurer la qualité du service des dites applications. Elles sont réparties en deux couches : réseau et contrôle d’accès. Toutefois, ces méthodes présentent plusieurs lacunes. Cette thèse a trois volets. Le premier aborde la question du routage dans le milieu urbain. A cet égard, un nouveau protocole, appelé SCRP, a été proposé. Il exploite l’information sur la circulation des véhicules en temps réel pour créer des épines dorsales sur les routes et les connecter aux intersections à l’aide des nœuds de pont. Ces derniers collectent des informations concernant la connectivité et le délai, utilisées pour choisir les chemins de routage ayant un délai de bout-en-bout faible. Le deuxième s’attaque au problème d’affectation des canaux de services afin d’augmenter le débit. A cet effet, un nouveau mécanisme, appelé ASSCH, a été conçu. ASSCH collecte des informations sur les canaux en temps réel et les donne à un modèle stochastique afin de prédire leurs états dans l’avenir. Les canaux les moins encombrés sont sélectionnés pour être utilisés. Le dernier volet vise à proposer un modèle analytique pour examiner la performance du mécanisme EDCA de la norme IEEE 802.11p. Ce modèle tient en compte plusieurs facteurs, dont l’opportunité de transmission, non exploitée dans IEEE 802.11p.The fact that vehicular ad hoc network accommodates two types of communications, Vehicle-to-Vehicle and Vehicle-to-Infrastructure, has opened the door for a plethora of interesting applications to thrive. Some of these applications, known as infotainment applications, focus on enhancing the passengers' experience. They have rigid requirements in terms of delivery delay and throughput. Numerous approaches have been proposed, at medium access control and routing layers, to enhance the quality of service of such applications. However, existing schemes have several shortcomings. Subsequently, the design of new and efficient approaches is vital for the proper functioning of infotainment applications. This work proposes three schemes. The first is a novel routing protocol, labeled SCRP. It leverages real-time vehicular traffic information to create backbones over road segments and connect them at intersections using bridge nodes. These nodes are responsible for collecting connectivity and delay information, which are used to select routing paths with low end-to-end delay. The second is an altruistic service channel selection scheme, labeled ASSCH. It first collects real-time service channels information and feeds it to a stochastic model that predicts the state of these channels in the near future. The least congested channels are then selected to be used. The third is an analytical model for the performance of the IEEE 802.11p Enhanced Distributed Channel Access mechanism that considers various factors, including the transmission opportunity (TXOP), unexploited by IEEE 802.11p

Network analysis of multivariate data in psychological science

Stress and Psychopatholog