Joint U.S./Japan Conference on Adaptive Structures, 1st, Maui, HI, Nov. 13-15, 1990, Proceedings

NASA Astrophysics Data System (ADS)

Wada, Ben K.; Fanson, James L.; Miura, Koryo

1991-11-01

The present volume of adaptive structures discusses the development of control laws for an orbiting tethered antenna/reflector system test scale model, the sizing of active piezoelectric struts for vibration suppression on a space-based interferometer, the control design of a space station mobile transporter with multiple constraints, and optimum configuration control of an intelligent truss structure. Attention is given to the formulation of full state feedback for infinite order structural systems, robustness issues in the design of smart structures, passive piezoelectric vibration damping, shape control experiments with a functional model for large optical reflectors, and a mathematical basis for the design optimization of adaptive trusses in precision control. Topics addressed include approaches to the optimal adaptive geometries of intelligent truss structures, the design of an automated manufacturing system for tubular smart structures, the Sandia structural control experiments, and the zero-gravity dynamics of space structures in parabolic aircraft flight.

Advanced controls for light sources

NASA Astrophysics Data System (ADS)

Biedron, S. G.; Edelen, A. L.; Milton, S. V.

2016-09-01

We present a summary of our team's recent efforts in developing adaptive, artificial intelligence-inspired techniques specifically to address several control challenges that arise in machines/systems including those in particle accelerator systems. These techniques can readily be adapted to other systems such as lasers, beamline optics, etc… We are not at all suggesting that we create an autonomous system, but create a system with an intelligent control system, that can continually use operational data to improve itself and combines both traditional and advanced techniques. We believe that the system performance and reliability can be increased based on our findings. Another related point is that the controls sub-system of an overall system is usually not the heart of the system architecture or design process. More bluntly, often times all of the peripheral systems are considered as secondary to the main system components in the architecture design process because it is assumed that the controls system will be able to "fix" challenges found later with the sub-systems for overall system operation. We will show that this is not always the case and that it took an intelligent control application to overcome a sub-system's challenges. We will provide a recent example of such a "fix" with a standard controller and with an artificial intelligence-inspired controller. A final related point to be covered is that of system adaptation for requirements not original to a system's original design.

Realizing Autonomy via Intelligent Hybrid Control: Adaptable Autonomy for Achieving UxV RSTA Team Decision Superiority (also known as Intelligent Multi-UxV Planner with Adaptive Collaborative/Control Technologies (IMPACT))

DTIC Science & Technology

2018-01-30

algorithms. Due to this, Fusion was built with the goal of extensibility throughout the architecture. The Fusion infrastructure enables software...DISTRIBUTION STATEMENT A: Approved for public release. Cleared, 88PA, Case# 2018-0820. b. Trigger a Highly Mobile ...modes were developed in IMPACT (i.e., normal full coverage patrol (NFCP) and highly mobile (HM)). In both NFCP and HM, all UxVs patrol their assigned

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

NASA Technical Reports Server (NTRS)

Bosworth, John T.; Williams-Hayes, Peggy S.

2007-01-01

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

NASA Technical Reports Server (NTRS)

Bosworth, John T.; Williams-Hayes, Peggy S.

2010-01-01

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Failure of Working Memory Training to Enhance Cognition or Intelligence

PubMed Central

Thompson, Todd W.; Waskom, Michael L.; Garel, Keri-Lee A.; Cardenas-Iniguez, Carlos; Reynolds, Gretchen O.; Winter, Rebecca; Chang, Patricia; Pollard, Kiersten; Lala, Nupur; Alvarez, George A.; Gabrieli, John D. E.

2013-01-01

Fluid intelligence is important for successful functioning in the modern world, but much evidence suggests that fluid intelligence is largely immutable after childhood. Recently, however, researchers have reported gains in fluid intelligence after multiple sessions of adaptive working memory training in adults. The current study attempted to replicate and expand those results by administering a broad assessment of cognitive abilities and personality traits to young adults who underwent 20 sessions of an adaptive dual n-back working memory training program and comparing their post-training performance on those tests to a matched set of young adults who underwent 20 sessions of an adaptive attentional tracking program. Pre- and post-training measurements of fluid intelligence, standardized intelligence tests, speed of processing, reading skills, and other tests of working memory were assessed. Both training groups exhibited substantial and specific improvements on the trained tasks that persisted for at least 6 months post-training, but no transfer of improvement was observed to any of the non-trained measurements when compared to a third untrained group serving as a passive control. These findings fail to support the idea that adaptive working memory training in healthy young adults enhances working memory capacity in non-trained tasks, fluid intelligence, or other measures of cognitive abilities. PMID:23717453

Adaptive Urban Signal Control and Integration (AUSCI) : evaluation final report

DOT National Transportation Integrated Search

2000-10-01

This report presents an evaluation of the Adaptive Urban Signal Control and Integration (AUSCI) Intelligent Transportation System (ITS) Field Operational Test in Minneapolis, Minnesota. The project involved a 56-intersection portion of Minneapolis, e...

Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)

DTIC Science & Technology

2007-04-01

weight will be reduced by replacing heavy harness assemblies and FADECs , with distributed processing elements interconnected. This paper reviews...Digital Electronic Controls ( FADECs ), with distributed processing elements interconnected through a serial bus. Efficient data flow throughout the...because intelligence is embedded in components while overall control is maintained in the FADEC . The need for Distributed Control Systems in

Intelligent robot trends and predictions for the .net future

NASA Astrophysics Data System (ADS)

Hall, Ernest L.

2001-10-01

An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The use of these machines in factory automation can improve productivity, increase product quality and improve competitiveness. This paper presents a discussion of recent and future technical and economic trends. During the past twenty years the use of industrial robots that are equipped not only with precise motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. Intelligent robot products have been developed in many cases for factory automation and for some hospital and home applications. To reach an even higher degree of applications, the addition of learning may be required. Recently, learning theories such as the adaptive critic have been proposed. In this type of learning, a critic provides a grade to the controller of an action module such as a robot. The adaptive critic is a good model for human learning. In general, the critic may be considered to be the human with the teach pendant, plant manager, line supervisor, quality inspector or the consumer. If the ultimate critic is the consumer, then the quality inspector must model the consumer's decision-making process and use this model in the design and manufacturing operations. Can the adaptive critic be used to advance intelligent robots? Intelligent robots have historically taken decades to be developed and reduced to practice. Methods for speeding this development include technology such as rapid prototyping and product development and government, industry and university cooperation.

Control Automation in Undersea Search and Manipulation

NASA Technical Reports Server (NTRS)

Weltman, Gershon; Freedy, Amos

1974-01-01

Automatic decision making and control mechanisms of the type termed "adaptive" or "intelligent" offer unique advantages for exploration and manipulation of the undersea environment, particularly at great depths. Because they are able to carry out human-like functions autonomously, such mechanisms can aid and extend the capabilities of the human operator. This paper reviews past and present work in the areas of adaptive control and robotics with the purpose of establishing logical guidelines for the application of automatic techniques underwater. Experimental research data are used to illustrate the importance of information feedback, personnel training, and methods of control allocation in the interaction between operator and intelligent machine.

A Probabilistic System Analysis of Intelligent Propulsion System Technologies

NASA Technical Reports Server (NTRS)

Tong, Michael T.

2007-01-01

NASA s Intelligent Propulsion System Technology (Propulsion 21) project focuses on developing adaptive technologies that will enable commercial gas turbine engines to produce fewer emissions and less noise while increasing reliability. It features adaptive technologies that have included active tip-clearance control for turbine and compressor, active combustion control, turbine aero-thermal and flow control, and enabling technologies such as sensors which are reliable at high operating temperatures and are minimally intrusive. A probabilistic system analysis is performed to evaluate the impact of these technologies on aircraft CO2 (directly proportional to fuel burn) and LTO (landing and takeoff) NO(x) reductions. A 300-passenger aircraft, with two 396-kN thrust (85,000-pound) engines is chosen for the study. The results show that NASA s Intelligent Propulsion System technologies have the potential to significantly reduce the CO2 and NO(x) emissions. The results are used to support informed decisionmaking on the development of the intelligent propulsion system technology portfolio for CO2 and NO(x) reductions.

Intelligent control based on fuzzy logic and neural net theory

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

Embedded intelligent adaptive PI controller for an electromechanical system.

PubMed

El-Nagar, Ahmad M

2016-09-01

In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Certification Considerations for Adaptive Systems

NASA Technical Reports Server (NTRS)

Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

2015-01-01

Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2008-01-01

Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

Intelligent Adaptive Systems: Literature Research of Design Guidance for Intelligent Adaptive Automation and Interfaces

DTIC Science & Technology

2007-09-01

behaviour based on past experience of interacting with the operator), and mobile (i.e., can move themselves from one machine to another). Edwards argues that...Sofge, D., Bugajska, M., Adams, W., Perzanowski, D., and Schultz, A. (2003). Agent-based Multimodal Interface for Dynamically Autonomous Mobile Robots...based architecture can provide a natural and scalable approach to implementing a multimodal interface to control mobile robots through dynamic

Compact Microscope Imaging System With Intelligent Controls Improved

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The Compact Microscope Imaging System (CMIS) with intelligent controls is a diagnostic microscope analysis tool with intelligent controls for use in space, industrial, medical, and security applications. This compact miniature microscope, which can perform tasks usually reserved for conventional microscopes, has unique advantages in the fields of microscopy, biomedical research, inline process inspection, and space science. Its unique approach integrates a machine vision technique with an instrumentation and control technique that provides intelligence via the use of adaptive neural networks. The CMIS system was developed at the NASA Glenn Research Center specifically for interface detection used for colloid hard spheres experiments; biological cell detection for patch clamping, cell movement, and tracking; and detection of anode and cathode defects for laboratory samples using microscope technology.

An Intelligent Propulsion Control Architecture to Enable More Autonomous Vehicle Operation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Sowers, T. Shane; Simon, Donald L.; Owen, A. Karl; Rinehart, Aidan W.; Chicatelli, Amy K.; Acheson, Michael J.; Hueschen, Richard M.; Spiers, Christopher W.

2018-01-01

This paper describes an intelligent propulsion control architecture that coordinates with the flight control to reduce the amount of pilot intervention required to operate the vehicle. Objectives of the architecture include the ability to: automatically recognize the aircraft operating state and flight phase; configure engine control to optimize performance with knowledge of engine condition and capability; enhance aircraft performance by coordinating propulsion control with flight control; and recognize off-nominal propulsion situations and to respond to them autonomously. The hierarchical intelligent propulsion system control can be decomposed into a propulsion system level and an individual engine level. The architecture is designed to be flexible to accommodate evolving requirements, adapt to technology improvements, and maintain safety.

Intelligent failure-tolerant control

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1991-01-01

An overview of failure-tolerant control is presented, beginning with robust control, progressing through parallel and analytical redundancy, and ending with rule-based systems and artificial neural networks. By design or implementation, failure-tolerant control systems are 'intelligent' systems. All failure-tolerant systems require some degrees of robustness to protect against catastrophic failure; failure tolerance often can be improved by adaptivity in decision-making and control, as well as by redundancy in measurement and actuation. Reliability, maintainability, and survivability can be enhanced by failure tolerance, although each objective poses different goals for control system design. Artificial intelligence concepts are helpful for integrating and codifying failure-tolerant control systems, not as alternatives but as adjuncts to conventional design methods.

Adaptive quantum computation in changing environments using projective simulation

NASA Astrophysics Data System (ADS)

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-08-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks.

Adaptive quantum computation in changing environments using projective simulation

PubMed Central

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-01-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks. PMID:26260263

On the Effectiveness of a Neural Network for Adaptive External Pacing.

ERIC Educational Resources Information Center

Montazemi, Ali R.; Wang, Feng

1995-01-01

Proposes a neural network model for an intelligent tutoring system featuring adaptive external control of student pacing. An experiment was conducted, and students using adaptive external pacing experienced improved mastery learning and increased motivation for time management. Contains 66 references. (JKP)

An Architecture and Methodology for Creating a Domain-Independent, Plan-Based Intelligent Tutoring System.

ERIC Educational Resources Information Center

Vassileva, Julita

1990-01-01

Discusses the structure of intelligent tutoring systems (ITSs) and describes the development of a new structure for ITSs that is not domain dependent and is more readily adaptable by individual teachers. Pedagogical rules that help decide how much student control versus how much teacher control is present in the system are discussed. (14…

Intelligent neural network and fuzzy logic control of industrial and power systems

NASA Astrophysics Data System (ADS)

Kuljaca, Ognjen

The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of adaptive and neural network control systems, as well as for the analysis of the different algorithms such as elastic fuzzy systems.

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Enhancing TSM&O strategies through life cycle benefit/cost analysis : life cycle benefit/cost analysis & life cycle assessment of adaptive traffic control systems and ramp metering systems.

DOT National Transportation Integrated Search

2015-05-01

The research team developed a comprehensive Benefit/Cost (B/C) analysis framework to evaluate existing and anticipated : intelligent transportation system (ITS) strategies, particularly, adaptive traffic control systems and ramp metering systems, : i...

Energy-saving technology of vector controlled induction motor based on the adaptive neuro-controller

NASA Astrophysics Data System (ADS)

Engel, E.; Kovalev, I. V.; Karandeev, D.

2015-10-01

The ongoing evolution of the power system towards a Smart Grid implies an important role of intelligent technologies, but poses strict requirements on their control schemes to preserve stability and controllability. This paper presents the adaptive neuro-controller for the vector control of induction motor within Smart Gird. The validity and effectiveness of the proposed energy-saving technology of vector controlled induction motor based on adaptive neuro-controller are verified by simulation results at different operating conditions over a wide speed range of induction motor.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

PubMed

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-05-30

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

PubMed Central

Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

2017-01-01

The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control. PMID:28556817

Intelligent Systems For Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

KrishnaKumar, K.

2003-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Intelligent Systems for Aerospace Engineering: An Overview

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2002-01-01

Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become extremely important for advancing the current trends in information technology. Artificially intelligent systems currently utilize computers to emulate various faculties of human intelligence and biological metaphors. They use a combination of symbolic and sub-symbolic systems capable of evolving human cognitive skills and intelligence, not just systems capable of doing things humans do not do well. Intelligent systems are ideally suited for tasks such as search and optimization, pattern recognition and matching, planning, uncertainty management, control, and adaptation. In this paper, the intelligent system technologies and their application potential are highlighted via several examples.

Soundscape elaboration from anthrophonic adaptation of community noise

NASA Astrophysics Data System (ADS)

Teddy Badai Samodra, FX

2018-03-01

Under the situation of an urban environment, noise has been a critical issue in affecting the indoor environment. A reliable approach is required for evaluation of the community noise as one factor of anthrophonic in the urban environment. This research investigates the level of noise exposure from different community noise sources and elaborates the advantage of the noise disadvantages for soundscape innovation. Integrated building element design as a protector for noise control and speech intelligibility compliance using field experiment and MATLAB programming and modeling are also carried out. Meanwhile, for simulation analysis and building acoustic optimization, Sound Reduction-Speech Intelligibility and Reverberation Time are the main parameters for identifying tropical building model as case study object. The results show that the noise control should consider its integration with the other critical issue, thermal control, in an urban environment. The 1.1 second of reverberation time for speech activities and noise reduction more than 28.66 dBA for critical frequency (20 Hz), the speech intelligibility index could be reached more than fair assessment, 0.45. Furthermore, the environmental psychology adaptation result “Close The Opening” as the best method in high noise condition and personal adjustment as the easiest and the most adaptable way.

Controls and Health Management Technologies for Intelligent Aerospace Propulsion Systems

NASA Technical Reports Server (NTRS)

Garg, Sanjay

2004-01-01

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Technology Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of an Intelligent Engine. The key enabling technologies for an Intelligent Engine are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Technology Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Intelligent fault-tolerant controllers

NASA Technical Reports Server (NTRS)

Huang, Chien Y.

1987-01-01

A system with fault tolerant controls is one that can detect, isolate, and estimate failures and perform necessary control reconfiguration based on this new information. Artificial intelligence (AI) is concerned with semantic processing, and it has evolved to include the topics of expert systems and machine learning. This research represents an attempt to apply AI to fault tolerant controls, hence, the name intelligent fault tolerant control (IFTC). A generic solution to the problem is sought, providing a system based on logic in addition to analytical tools, and offering machine learning capabilities. The advantages are that redundant system specific algorithms are no longer needed, that reasonableness is used to quickly choose the correct control strategy, and that the system can adapt to new situations by learning about its effects on system dynamics.

Sensor Needs for Control and Health Management of Intelligent Aircraft Engines

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Gang, Sanjay; Hunter, Gary W.; Guo, Ten-Huei; Semega, Kenneth J.

2004-01-01

NASA and the U.S. Department of Defense are conducting programs which support the future vision of "intelligent" aircraft engines for enhancing the affordability, performance, operability, safety, and reliability of aircraft propulsion systems. Intelligent engines will have advanced control and health management capabilities enabling these engines to be self-diagnostic, self-prognostic, and adaptive to optimize performance based upon the current condition of the engine or the current mission of the vehicle. Sensors are a critical technology necessary to enable the intelligent engine vision as they are relied upon to accurately collect the data required for engine control and health management. This paper reviews the anticipated sensor requirements to support the future vision of intelligent engines from a control and health management perspective. Propulsion control and health management technologies are discussed in the broad areas of active component controls, propulsion health management and distributed controls. In each of these three areas individual technologies will be described, input parameters necessary for control feedback or health management will be discussed, and sensor performance specifications for measuring these parameters will be summarized.

Intelligent Control Systems Research

NASA Technical Reports Server (NTRS)

Loparo, Kenneth A.

1994-01-01

Results of a three phase research program into intelligent control systems are presented. The first phase looked at implementing the lowest or direct level of a hierarchical control scheme using a reinforcement learning approach assuming no a priori information about the system under control. The second phase involved the design of an adaptive/optimizing level of the hierarchy and its interaction with the direct control level. The third and final phase of the research was aimed at combining the results of the previous phases with some a priori information about the controlled system.

Adaptive neural network/expert system that learns fault diagnosis for different structures

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

Corporations need better real-time monitoring and control systems to improve productivity by watching quality and increasing production flexibility. The innovative technology to achieve this goal is evolving in the form artificial intelligence and neural networks applied to sensor processing, fusion, and interpretation. By using these advanced Al techniques, we can leverage existing systems and add value to conventional techniques. Neural networks and knowledge-based expert systems can be combined into intelligent sensor systems which provide real-time monitoring, control, evaluation, and fault diagnosis for production systems. Neural network-based intelligent sensor systems are more reliable because they can provide continuous, non-destructive monitoring and inspection. Use of neural networks can result in sensor fusion and the ability to model highly, non-linear systems. Improved models can provide a foundation for more accurate performance parameters and predictions. We discuss a research software/hardware prototype which integrates neural networks, expert systems, and sensor technologies and which can adapt across a variety of structures to perform fault diagnosis. The flexibility and adaptability of the prototype in learning two structures is presented. Potential applications are discussed.

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

Identification and control of a multizone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.; Singh, N. B.

1992-01-01

This paper presents an intelligent adaptive control system for the control of a solid-liquid interface of a crystal while it is growing via directional solidification inside a multizone transparent furnace. The task of the process controller is to establish a user-specified axial temperature profile and to maintain a desirable interface shape. Both single-input-single-output and multi-input-multi-output adaptive pole placement algorithms have been used to control the temperature. Also described is an intelligent measurement system to assess the shape of the crystal while it is growing. A color video imaging system observes the crystal in real time and determines the position and the shape of the interface. This information is used to evaluate the crystal growth rate, and to analyze the effects of translational velocity and temperature profiles on the shape of the interface. Creation of this knowledge base is the first step to incorporate image processing into furnace control.

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Adaptive Control of Visually Guided Grasping in Neural Networks

DTIC Science & Technology

1990-03-12

D.P. Shankweiler, M. Studdert-Kennedy (1967) Perception of the speech code, Psychol. Rev. 74, 43 1. J. Piaget ( 1952 ), The Origins of Intelligence in...Coordination, IEEE Control Systems Magazine.V9:3 p.25-30 Piaget , J. ( 1952 ), The Origins of Intelligence in Children, translated by M.Cook, (International...University Press, New York. Piaget , J. (1954) The Construction of Reality in the Child, Translated by M. Cook , Ballentine Books, New York - 24-

Intelligent control of robotic arm/hand systems for the NASA EVA retriever using neural networks

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

Adaptive/general learning algorithms using varying neural network models are considered for the intelligent control of robotic arm plus dextrous hand/manipulator systems. Results are summarized and discussed for the use of the Barto/Sutton/Anderson neuronlike, unsupervised learning controller as applied to the stabilization of an inverted pendulum on a cart system. Recommendations are made for the application of the controller and a kinematic analysis for trajectory planning to simple object retrieval (chase/approach and capture/grasp) scenarios in two dimensions.

Relation of intelligence to ego functioning in an adult psychiatric population.

PubMed

Allen, J G; Coyne, L; David, E

1986-01-01

Wechsler Adult Intelligence Scale-Revised (WAIS-R) IQs and clinical ratings of 10 ego functions in a diagnostically heterogeneous sample of 60 adult psychiatric inpatients were correlated. With severity of pathology statistically controlled, higher intelligence was associated with more adequate ego functioning in several spheres: primary autonomous functions, thought processes, object relations, and mastery-competence. There were also some clinically meaningful differences between the Verbal and Performance IQs in the pattern of correlations. Extending Hartmann's original views, the authors employ an ethological framework to conceptualize intelligence in relation to the ego's role in adaptation, emphasizing that intelligence is an important-albeit neglected-aspect of ego functioning.

Adaptive Computerized Instruction.

ERIC Educational Resources Information Center

Ray, Roger D.; And Others

1995-01-01

Describes an artificially intelligent multimedia computerized instruction system capable of developing a conceptual image of what a student is learning while the student is learning it. It focuses on principles of learning and adaptive behavioral control systems theory upon which the system is designed and demonstrates multiple user modes.…

Traveling With Success, How Local Governments Use Intelligent Transportation Systems

DOT National Transportation Integrated Search

1995-01-01

ELECTRONIC TOLL COLLECTION AND TRAFFIC MANAGEMENT OR ETC/ETTM, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS, ADVANCED TRAVELER INFORMATION SYSTEMS OR ATIS, ELECTRONIC PAYMENTS SYSTEMS, TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, TRANSIT MANAGEM...

Conflict resolution and adaptation in normal aging: the role of verbal intelligence and cognitive reserve.

PubMed

Puccioni, Olga; Vallesi, Antonino

2012-12-01

The present study investigated effects of cognitive aging on conflict resolution (the ability to suppress prepotent and distracting, irrelevant information) and conflict adaptation (the adjustment of conflict resolution based on previously experienced conflict level). In addition, it aimed at investigating whether Cognitive Reserve (CR) and intelligence play a compensatory role against age-related deficits in both factors. A color-word Stroop task with no feature repetitions (i.e., neither the word nor the color was repeated in two subsequent trials) was administered to 23 older adults with no dimentia (65-79 years old) and 22 younger controls (18-34 years old), in addition to measures of intelligence and CR. Older adults' performance was characterized by general slowing. However, response slowing inversely correlated with intelligence, education, and a cognitive-reserve index. The Stroop effect (i.e., response-time (RT) difference between incongruent and congruent conditions) was larger in older adults than in younger controls, and in the older group only, it negatively correlated with verbal IQ. With this feature-repetitions-free Stroop task, we confirmed the presence of some conflict adaptation effects, which, however, were spared by aging. Altogether, these findings show that older adults can cope better with age-related impairment in verbal interference resolution, if they have enough intelligence resources in a related (verbal) domain, whereas CR plays a role in general performance speed only. We therefore suggest that general and specific accounts of cognitive aging may apply to different processing stages, which are influenced by partially different compensatory factors. 2013 APA, all rights reserved

[Keeping company in an emotional trip. Emotional intelligence applied to the help relationship].

PubMed

Conangla Marín, M Mercè

2004-03-01

In order to be a good professional and caretaker, it is essential to work on one's capacity to manage one's own feelings and emotions in an adaptable, intelligent manner. This set of abilities form part of the concept known as Emotional Intelligence. One can only give to another what one is and one knows how to give to oneself. The five ability groups which make up affective or emotional intelligence are: self-knowledge, self-control, self-motivation, empathy and relationship abilities. All are necessary in order to carry out good management of our feelings and emotions.

Performance Monitoring and Assessment of Neuro-Adaptive Controllers for Aerospace Applications Using a Bayesian Approach

NASA Technical Reports Server (NTRS)

Gupta, Pramod; Guenther, Kurt; Hodgkinson, John; Jacklin, Stephen; Richard, Michael; Schumann, Johann; Soares, Fola

2005-01-01

Modern exploration missions require modern control systems-control systems that can handle catastrophic changes in the system's behavior, compensate for slow deterioration in sustained operations, and support fast system ID. Adaptive controllers, based upon Neural Networks have these capabilities, but they can only be used safely if proper verification & validation (V&V) can be done. In this paper we present our V & V approach and simulation result within NASA's Intelligent Flight Control Systems (IFCS).

Adaptive fuzzy PID control of hydraulic servo control system for large axial flow compressor

NASA Astrophysics Data System (ADS)

Wang, Yannian; Wu, Peizhi; Liu, Chengtao

2017-09-01

To improve the stability of the large axial compressor, an efficient and special intelligent hydraulic servo control system is designed and implemented. The adaptive fuzzy PID control algorithm is used to control the position of the hydraulic servo cylinder steadily, which overcomes the drawback that the PID parameters should be adjusted based on the different applications. The simulation and the test results show that the system has a better dynamic property and a stable state performance.

Introduction to Advanced Engine Control Concepts

NASA Technical Reports Server (NTRS)

Sanjay, Garg

2007-01-01

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This presentation describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Fluid intelligence and psychosocial outcome: from logical problem solving to social adaptation.

PubMed

Huepe, David; Roca, María; Salas, Natalia; Canales-Johnson, Andrés; Rivera-Rei, Álvaro A; Zamorano, Leandro; Concepción, Aimée; Manes, Facundo; Ibañez, Agustín

2011-01-01

While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized. A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM) and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire), domestic abuse of adolescents (Conflict Tactic Scale), drug intake (ONUDD), self-esteem (Rosenberg's Self Esteem Scale) and the Perceived Mental Health Scale (Spanish adaptation). Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher. Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts.

Fluid Intelligence and Psychosocial Outcome: From Logical Problem Solving to Social Adaptation

PubMed Central

Huepe, David; Roca, María; Salas, Natalia; Canales-Johnson, Andrés; Rivera-Rei, Álvaro A.; Zamorano, Leandro; Concepción, Aimée; Manes, Facundo; Ibañez, Agustín

2011-01-01

Background While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized. Methodology/Principal Findings A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM) and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire), domestic abuse of adolescents (Conflict Tactic Scale), drug intake (ONUDD), self-esteem (Rosenberg's Self Esteem Scale) and the Perceived Mental Health Scale (Spanish adaptation). Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher. Conclusions/Significance Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts. PMID:21957464

An Adaptive Supervisory Sliding Fuzzy Cerebellar Model Articulation Controller for Sensorless Vector-Controlled Induction Motor Drive Systems

PubMed Central

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-01-01

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes—the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC—were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes. PMID:25815450

An adaptive supervisory sliding fuzzy cerebellar model articulation controller for sensorless vector-controlled induction motor drive systems.

PubMed

Wang, Shun-Yuan; Tseng, Chwan-Lu; Lin, Shou-Chuang; Chiu, Chun-Jung; Chou, Jen-Hsiang

2015-03-25

This paper presents the implementation of an adaptive supervisory sliding fuzzy cerebellar model articulation controller (FCMAC) in the speed sensorless vector control of an induction motor (IM) drive system. The proposed adaptive supervisory sliding FCMAC comprised a supervisory controller, integral sliding surface, and an adaptive FCMAC. The integral sliding surface was employed to eliminate steady-state errors and enhance the responsiveness of the system. The adaptive FCMAC incorporated an FCMAC with a compensating controller to perform a desired control action. The proposed controller was derived using the Lyapunov approach, which guarantees learning-error convergence. The implementation of three intelligent control schemes--the adaptive supervisory sliding FCMAC, adaptive sliding FCMAC, and adaptive sliding CMAC--were experimentally investigated under various conditions in a realistic sensorless vector-controlled IM drive system. The root mean square error (RMSE) was used as a performance index to evaluate the experimental results of each control scheme. The analysis results indicated that the proposed adaptive supervisory sliding FCMAC substantially improved the system performance compared with the other control schemes.

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the…

An intelligent CNC machine control system architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, D.J.; Loucks, C.S.

1996-10-01

Intelligent, agile manufacturing relies on automated programming of digitally controlled processes. Currently, processes such as Computer Numerically Controlled (CNC) machining are difficult to automate because of highly restrictive controllers and poor software environments. It is also difficult to utilize sensors and process models for adaptive control, or to integrate machining processes with other tasks within a factory floor setting. As part of a Laboratory Directed Research and Development (LDRD) program, a CNC machine control system architecture based on object-oriented design and graphical programming has been developed to address some of these problems and to demonstrate automated agile machining applications usingmore » platform-independent software.« less

Fuzzy control of burnout of multilayer ceramic actuators

NASA Astrophysics Data System (ADS)

Ling, Alice V.; Voss, David; Christodoulou, Leo

1996-08-01

To improve the yield and repeatability of the burnout process of multilayer ceramic actuators (MCAs), an intelligent processing of materials (IPM-based) control system has been developed for the manufacture of MCAs. IPM involves the active (ultimately adaptive) control of a material process using empirical or analytical models and in situ sensing of critical process states (part features and process parameters) to modify the processing conditions in real time to achieve predefined product goals. Thus, the three enabling technologies for the IPM burnout control system are process modeling, in situ sensing and intelligent control. This paper presents the design of an IPM-based control strategy for the burnout process of MCAs.

NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

NASA Technical Reports Server (NTRS)

2005-01-01

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. Also the propulsion systems required to enable the NASA (National Aeronautics and Space Administration) Vision for Space Exploration in an affordable manner will need to have high reliability, safety and autonomous operation capability. The Controls and Dynamics Branch at NASA Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. The key enabling technologies for an Intelligent Propulsion System are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance operational reliability and component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

Diversity of Emotional Intelligence among Nursing and Medical Students.

PubMed

Chun, Kyung Hee; Park, Euna

2016-08-01

The purpose of this study is to identify the types of perception of emotional intelligence among nursing and medical students and their characteristics using Q methodology, and to build the basic data for the development of a program for the would-be medical professionals to effectively adapt to various clinical settings in which their emotions are involved. Data were collected from 35 nursing and medical students by allowing them to classify 40 Q statements related to emotional intelligence and processed using the PC QUANL program. The perceptions of emotional intelligence by nursing and medical students were categorized into three types: "sensitivity-control type", "sympathy-motivation type", and "concern-sympathy type". The perceptions of emotional intelligence by nursing and medical students can represent an effective coping strategy in a situation where emotion is involved. In the medical profession, an occupation with a high level of emotional labor, it is important to identify the types of emotional intelligence for an effective coping strategy, which may have a positive effect on the performance of an organization. Based on the findings of this study, it is necessary to plan an education program for vocational adaptability for nursing and medical students by their types.

Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

PubMed

Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

2006-04-01

This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control system. Performance of the control system is successfully tested by performing several six-degrees-of-freedom nonlinear simulations.

An Approach to V&V of Embedded Adaptive Systems

NASA Technical Reports Server (NTRS)

Liu, Yan; Yerramalla, Sampath; Fuller, Edgar; Cukic, Bojan; Gururajan, Srikaruth

2004-01-01

Rigorous Verification and Validation (V&V) techniques are essential for high assurance systems. Lately, the performance of some of these systems is enhanced by embedded adaptive components in order to cope with environmental changes. Although the ability of adapting is appealing, it actually poses a problem in terms of V&V. Since uncertainties induced by environmental changes have a significant impact on system behavior, the applicability of conventional V&V techniques is limited. In safety-critical applications such as flight control system, the mechanisms of change must be observed, diagnosed, accommodated and well understood prior to deployment. In this paper, we propose a non-conventional V&V approach suitable for online adaptive systems. We apply our approach to an intelligent flight control system that employs a particular type of Neural Networks (NN) as the adaptive learning paradigm. Presented methodology consists of a novelty detection technique and online stability monitoring tools. The novelty detection technique is based on Support Vector Data Description that detects novel (abnormal) data patterns. The Online Stability Monitoring tools based on Lyapunov's Stability Theory detect unstable learning behavior in neural networks. Cases studies based on a high fidelity simulator of NASA's Intelligent Flight Control System demonstrate a successful application of the presented V&V methodology. ,

The intelligence paradox; will ET get the metabolic syndrome? Lessons from and for Earth.

PubMed

Nunn, Alistair V W; Guy, Geoffrey W; Bell, Jimmy D

2014-01-01

Mankind is facing an unprecedented health challenge in the current pandemic of obesity and diabetes. We propose that this is the inevitable (and predictable) consequence of the evolution of intelligence, which itself could be an expression of life being an information system driven by entropy. Because of its ability to make life more adaptable and robust, intelligence evolved as an efficient adaptive response to the stresses arising from an ever-changing environment. These adaptive responses are encapsulated by the epiphenomena of "hormesis", a phenomenon we believe to be central to the evolution of intelligence and essential for the maintenance of optimal physiological function and health. Thus, as intelligence evolved, it would eventually reach a cognitive level with the ability to control its environment through technology and have the ability remove all stressors. In effect, it would act to remove the very hormetic factors that had driven its evolution. Mankind may have reached this point, creating an environmental utopia that has reduced the very stimuli necessary for optimal health and the evolution of intelligence - "the intelligence paradox". One of the hallmarks of this paradox is of course the rising incidence in obesity, diabetes and the metabolic syndrome. This leads to the conclusion that wherever life evolves, here on earth or in another part of the galaxy, the "intelligence paradox" would be the inevitable side-effect of the evolution of intelligence. ET may not need to just "phone home" but may also need to "phone the local gym". This suggests another possible reason to explain Fermi's paradox; Enrico Fermi, the famous physicist, suggested in the 1950s that if extra-terrestrial intelligence was so prevalent, which was a common belief at the time, then where was it? Our suggestion is that if advanced life has got going elsewhere in our galaxy, it can't afford to explore the galaxy because it has to pay its healthcare costs.

The intelligence paradox; will ET get the metabolic syndrome? Lessons from and for Earth

PubMed Central

2014-01-01

Mankind is facing an unprecedented health challenge in the current pandemic of obesity and diabetes. We propose that this is the inevitable (and predictable) consequence of the evolution of intelligence, which itself could be an expression of life being an information system driven by entropy. Because of its ability to make life more adaptable and robust, intelligence evolved as an efficient adaptive response to the stresses arising from an ever-changing environment. These adaptive responses are encapsulated by the epiphenomena of “hormesis”, a phenomenon we believe to be central to the evolution of intelligence and essential for the maintenance of optimal physiological function and health. Thus, as intelligence evolved, it would eventually reach a cognitive level with the ability to control its environment through technology and have the ability remove all stressors. In effect, it would act to remove the very hormetic factors that had driven its evolution. Mankind may have reached this point, creating an environmental utopia that has reduced the very stimuli necessary for optimal health and the evolution of intelligence – “the intelligence paradox”. One of the hallmarks of this paradox is of course the rising incidence in obesity, diabetes and the metabolic syndrome. This leads to the conclusion that wherever life evolves, here on earth or in another part of the galaxy, the “intelligence paradox” would be the inevitable side-effect of the evolution of intelligence. ET may not need to just “phone home” but may also need to “phone the local gym”. This suggests another possible reason to explain Fermi’s paradox; Enrico Fermi, the famous physicist, suggested in the 1950s that if extra-terrestrial intelligence was so prevalent, which was a common belief at the time, then where was it? Our suggestion is that if advanced life has got going elsewhere in our galaxy, it can’t afford to explore the galaxy because it has to pay its healthcare costs. PMID:25089149

The Intelligent Control System and Experiments for an Unmanned Wave Glider.

PubMed

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the "Ocean Rambler" UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified.

The Intelligent Control System and Experiments for an Unmanned Wave Glider

PubMed Central

Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

2016-01-01

The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the “Ocean Rambler” UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified. PMID:28005956

Flight Test Comparison of Different Adaptive Augmentations for Fault Tolerant Control Laws for a Modified F-15 Aircraft

NASA Technical Reports Server (NTRS)

Burken, John J.; Hanson, Curtis E.; Lee, James A.; Kaneshige, John T.

2009-01-01

This report describes the improvements and enhancements to a neural network based approach for directly adapting to aerodynamic changes resulting from damage or failures. This research is a follow-on effort to flight tests performed on the NASA F-15 aircraft as part of the Intelligent Flight Control System research effort. Previous flight test results demonstrated the potential for performance improvement under destabilizing damage conditions. Little or no improvement was provided under simulated control surface failures, however, and the adaptive system was prone to pilot-induced oscillations. An improved controller was designed to reduce the occurrence of pilot-induced oscillations and increase robustness to failures in general. This report presents an analysis of the neural networks used in the previous flight test, the improved adaptive controller, and the baseline case with no adaptation. Flight test results demonstrate significant improvement in performance by using the new adaptive controller compared with the previous adaptive system and the baseline system for control surface failures.

Statewide Intelligent Transportation Systems As-Is Agency Reports For Minnesota, Volume 6, City Of St. Paul

DOT National Transportation Integrated Search

1996-08-01

KEYWORDS: : TRAFFIC SIGNAL CONTROL/REAL-TIME ADAPTIVE CONTROL, ADVANCED TRAFFIC MANAGEMENT SYSTEMS OR ATMS : THIS DOCUMENT PRESENTS THE METHODS, ASSUMPTIONS AND PROCEDURES USED TO COLLECT THE BASELINE INFORMATION. THE DOCUMENTATION OF SYSTEMS ...

Programming model for distributed intelligent systems

NASA Technical Reports Server (NTRS)

Sztipanovits, J.; Biegl, C.; Karsai, G.; Bogunovic, N.; Purves, B.; Williams, R.; Christiansen, T.

1988-01-01

A programming model and architecture which was developed for the design and implementation of complex, heterogeneous measurement and control systems is described. The Multigraph Architecture integrates artificial intelligence techniques with conventional software technologies, offers a unified framework for distributed and shared memory based parallel computational models and supports multiple programming paradigms. The system can be implemented on different hardware architectures and can be adapted to strongly different applications.

Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

DTIC Science & Technology

1991-06-01

Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

Development of intelligent robots - Achievements and issues

NASA Astrophysics Data System (ADS)

Nitzan, D.

1985-03-01

A flexible, intelligent robot is regarded as a general purpose machine system that may include effectors, sensors, computers, and auxiliary equipment and, like a human, can perform a variety of tasks under unpredictable conditions. Development of intelligent robots is essential for increasing the growth rate of today's robot population in industry and elsewhere. Robotics research and development topics include manipulation, end effectors, mobility, sensing (noncontact and contact), adaptive control, robot programming languages, and manufacturing process planning. Past achievements and current issues related to each of these topics are described briefly.

Final Environmental Impact Statement Establishment and Operation of an Intelligence, Surveillance, Reconnaissance, and Strike Capability Andersen Air Force Base, Guam

DTIC Science & Technology

2007-01-01

Mariana Fruit Bat Pup Recruitment at Pati Point Colony; • Brown Tree Snake Interdiction and Control; and • Adaptive Management and Ground Track...establishment of a mitigation monitoring plan and adaptive management program. FUTURE ACTIONS As discussed in the Final EIS, the Air Force recognizes that...would initiate modifications to aircraft ground tracks and profiles over sensitive areas through an adaptive management strategy. This adaptive

Architecture for Adaptive Intelligent Systems

NASA Technical Reports Server (NTRS)

Hayes-Roth, Barbara

1993-01-01

We identify a class of niches to be occupied by 'adaptive intelligent systems (AISs)'. In contrast with niches occupied by typical AI agents, AIS niches present situations that vary dynamically along several key dimensions: different combinations of required tasks, different configurations of available resources, contextual conditions ranging from benign to stressful, and different performance criteria. We present a small class hierarchy of AIS niches that exhibit these dimensions of variability and describe a particular AIS niche, ICU (intensive care unit) patient monitoring, which we use for illustration throughout the paper. We have designed and implemented an agent architecture that supports all of different kinds of adaptation by exploiting a single underlying theoretical concept: An agent dynamically constructs explicit control plans to guide its choices among situation-triggered behaviors. We illustrate the architecture and its support for adaptation with examples from Guardian, an experimental agent for ICU monitoring.

A generic architecture for an adaptive, interoperable and intelligent type 2 diabetes mellitus care system.

PubMed

Uribe, Gustavo A; Blobel, Bernd; López, Diego M; Schulz, Stefan

2015-01-01

Chronic diseases such as Type 2 Diabetes Mellitus (T2DM) constitute a big burden to the global health economy. T2DM Care Management requires a multi-disciplinary and multi-organizational approach. Because of different languages and terminologies, education, experiences, skills, etc., such an approach establishes a special interoperability challenge. The solution is a flexible, scalable, business-controlled, adaptive, knowledge-based, intelligent system following a systems-oriented, architecture-centric, ontology-based and policy-driven approach. The architecture of real systems is described, using the basics and principles of the Generic Component Model (GCM). For representing the functional aspects of a system the Business Process Modeling Notation (BPMN) is used. The system architecture obtained is presented using a GCM graphical notation, class diagrams and BPMN diagrams. The architecture-centric approach considers the compositional nature of the real world system and its functionalities, guarantees coherence, and provides right inferences. The level of generality provided in this paper facilitates use case specific adaptations of the system. By that way, intelligent, adaptive and interoperable T2DM care systems can be derived from the presented model as presented in another publication.

Performance in noise: Impact of reduced speech intelligibility on Sailor performance in a Navy command and control environment.

PubMed

Keller, M David; Ziriax, John M; Barns, William; Sheffield, Benjamin; Brungart, Douglas; Thomas, Tony; Jaeger, Bobby; Yankaskas, Kurt

2017-06-01

Noise, hearing loss, and electronic signal distortion, which are common problems in military environments, can impair speech intelligibility and thereby jeopardize mission success. The current study investigated the impact that impaired communication has on operational performance in a command and control environment by parametrically degrading speech intelligibility in a simulated shipborne Combat Information Center. Experienced U.S. Navy personnel served as the study participants and were required to monitor information from multiple sources and respond appropriately to communications initiated by investigators playing the roles of other personnel involved in a realistic Naval scenario. In each block of the scenario, an adaptive intelligibility modification system employing automatic gain control was used to adjust the signal-to-noise ratio to achieve one of four speech intelligibility levels on a Modified Rhyme Test: No Loss, 80%, 60%, or 40%. Objective and subjective measures of operational performance suggested that performance systematically degraded with decreasing speech intelligibility, with the largest drop occurring between 80% and 60%. These results confirm the importance of noise reduction, good communication design, and effective hearing conservation programs to maximize the operational effectiveness of military personnel. Published by Elsevier B.V.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

Evaluation of the Fake Resistance of a Forced-choice Paired-comparison Computer Adaptive Personality Measure

DTIC Science & Technology

2008-08-01

version of NCAPS, participants higher in cognitive ability and reading ability were able to produce higher fakability scores. Higher intelligence ... intelligence and reading ability. Therefore, the adaptive paired- comparison NCAPS is very likely to provide scores close to the true trait scores for...regardless of the intelligence or reading levels associated with those taking the adaptive NCAPS; it will be difficult to fake the adaptive paired

A biologically based model for the integration of sensory-motor contingencies in rules and plans: a prefrontal cortex based extension of the Distributed Adaptive Control architecture.

PubMed

Duff, Armin; Fibla, Marti Sanchez; Verschure, Paul F M J

2011-06-30

Intelligence depends on the ability of the brain to acquire and apply rules and representations. At the neuronal level these properties have been shown to critically depend on the prefrontal cortex. Here we present, in the context of the Distributed Adaptive Control architecture (DAC), a biologically based model for flexible control and planning based on key physiological properties of the prefrontal cortex, i.e. reward modulated sustained activity and plasticity of lateral connectivity. We test the model in a series of pertinent tasks, including multiple T-mazes and the Tower of London that are standard experimental tasks to assess flexible control and planning. We show that the model is both able to acquire and express rules that capture the properties of the task and to quickly adapt to changes. Further, we demonstrate that this biomimetic self-contained cognitive architecture generalizes to planning. In addition, we analyze the extended DAC architecture, called DAC 6, as a model that can be applied for the creation of intelligent and psychologically believable synthetic agents. Copyright © 2010 Elsevier Inc. All rights reserved.

Adaptable and adaptive materials for light flux control

NASA Astrophysics Data System (ADS)

Sixou, Pierre; Magnaldo, A.; Nourry, J.; Laye, C.

1996-04-01

The purpose of this paper is to describe and examine properties of light flux control materials. Indeed, intelligent light flux control is necessary not only to improve everyday visual convenience but also in an economical point of view in order to reduce global home energetic cost. Several types of materials are good potential candidates for such functions: (1) The most well-known investigations concern inorganic materials such as tungsten or molybdenum oxides in which an electrochrom layer darkens when enriched in ions, and looses its color when impoverished. Unfortunately, at the moment, there is no convenient way to realize correct ions suppliers. Moreover, other drawbacks arise, such as poor reversibility, reactive interferences or a sensitivity of the material to its environment. These systems only need a low voltage level to work. But, their dynamic response, which is correlated to the component surface, is quite long. (2) At the present time, another attractive issue seems promising. More and more studies concern micro-composite liquid crystal films. For first, we shall remind their principles as well as their way of preparation. After having talked about their main advantages as intelligent materials, we shall discuss their control, their light flux adaptability, or their memory capabilities.

Flight Test Implementation of a Second Generation Intelligent Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2005-01-01

The NASA F-15 Intelligent Flight Control System project team has developed a series of flight control concepts designed to demonstrate the benefits of a neural network-based adaptive controller. The objective of the team was to develop and flight-test control systems that use neural network technology, to optimize the performance of the aircraft under nominal conditions, and to stabilize the aircraft under failure conditions. Failure conditions include locked or failed control surfaces as well as unforeseen damage that might occur to the aircraft in flight. The Intelligent Flight Control System team is currently in the process of implementing a second generation control scheme, collectively known as Generation 2 or Gen 2, for flight testing on the NASA F-15 aircraft. This report describes the Gen 2 system as implemented by the team for flight test evaluation. Simulation results are shown which describe the experiment to be performed in flight and highlight the ways in which the Gen 2 system meets the defined objectives.

Advanced Sensor and Packaging Technologies for Intelligent Adaptive Engine Controls (Preprint)

DTIC Science & Technology

2013-05-01

combination of micro-electromechanical systems (MEMS) sensor technology, novel ceramic materials, high - temperature electronics, and advanced harsh...with simultaneous pressure measurements up to 1,000 psi. The combination of a high - temperature , high -pressure-ratio compressor system, and adaptive...combination of micro-electromechanical systems (MEMS) sensor technology, novel ceramic materials, high temperature electronics, and advanced harsh

Adaptive Inner-Loop Rover Control

NASA Technical Reports Server (NTRS)

Kulkarni, Nilesh; Ippolito, Corey; Krishnakumar, Kalmanje; Al-Ali, Khalid M.

2006-01-01

Adaptive control technology is developed for the inner-loop speed and steering control of the MAX Rover. MAX, a CMU developed rover, is a compact low-cost 4-wheel drive, 4-wheel steer (double Ackerman), high-clearance agile durable chassis, outfitted with sensors and electronics that make it ideally suited for supporting research relevant to intelligent teleoperation and as a low-cost autonomous robotic test bed and appliance. The design consists of a feedback linearization based controller with a proportional - integral (PI) feedback that is augmented by an online adaptive neural network. The adaptation law has guaranteed stability properties for safe operation. The control design is retrofit in nature so that it fits inside the outer-loop path planning algorithms. Successful hardware implementation of the controller is illustrated for several scenarios consisting of actuator failures and modeling errors in the nominal design.

From pilot's associate to satellite controller's associate

NASA Technical Reports Server (NTRS)

Neyland, David L.; Lizza, Carl; Merkel, Philip A.

1992-01-01

Associate technology is an emerging engineering discipline wherein intelligent automation can significantly augment the performance of man-machine systems. An associate system is one that monitors operator activity and adapts its operational behavior accordingly. Associate technology is most effectively applied when mapped into management of the human-machine interface and display-control loop in typical manned systems. This paper addresses the potential for application of associate technology into the arena of intelligent command and control of satellite systems, from diagnosis of onboard and onground of satellite systems fault conditions, to execution of nominal satellite control functions. Rather than specifying a specific solution, this paper draws parallels between the Pilot's Associate concept and the domain of satellite control.

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

NASA Technical Reports Server (NTRS)

Burken, John J.; Larson, Richard R.

2009-01-01

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

A cognitive robotics system: the symbolic and sub-symbolic robotic intelligence control system (SS-RICS)

NASA Astrophysics Data System (ADS)

Kelley, Troy D.; Avery, Eric

2010-04-01

This paper will detail the progress on the development of the Symbolic and Subsymbolic Robotics Intelligence Control System (SS-RICS). The system is a goal oriented production system, based loosely on the cognitive architecture, the Adaptive Control of Thought-Rational (ACT-R) some additions and changes. We have found that in order to simulate complex cognition on a robot, many aspects of cognition (long term memory (LTM), perception) needed to be in place before any generalized intelligent behavior can be produced. In working with ACT-R, we found that it was a good instantiation of working memory, but that we needed to add other aspects of cognition including LTM and perception to have a complete cognitive system. Our progress to date will be noted and the challenges that remain will be addressed.

Laser diodes for sensing applications: adaptive cruise control and more

NASA Astrophysics Data System (ADS)

Heerlein, Joerg; Morgott, Stefan; Ferstl, Christian

2005-02-01

Adaptive Cruise Controls (ACC) and pre-crash sensors require an intelligent eye which can recognize traffic situations and deliver a 3-dimensional view. Both microwave RADAR and "Light RADAR" (LIDAR) systems are well suited as sensors. In order to utilize the advantages of LIDARs -- such as lower cost, simpler assembly and high reliability -- the key component, the laser diode, is of primary importance. Here, we present laser diodes which meet the requirements of the automotive industry.

Verification and Validation of Neural Networks for Aerospace Systems

NASA Technical Reports Server (NTRS)

Mackall, Dale; Nelson, Stacy; Schumman, Johann; Clancy, Daniel (Technical Monitor)

2002-01-01

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: 1) Overview of Adaptive Systems; and 2) V&V Processes/Methods.

Verification and Validation of Neural Networks for Aerospace Systems

NASA Technical Reports Server (NTRS)

Mackall, Dale; Nelson, Stacy; Schumann, Johann

2002-01-01

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: Overview of Adaptive Systems and V&V Processes/Methods.

Industry Cluster's Adaptive Co-competition Behavior Modeling Inspired by Swarm Intelligence

NASA Astrophysics Data System (ADS)

Xiang, Wei; Ye, Feifan

Adaptation helps the individual enterprise to adjust its behavior to uncertainties in environment and hence determines a healthy growth of both the individuals and the whole industry cluster as well. This paper is focused on the study on co-competition adaptation behavior of industry cluster, which is inspired by swarm intelligence mechanisms. By referencing to ant cooperative transportation and ant foraging behavior and their related swarm intelligence approaches, the cooperative adaptation and competitive adaptation behavior are studied and relevant models are proposed. Those adaptive co-competition behaviors model can be integrated to the multi-agent system of industry cluster to make the industry cluster model more realistic.

Genetic mechanism for designing new generation of buildings from data obtained by sensor agent robots

NASA Astrophysics Data System (ADS)

Ono, Chihiro; Mita, Akira

2012-04-01

Due to an increase in an elderly-people household, and global warming, the design of building spaces requires delicate consideration of the needs of elderly-people. Studies of intelligent spaces that can control suitable devices for residents may provide some of functions needed. However, these intelligent spaces are based on predefined scenarios so that it is difficult to handle unexpected circumstances and adapt to the needs of people. This study aims to suggest a Genetic adaption algorithm for building spaces. The feasibility of the algorithm is tested by simulation. The algorithm extend the existing design methodology by reflecting ongoing living information quickly in the variety of patterns.

Intelligent Optical Systems Using Adaptive Optics

NASA Technical Reports Server (NTRS)

Clark, Natalie

2012-01-01

Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

Intelligent Adaptive Interfaces: Summary Report on Design, Development, and Evaluation of Intelligent Adaptive Interfaces for the Control of Multiple UAVs from an Airborne Platform

DTIC Science & Technology

2006-12-01

gestion de la masse d’informations nécessaires pour appuyer la prise de décision efficace. De l’avis des opérateurs d’engins télépilotés...opérateurs d’engins télépilotés risque de croître exponentiellement, de sorte que de fortes contraintes seront imposées au personnel exécutant les missions...commande réelle des engins télépilotés que la gestion des données, y compris la conversion de ces données en information et l’acheminement

Adaptation of the Wechsler Intelligence Scale for Children-IV (WISC-IV) for Vietnam.

PubMed

Dang, Hoang-Minh; Weiss, Bahr; Pollack, Amie; Nguyen, Minh Cao

2012-12-01

Intelligence testing is used for many purposes including identification of children for proper educational placement (e.g., children with learning disabilities, or intellectually gifted students), and to guide education by identifying cognitive strengths and weaknesses so that teachers can adapt their instructional style to students' specific learning styles. Most of the research involving intelligence tests has been conducted in highly developed Western countries, yet the need for intelligence testing is as or even more important in developing countries. The present study, conducted through the Vietnam National University Clinical Psychology CRISP Center , focused on the cultural adaptation of the WISC-IV intelligence test for Vietnam. We report on (a) the adaptation process including the translation, cultural analysis and modifications involved in adaptation, (b) present results of two pilot studies, and (c) describe collection of the standardization sample and results of analyses with the standardization sample, with the goal of sharing our experience with other researchers who may be involved in or interested in adapting or developing IQ tests for non-Western, non-English speaking cultures.

ER fluid applications to vibration control devices and an adaptive neural-net controller

NASA Astrophysics Data System (ADS)

Morishita, Shin; Ura, Tamaki

1993-07-01

Four applications of electrorheological (ER) fluid to vibration control actuators and an adaptive neural-net control system suitable for the controller of ER actuators are described: a shock absorber system for automobiles, a squeeze film damper bearing for rotational machines, a dynamic damper for multidegree-of-freedom structures, and a vibration isolator. An adaptive neural-net control system composed of a forward model network for structural identification and a controller network is introduced for the control system of these ER actuators. As an example study of intelligent vibration control systems, an experiment was performed in which the ER dynamic damper was attached to a beam structure and controlled by the present neural-net controller so that the vibration in several modes of the beam was reduced with a single dynamic damper.

Neuropsychological late effects of treatment for acute leukemia in children with Down syndrome.

PubMed

Roncadin, Caroline; Hitzler, Johann; Downie, Andrea; Montour-Proulx, Isabelle; Alyman, Cheryl; Cairney, Elizabeth; Spiegler, Brenda J

2015-05-01

Children with Down syndrome (DS) have an elevated risk of developing acute leukemia, but little is known about treatment-related neuropsychological morbidity because they are systematically excluded from research in this area. The current study investigated neuropsychological outcomes in children with DS treated for acute lymphoblastic leukemia (ALL) or acute myeloid leukemia (AML) compared to children with DS with no history of cancer. Participants were 4 to 17 years of age at testing and were administered measures of intelligence, academic achievement, language, visual-motor and fine-motor skills, and adaptive function. Patients had been off treatment for at least 2 years. The AML group (N = 12) had significantly lower verbal intelligence and receptive vocabulary compared to controls (N = 21). By contrast, the ALL group (N = 14) performed significantly worse than controls on measures of verbal intelligence, spelling, receptive and expressive vocabulary, visual-motor skills, and adaptive function. Patients with DS treated for AML may have specific post-treatment morbidity in verbal function, whereas those treated for ALL have broader morbidity affecting multiple neuropsychological domains and overall adaptive function. We hypothesize that the broader impairment profile of ALL survivors may be related to a combination of the longer duration of central nervous system-directed treatment for ALL compared to AML and the concomitant limited access to intervention opportunities during active treatment. © 2014 Wiley Periodicals, Inc.

Status, Vision, and Challenges of an Intelligent Distributed Engine Control Architecture (Postprint)

DTIC Science & Technology

2007-09-18

TERMS turbine engine control, engine health management, FADEC , Universal FADEC , Distributed Controls, UF, UF Platform, common FADEC , Generic FADEC ...Modular FADEC , Adaptive Control 16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON (Monitor) a. REPORT Unclassified b. ABSTRACT...Eventually the Full Authority Digital Electronic Control ( FADEC ) became the norm. Presently, this control system architecture accounts for 15 to 20% of

The architecture of adaptive neural network based on a fuzzy inference system for implementing intelligent control in photovoltaic systems

NASA Astrophysics Data System (ADS)

Gimazov, R.; Shidlovskiy, S.

2018-05-01

In this paper, we consider the architecture of the algorithm for extreme regulation in the photovoltaic system. An algorithm based on an adaptive neural network with fuzzy inference is proposed. The implementation of such an algorithm not only allows solving a number of problems in existing algorithms for extreme power regulation of photovoltaic systems, but also creates a reserve for the creation of a universal control system for a photovoltaic system.

Developing Adaptive and Intelligent Tutoring Systems (AITS): A General Framework and Its Implementations

ERIC Educational Resources Information Center

Hafidi, Mohamed; Bensebaa, Tahar

2014-01-01

Several adaptive and intelligent tutoring systems (AITS) have been developed with different variables. These variables were the cognitive traits, cognitive styles, and learning behavior. However, these systems neglect the importance of the learner's multiple intelligences, the learner's skill level and the learner's feedback when implementing…

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2014-01-01

Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…

Adaptive Interfaces

DTIC Science & Technology

1990-11-01

to design and implement an adaptive intelligent interface for a command-and-control-style domain. The primary functionality of the resulting...technical tasks, as follows: 1. Analysis of Current Interface Technologies 2. Dejineation of User Roles 3. Development of User Models 4. Design of Interface...Management Association (FEMA). In the initial version of the prototype, two distin-t user models were designed . One type of user modeled by the system is

Intelligent transportation systems for work zones : deployment benefits and lessons learned

DOT National Transportation Integrated Search

2000-12-01

This paper presents what has been learned in four principal areas of arterial management: 1) adaptive control strategies; 2) advanced traveler information systems; 3) automated enforcement; and 4) integration. The levels of deployment, benefits, depl...

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

PubMed Central

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-01-01

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains. PMID:26972968

From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks.

PubMed

Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming

2016-03-14

The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

Intelligent control of an IPMC actuated manipulator using emotional learning-based controller

NASA Astrophysics Data System (ADS)

Shariati, Azadeh; Meghdari, Ali; Shariati, Parham

2008-08-01

In this research an intelligent emotional learning controller, Takagi- Sugeno- Kang (TSK) is applied to govern the dynamics of a novel Ionic-Polymer Metal Composite (IPMC) actuated manipulator. Ionic-Polymer Metal Composites are active actuators that show very large deformation in existence of low applied voltage. In this research, a new IPMC actuator is considered and applied to a 2-dof miniature manipulator. This manipulator is designed for miniature tasks. The control system consists of a set of neurofuzzy controller whose parameters are adapted according to the emotional learning rules, and a critic with task to assess the present situation resulted from the applied control action in terms of satisfactory achievement of the control goals and provides the emotional signal (the stress). The controller modifies its characteristics so that the critic's stress decreased.

Neural robust stabilization via event-triggering mechanism and adaptive learning technique.

PubMed

Wang, Ding; Liu, Derong

2018-06-01

The robust control synthesis of continuous-time nonlinear systems with uncertain term is investigated via event-triggering mechanism and adaptive critic learning technique. We mainly focus on combining the event-triggering mechanism with adaptive critic designs, so as to solve the nonlinear robust control problem. This can not only make better use of computation and communication resources, but also conduct controller design from the view of intelligent optimization. Through theoretical analysis, the nonlinear robust stabilization can be achieved by obtaining an event-triggered optimal control law of the nominal system with a newly defined cost function and a certain triggering condition. The adaptive critic technique is employed to facilitate the event-triggered control design, where a neural network is introduced as an approximator of the learning phase. The performance of the event-triggered robust control scheme is validated via simulation studies and comparisons. The present method extends the application domain of both event-triggered control and adaptive critic control to nonlinear systems possessing dynamical uncertainties. Copyright © 2018 Elsevier Ltd. All rights reserved.

Distributed sensor architecture for intelligent control that supports quality of control and quality of service.

PubMed

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-02-25

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

Distributed Sensor Architecture for Intelligent Control that Supports Quality of Control and Quality of Service

PubMed Central

Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

2015-01-01

This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems. PMID:25723145

An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Hariri, Mohamad; Faddel, Samy; Mohammed, Osama

Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted tomore » verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.« less

SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): Overlaying Natural Language Tutoring on an Adaptive Learning System for Mathematics

ERIC Educational Resources Information Center

Nye, Benjamin D.; Pavlik, Philip I., Jr.; Windsor, Alistair; Olney, Andrew M.; Hajeer, Mustafa; Hu, Xiangen

2018-01-01

Background: This study investigated learning outcomes and user perceptions from interactions with a hybrid intelligent tutoring system created by combining the AutoTutor conversational tutoring system with the Assessment and Learning in Knowledge Spaces (ALEKS) adaptive learning system for mathematics. This hybrid intelligent tutoring system (ITS)…

An adaptive trajectory tracking control of four rotor hover vehicle using extended normalized radial basis function network

NASA Astrophysics Data System (ADS)

ul Amin, Rooh; Aijun, Li; Khan, Muhammad Umer; Shamshirband, Shahaboddin; Kamsin, Amirrudin

2017-01-01

In this paper, an adaptive trajectory tracking controller based on extended normalized radial basis function network (ENRBFN) is proposed for 3-degree-of-freedom four rotor hover vehicle subjected to external disturbance i.e. wind turbulence. Mathematical model of four rotor hover system is developed using equations of motions and a new computational intelligence based technique ENRBFN is introduced to approximate the unmodeled dynamics of the hover vehicle. The adaptive controller based on the Lyapunov stability approach is designed to achieve tracking of the desired attitude angles of four rotor hover vehicle in the presence of wind turbulence. The adaptive weight update based on the Levenberg-Marquardt algorithm is used to avoid weight drift in case the system is exposed to external disturbances. The closed-loop system stability is also analyzed using Lyapunov stability theory. Simulations and experimental results are included to validate the effectiveness of the proposed control scheme.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

PubMed

Mumtaz, Sidra; Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system

PubMed Central

Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

2017-01-01

This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms. PMID:28877191

Connectivity-enhanced route selection and adaptive control for the Chevrolet Volt

DOE PAGES

Gonder, Jeffrey; Wood, Eric; Rajagopalan, Sai

2016-01-01

The National Renewable Energy Laboratory and General Motors evaluated connectivity-enabled efficiency enhancements for the Chevrolet Volt. A high-level model was developed to predict vehicle fuel and electricity consumption based on driving characteristics and vehicle state inputs. These techniques were leveraged to optimize energy efficiency via green routing and intelligent control mode scheduling, which were evaluated using prospective driving routes between tens of thousands of real-world origin/destination pairs. The overall energy savings potential of green routing and intelligent mode scheduling was estimated at 5% and 3%, respectively. Furthermore, these represent substantial opportunities considering that they only require software adjustments to implement.

Adaptive Fuzzy Systems in Computational Intelligence

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

In recent years, the interest in computational intelligence techniques, which currently includes neural networks, fuzzy systems, and evolutionary programming, has grown significantly and a number of their applications have been developed in the government and industry. In future, an essential element in these systems will be fuzzy systems that can learn from experience by using neural network in refining their performances. The GARIC architecture, introduced earlier, is an example of a fuzzy reinforcement learning system which has been applied in several control domains such as cart-pole balancing, simulation of to Space Shuttle orbital operations, and tether control. A number of examples from GARIC's applications in these domains will be demonstrated.

Generalized anxiety disorder and online intelligence: A phenomenological account of why worrying is unhelpful

PubMed Central

2011-01-01

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD. PMID:21539727

Generalized anxiety disorder and online intelligence: a phenomenological account of why worrying is unhelpful.

PubMed

Meynen, Gerben

2011-05-03

Worrying is the central feature of generalized anxiety disorder (GAD). Many people worry from time to time, but in GAD the worrying is prolonged and difficult to control. Worrying is a specific way of coping with perceived threats and feared situations. Meanwhile, it is not considered to be a helpful coping strategy, and the phenomenological account developed in this paper aims to show why. It builds on several phenomenological notions and in particular on Michael Wheeler's application of these notions to artificial intelligence and the cognitive sciences. Wheeler emphasizes the value of 'online intelligence' as contrasted to 'offline intelligence'. I discuss and apply these concepts with respect to worrying as it occurs in GAD, suggesting that GAD patients overrate the value of detached contemplation (offline intelligence), while underrating their embodied-embedded adaptive skills (online intelligence). I argue that this phenomenological account does not only help explaining why worrying is used as a coping strategy, but also why cognitive behavioral therapy is successful in treating GAD.

Intelligent robot control using an adaptive critic with a task control center and dynamic database

NASA Astrophysics Data System (ADS)

Hall, E. L.; Ghaffari, M.; Liao, X.; Alhaj Ali, S. M.

2006-10-01

The purpose of this paper is to describe the design, development and simulation of a real time controller for an intelligent, vision guided robot. The use of a creative controller that can select its own tasks is demonstrated. This creative controller uses a task control center and dynamic database. The dynamic database stores both global environmental information and local information including the kinematic and dynamic models of the intelligent robot. The kinematic model is very useful for position control and simulations. However, models of the dynamics of the manipulators are needed for tracking control of the robot's motions. Such models are also necessary for sizing the actuators, tuning the controller, and achieving superior performance. Simulations of various control designs are shown. Also, much of the model has also been used for the actual prototype Bearcat Cub mobile robot. This vision guided robot was designed for the Intelligent Ground Vehicle Contest. A novel feature of the proposed approach is that the method is applicable to both robot arm manipulators and robot bases such as wheeled mobile robots. This generality should encourage the development of more mobile robots with manipulator capability since both models can be easily stored in the dynamic database. The multi task controller also permits wide applications. The use of manipulators and mobile bases with a high-level control are potentially useful for space exploration, certain rescue robots, defense robots, and medical robotics aids.

Robotics

NASA Astrophysics Data System (ADS)

Popov, E. P.; Iurevich, E. I.

The history and the current status of robotics are reviewed, as are the design, operation, and principal applications of industrial robots. Attention is given to programmable robots, robots with adaptive control and elements of artificial intelligence, and remotely controlled robots. The applications of robots discussed include mechanical engineering, cargo handling during transportation and storage, mining, and metallurgy. The future prospects of robotics are briefly outlined.

Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

ERIC Educational Resources Information Center

Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

2017-01-01

Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

Lateral Prefrontal Cortex Contributes to Fluid Intelligence Through Multinetwork Connectivity.

PubMed

Cole, Michael W; Ito, Takuya; Braver, Todd S

2015-10-01

Our ability to effectively adapt to novel circumstances--as measured by general fluid intelligence--has recently been tied to the global connectivity of lateral prefrontal cortex (LPFC). Global connectivity is a broad measure that summarizes both within-network connectivity and across-network connectivity. We used additional graph theoretical measures to better characterize the nature of LPFC connectivity and its relationship with fluid intelligence. We specifically hypothesized that LPFC is a connector hub with an across-network connectivity that contributes to fluid intelligence independent of within-network connectivity. We verified that LPFC was in the top 10% of brain regions in terms of across-network connectivity, suggesting it is a strong connector hub. Importantly, we found that the LPFC across-network connectivity predicted individuals' fluid intelligence and this correlation remained statistically significant when controlling for global connectivity (which includes within-network connectivity). This supports the conclusion that across-network connectivity independently contributes to the relationship between LPFC connectivity and intelligence. These results suggest that LPFC contributes to fluid intelligence by being a connector hub with a truly global multisystem connectivity throughout the brain.

Evolutionary psychology and intelligence research.

PubMed

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative variation on a monomorphic design allows us to incorporate heritable individual differences in evolved adaptations. The Savanna-IQ Interaction Hypothesis, which is one consequence of the integration of evolutionary psychology and intelligence research, can potentially explain why less intelligent individuals enjoy TV more, why liberals are more intelligent than conservatives, and why night owls are more intelligent than morning larks, among many other findings. The general approach proposed here will allow us to integrate evolutionary psychology with any other aspect of differential psychology. Copyright 2010 APA, all rights reserved.

Exploiting co-adaptation for the design of symbiotic neuroprosthetic assistants.

PubMed

Sanchez, Justin C; Mahmoudi, Babak; DiGiovanna, Jack; Principe, Jose C

2009-04-01

The success of brain-machine interfaces (BMI) is enabled by the remarkable ability of the brain to incorporate the artificial neuroprosthetic 'tool' into its own cognitive space and use it as an extension of the user's body. Unlike other tools, neuroprosthetics create a shared space that seamlessly spans the user's internal goal representation of the world and the external physical environment enabling a much deeper human-tool symbiosis. A key factor in the transformation of 'simple tools' into 'intelligent tools' is the concept of co-adaptation where the tool becomes functionally involved in the extraction and definition of the user's goals. Recent advancements in the neuroscience and engineering of neuroprosthetics are providing a blueprint for how new co-adaptive designs based on reinforcement learning change the nature of a user's ability to accomplish tasks that were not possible using conventional methodologies. By designing adaptive controls and artificial intelligence into the neural interface, tools can become active assistants in goal-directed behavior and further enhance human performance in particular for the disabled population. This paper presents recent advances in computational and neural systems supporting the development of symbiotic neuroprosthetic assistants.

Multimodal Interfaces: Literature Review of Ecological Interface Design, Multimodal Perception and Attention, and Intelligent Adaptive Multimodal Interfaces

DTIC Science & Technology

2010-05-01

Multimodal Interfaces Literature Review of Ecological Interface Design , Multimodal Perception and Attention, and Intelligent... Design , Multimodal Perception and Attention, and Intelligent Adaptive Multimodal Interfaces Wayne Giang, Sathya Santhakumaran, Ehsan Masnavi, Doug...Advanced Interface Design Laboratory, E2-1303N 200 University Avenue West Waterloo, Ontario Canada N2L 3G1 Contract Project Manager: Dr. Catherine

Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

NASA Technical Reports Server (NTRS)

Aucoin, B. M.; Heller, R. P.

1990-01-01

An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

[Effects of acaoustic adaptation of classrooms on the quality of verbal communication].

PubMed

Mikulski, Witold

2013-01-01

Voice organ disorders among teachers are caused by excessive voice strain. One of the measures to reduce this strain is to decrease background noise when teaching. Increasing the acoustic absorption of the room is a technical measure for achieving this aim. The absorption level also improves speech intelligibility rated by the following parameters: room reverberation time and speech transmission index (STI). This article presents the effects of acoustic adaptation of classrooms on the quality of verbal communication, aimed at getting the speech intelligibility at the good or excellent level. The article lists the criteria for evaluating classrooms in terms of the quality of verbal communication. The parameters were defined, using the measurement methods according to PN-EN ISO 3382-2:2010 and PN-EN 60268-16:2011. Acoustic adaptations were completed in two classrooms. After completing acoustic adaptations the reverberation time for the frequency of 1 kHz was reduced: in room no. 1 from 1.45 s to 0.44 s and in room no. 2 from 1.03 s to 0.37 s (maximum 0.65 s). At the same time, the speech transmission index increased: in room no. 1 from 0.55 (satisfactory speech intelligibility) to 0.75 (speech intelligibility close to excellent); in room no. 2 from 0.63 (good speech intelligibility) to 0.80 (excellent speech intelligibility). Therefore, it can be stated that prior to completing acoustic adaptations room no. 1 did not comply and room no. 2 barely complied with the criterion (speech transmission index of 0.62). After completing acoustic adaptations both rooms meet the requirements.

An intelligent interface for satellite operations: Your Orbit Determination Assistant (YODA)

NASA Technical Reports Server (NTRS)

Schur, Anne

1988-01-01

An intelligent interface is often characterized by the ability to adapt evaluation criteria as the environment and user goals change. Some factors that impact these adaptations are redefinition of task goals and, hence, user requirements; time criticality; and system status. To implement adaptations affected by these factors, a new set of capabilities must be incorporated into the human-computer interface design. These capabilities include: (1) dynamic update and removal of control states based on user inputs, (2) generation and removal of logical dependencies as change occurs, (3) uniform and smooth interfacing to numerous processes, databases, and expert systems, and (4) unobtrusive on-line assistance to users of concepts were applied and incorporated into a human-computer interface using artificial intelligence techniques to create a prototype expert system, Your Orbit Determination Assistant (YODA). YODA is a smart interface that supports, in real teime, orbit analysts who must determine the location of a satellite during the station acquisition phase of a mission. Also described is the integration of four knowledge sources required to support the orbit determination assistant: orbital mechanics, spacecraft specifications, characteristics of the mission support software, and orbit analyst experience. This initial effort is continuing with expansion of YODA's capabilities, including evaluation of results of the orbit determination task.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

Intelligent Control and Health Monitoring. Chapter 3

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Kumar, Aditya; Mathews, H. Kirk; Rosenfeld, Taylor; Rybarik, Pavol; Viassolo, Daniel E.

2009-01-01

Advanced model-based control architecture overcomes the limitations state-of-the-art engine control and provides the potential of virtual sensors, for example for thrust and stall margin. "Tracking filters" are used to adapt the control parameters to actual conditions and to individual engines. For health monitoring standalone monitoring units will be used for on-board analysis to determine the general engine health and detect and isolate sudden faults. Adaptive models open up the possibility of adapting the control logic to maintain desired performance in the presence of engine degradation or to accommodate any faults. Improved and new sensors are required to allow sensing at stations within the engine gas path that are currently not instrumented due in part to the harsh conditions including high operating temperatures and to allow additional monitoring of vibration, mass flows and energy properties, exhaust gas composition, and gas path debris. The environmental and performance requirements for these sensors are summarized.

An RFID-based intelligent vehicle speed controller using active traffic signals.

PubMed

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver's attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results.

An RFID-Based Intelligent Vehicle Speed Controller Using Active Traffic Signals

PubMed Central

Pérez, Joshué; Seco, Fernando; Milanés, Vicente; Jiménez, Antonio; Díaz, Julio C.; de Pedro, Teresa

2010-01-01

These days, mass-produced vehicles benefit from research on Intelligent Transportation System (ITS). One prime example of ITS is vehicle Cruise Control (CC), which allows it to maintain a pre-defined reference speed, to economize on fuel or energy consumption, to avoid speeding fines, or to focus all of the driver’s attention on the steering of the vehicle. However, achieving efficient Cruise Control is not easy in roads or urban streets where sudden changes of the speed limit can happen, due to the presence of unexpected obstacles or maintenance work, causing, in inattentive drivers, traffic accidents. In this communication we present a new Infrastructure to Vehicles (I2V) communication and control system for intelligent speed control, which is based upon Radio Frequency Identification (RFID) technology for identification of traffic signals on the road, and high accuracy vehicle speed measurement with a Hall effect-based sensor. A fuzzy logic controller, based on sensor fusion of the information provided by the I2V infrastructure, allows the efficient adaptation of the speed of the vehicle to the circumstances of the road. The performance of the system is checked empirically, with promising results. PMID:22219692

Modeling Smart Structure of Wind Turbine Blade

NASA Astrophysics Data System (ADS)

Qiao, Yin-hu; Han, Jiang; Zhang, Chun-yan; Chen, Jie-ping

2012-06-01

With the increasing size of wind turbine blades, the need for more sophisticated load control techniques has induced the interest for aerodynamic control systems with build-in intelligence on the blades. The paper aims to provide a way for modeling the adaptive wind turbine blades and analyze its ability for vibration suppress. It consists of the modeling of the adaptive wind turbine blades with the wire of piezoelectric material embedded in blade matrix, and smart sandwich structure of wind turbine blade. By using this model, an active vibration method which effectively suppresses the vibrations of the smart blade is designed.

Introduction to Fuzzy Set Theory

NASA Technical Reports Server (NTRS)

Kosko, Bart

1990-01-01

An introduction to fuzzy set theory is described. Topics covered include: neural networks and fuzzy systems; the dynamical systems approach to machine intelligence; intelligent behavior as adaptive model-free estimation; fuzziness versus probability; fuzzy sets; the entropy-subsethood theorem; adaptive fuzzy systems for backing up a truck-and-trailer; product-space clustering with differential competitive learning; and adaptive fuzzy system for target tracking.

Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

NASA Technical Reports Server (NTRS)

Dufrene, Warren R., Jr.

2004-01-01

This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

MIXI: Mobile Intelligent X-Ray Inspection System

NASA Astrophysics Data System (ADS)

Arodzero, Anatoli; Boucher, Salime; Kutsaev, Sergey V.; Ziskin, Vitaliy

2017-07-01

A novel, low-dose Mobile Intelligent X-ray Inspection (MIXI) concept is being developed at RadiaBeam Technologies. The MIXI concept relies on a linac-based, adaptive, ramped energy source of short X-ray packets of pulses, a new type of fast X-ray detector, rapid processing of detector signals for intelligent control of the linac, and advanced radiography image processing. The key parameters for this system include: better than 3 mm line pair resolution; penetration greater than 320 mm of steel equivalent; scan speed with 100% image sampling rate of up to 15 km/h; and material discrimination over a range of thicknesses up to 200 mm of steel equivalent. Its minimal radiation dose, size and weight allow MIXI to be placed on a lightweight truck chassis.

Decision making and problem solving with computer assistance

NASA Technical Reports Server (NTRS)

Kraiss, F.

1980-01-01

In modern guidance and control systems, the human as manager, supervisor, decision maker, problem solver and trouble shooter, often has to cope with a marginal mental workload. To improve this situation, computers should be used to reduce the operator from mental stress. This should not solely be done by increased automation, but by a reasonable sharing of tasks in a human-computer team, where the computer supports the human intelligence. Recent developments in this area are summarized. It is shown that interactive support of operator by intelligent computer is feasible during information evaluation, decision making and problem solving. The applied artificial intelligence algorithms comprehend pattern recognition and classification, adaptation and machine learning as well as dynamic and heuristic programming. Elementary examples are presented to explain basic principles.

Adjustment of gripping force by optical systems

NASA Astrophysics Data System (ADS)

Jalba, C. K.; Barz, C.

2018-01-01

With increasing automation, robotics also requires ever more intelligent solutions in the handling of various tasks. In this context, many grippers must also be re-designed. For this, they must always be adapted for different requirements. The equipment of the gripper systems with sensors should help to make the gripping process more intelligent. In order to achieve such objectives, optical systems can also be used. This work analyzes how the gripping force can be adjusted by means of an optical recognition. The result of this work is the creation of a connection between optical recognition, tolerances, gripping force and real-time control. In this way, algorithms can be created, with the aid of which robot grippers as well as other gripping systems become more intelligent.

Analytical studies on the instabilities of heterogeneous intelligent traffic flow

NASA Astrophysics Data System (ADS)

Ngoduy, D.

2013-10-01

It has been widely reported in literature that a small perturbation in traffic flow such as a sudden deceleration of a vehicle could lead to the formation of traffic jams without a clear bottleneck. These traffic jams are usually related to instabilities in traffic flow. The applications of intelligent traffic systems are a potential solution to reduce the amplitude or to eliminate the formation of such traffic instabilities. A lot of research has been conducted to theoretically study the effect of intelligent vehicles, for example adaptive cruise control vehicles, using either computer simulation or analytical method. However, most current analytical research has only applied to single class traffic flow. To this end, the main topic of this paper is to perform a linear stability analysis to find the stability threshold of heterogeneous traffic flow using microscopic models, particularly the effect of intelligent vehicles on heterogeneous (or multi-class) traffic flow instabilities. The analytical results will show how intelligent vehicle percentages affect the stability of multi-class traffic flow.

Open-Source Intelligence in the Czech Military: Knowledge System and Process Design

DTIC Science & Technology

2002-06-01

in Open-Source Intelligence OSINT, as one of the intelligence disciplines, bears some of the general problems of intelligence " business " OSINT...ADAPTING KNOWLEDGE MANAGEMENT THEORY TO THE CZECH MILITARY INTELLIGENCE Knowledge work is the core business of the military intelligence . As...NAVAL POSTGRADUATE SCHOOL Monterey, California THESIS Approved for public release; distribution is unlimited OPEN-SOURCE INTELLIGENCE IN THE

Impact of HIV severity on cognitive and adaptive functioning during childhood and adolescence.

PubMed

Smith, Renee; Chernoff, Miriam; Williams, Paige L; Malee, Kathleen M; Sirois, Patricia A; Kammerer, Betsy; Wilkins, Megan; Nichols, Sharon; Mellins, Claude; Usitalo, Ann; Garvie, Patricia; Rutstein, Richard

2012-06-01

The influence of disease severity on cognitive and adaptive functioning in perinatally HIV-infected youth with (PHIV+/C) and without (PHIV+/NoC) a previous AIDS-defining illness (Centers for Disease Control and Prevention Class C event), compared with perinatally HIV-exposed but uninfected youth (PHEU) is not well understood. This was a cross-sectional analysis of cognitive and adaptive functioning in PHIV+/C (n = 88), PHIV+/NoC (n = 270) and PHEU (n = 200) youth aged 7-16 years, from a multisite prospective cohort study. Youth and caregivers completed the Wechsler Intelligence Scale for Children, Fourth Edition and the Adaptive Behavior Assessment System, Second Edition, respectively. We compared means and rates of impairment between groups, and examined associations with other psychosocial factors. Overall mean scores on measures of cognitive and adaptive functioning were in the low average range for all 3 groups. After adjustment for covariates, mean full-scale intelligence quotient scores were significantly lower for the PHIV+/C group than the PHIV+/NoC and PHEU groups (mean = 77.8 versus 83.4 and 83.3, respectively), whereas no significant differences were observed between the PHEU and PHIV+/NoC groups in any domain. Lower cognitive performance for the PHIV+/C group was primarily attributable to a prior diagnosis of encephalopathy. No significant differences between groups were observed in adaptive functioning. For long-term survivors, youth with HIV infection and a prior Centers for Disease Control and Prevention Class C event have higher risk for cognitive but not adaptive impairment regardless of current health status; this finding appears attributable to a previous diagnosis of encephalopathy. Early preventive therapy may be critical in reducing risk of later neurodevelopmental impairments.

A possible correlation between performance IQ, visuomotor adaptation ability and mu suppression.

PubMed

Anwar, Muhammad Nabeel; Navid, Muhammad Samran; Khan, Mushtaq; Kitajo, Keiichi

2015-04-07

Psychometric, anatomical and functional brain studies suggest that individuals differ in the way that they perceive and analyze information and strategically control and execute movements. Inter-individual differences are also observed in neural correlates of specific and general cognitive ability. As a result, some individuals perceive and adapt to environmental conditions and perform motor activities better than others. The aim of this study was to identify a common factor that predicts adaptation of a reaching movement to a visual perturbation and suppression of movement-related brain activity (mu rhythms). Twenty-eight participants participated in two different experiments designed to evaluate visuomotor adaptation and mu suppression ability. Performance intelligence quotient (IQ) was assessed using the revised Wechsler Adult Intelligence Scale. Performance IQ predicted adaptation index of visuomotor performance (r=0.43, p=0.02) and suppression of mu rhythms (r=-0.59; p<0.001). Participants with high performance IQ were faster at adapting to a visuomotor perturbation and better at suppressing mu activity than participants with low performance IQ. We found a possible link between performance IQ and mu suppression, and performance IQ and the initial rate of adaptation. Individuals with high performance IQ were better in suppressing mu rhythms and were quicker at associating motor command and required movement than individuals with low performance IQ. Copyright © 2015 Elsevier B.V. All rights reserved.

Towards Intelligent Control for Next Generation Aircraft

NASA Technical Reports Server (NTRS)

Acosta, Diana Michelle; KrishnaKumar, Kalmanje Srinvas; Frost, Susan Alane

2008-01-01

NASA Aeronautics Subsonic Fixed Wing Project is focused on mitigating the environmental and operation impacts expected as aviation operations triple by 2025. The approach is to extend technological capabilities and explore novel civil transport configurations that reduce noise, emissions, fuel consumption and field length. Two Next Generation (NextGen) aircraft have been identified to meet the Subsonic Fixed Wing Project goals - these are the Hybrid Wing-Body (HWB) and Cruise Efficient Short Take-Off and Landing (CESTOL) aircraft. The technologies and concepts developed for these aircraft complicate the vehicle s design and operation. In this paper, flight control challenges for NextGen aircraft are described. The objective of this paper is to examine the potential of state-of-the-art control architectures and algorithms to meet the challenges and needed performance metrics for NextGen flight control. A broad range of conventional and intelligent control approaches are considered, including dynamic inversion control, integrated flight-propulsion control, control allocation, adaptive dynamic inversion control, data-based predictive control and reinforcement learning control.

Beyond adaptive-critic creative learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it permits the discovery of the unknown problems, ones that are not yet recognized but may be critical to survival or success.

Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

PubMed Central

Vanacker, Gerolf; Millán, José del R.; Lew, Eileen; Ferrez, Pierre W.; Moles, Ferran Galán; Philips, Johan; Van Brussel, Hendrik; Nuttin, Marnix

2007-01-01

Controlling a robotic device by using human brain signals is an interesting and challenging task. The device may be complicated to control and the nonstationary nature of the brain signals provides for a rather unstable input. With the use of intelligent processing algorithms adapted to the task at hand, however, the performance can be increased. This paper introduces a shared control system that helps the subject in driving an intelligent wheelchair with a noninvasive brain interface. The subject's steering intentions are estimated from electroencephalogram (EEG) signals and passed through to the shared control system before being sent to the wheelchair motors. Experimental results show a possibility for significant improvement in the overall driving performance when using the shared control system compared to driving without it. These results have been obtained with 2 healthy subjects during their first day of training with the brain-actuated wheelchair. PMID:18354739

Brave New World of Intelligence Testing.

ERIC Educational Resources Information Center

Rice, Berkeley

1979-01-01

New approaches to assessing intelligence are discussed, as well as new intelligence tests. Among the developments are investigating neurometrics, adapting testing to the effects of technology on children, countering cultural bias, assessing social intelligence, focusing on aspects of cognitive styles, measuring learning potential, and using…

Knowledge-based control of an adaptive interface

NASA Technical Reports Server (NTRS)

Lachman, Roy

1989-01-01

The analysis, development strategy, and preliminary design for an intelligent, adaptive interface is reported. The design philosophy couples knowledge-based system technology with standard human factors approaches to interface development for computer workstations. An expert system has been designed to drive the interface for application software. The intelligent interface will be linked to application packages, one at a time, that are planned for multiple-application workstations aboard Space Station Freedom. Current requirements call for most Space Station activities to be conducted at the workstation consoles. One set of activities will consist of standard data management services (DMS). DMS software includes text processing, spreadsheets, data base management, etc. Text processing was selected for the first intelligent interface prototype because text-processing software can be developed initially as fully functional but limited with a small set of commands. The program's complexity then can be increased incrementally. The intelligent interface includes the operator's behavior and three types of instructions to the underlying application software are included in the rule base. A conventional expert-system inference engine searches the data base for antecedents to rules and sends the consequents of fired rules as commands to the underlying software. Plans for putting the expert system on top of a second application, a database management system, will be carried out following behavioral research on the first application. The intelligent interface design is suitable for use with ground-based workstations now common in government, industrial, and educational organizations.

The highly intelligent virtual agents for modeling financial markets

NASA Astrophysics Data System (ADS)

Yang, G.; Chen, Y.; Huang, J. P.

2016-02-01

Researchers have borrowed many theories from statistical physics, like ensemble, Ising model, etc., to study complex adaptive systems through agent-based modeling. However, one fundamental difference between entities (such as spins) in physics and micro-units in complex adaptive systems is that the latter are usually with high intelligence, such as investors in financial markets. Although highly intelligent virtual agents are essential for agent-based modeling to play a full role in the study of complex adaptive systems, how to create such agents is still an open question. Hence, we propose three principles for designing high artificial intelligence in financial markets and then build a specific class of agents called iAgents based on these three principles. Finally, we evaluate the intelligence of iAgents through virtual index trading in two different stock markets. For comparison, we also include three other types of agents in this contest, namely, random traders, agents from the wealth game (modified on the famous minority game), and agents from an upgraded wealth game. As a result, iAgents perform the best, which gives a well support for the three principles. This work offers a general framework for the further development of agent-based modeling for various kinds of complex adaptive systems.

Cognitions as determinants of (mal)adaptive emotions and emotionally intelligent behavior in an organizational context.

PubMed

Spörrle, Matthias; Welpe, Isabell M; Försterling, Friedrich

2006-01-01

This study applies the theoretical concepts of Rational Emotive Behavior Therapy (REBT; Ellis, 1962, 1994) to the analysis of functional and dysfunctional behaviour and emotions in the workplace and tests central assumptions of REBT in an organizational setting. We argue that Ellis' appraisal theory of emotion sheds light on some of the cognitive and emotional antecedents of emotional intelligence and emotionally intelligent behaviour. In an extension of REBT, we posit that adaptive emotions resulting from rational cognitions reflect more emotional intelligence than maladaptive emotions which result from irrational cognitions, because the former lead to functional behaviour. We hypothesize that semantically similar emotions (e.g. annoyance and rage) lead to different behavioural reactions and have a different functionality in an organizational context. The results of scenario experiments using organizational vignettes confirm the central assumptions of Ellis' appraisal theory and support our hypotheses of a correspondence between adaptive emotions and emotionally intelligent behaviour. Additionally, we find evidence that irrational job-related attitudes result in reduced work (but not life) satisfaction.

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.; Yokum, Steve

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.

Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences

PubMed Central

Soltani, Batoul; Keyvanara, Mahmoud

2013-01-01

Introduction: At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012. Methodology: The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students’ sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang’s Cultural Intelligence Questionnaire with the Cronbach’s coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach’s coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods. Results: The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for Iranian students vs. 47.6% for non-Iranians), motivational aspect (59.0% vs. 42.6%), behavioral aspect (31.8% vs. 41.2%) as well as social adaptability as the other variable in question ( 68.9% vs. 56.2%) (p<0.001). Conclusion: The comparison of the mean scores gained for meta-cognitive and motivational aspects of cultural intelligence as well as social adaptability in Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences revealed that the Iranian students had the higher rank. On the other hand, the mean score acquired for the behavioral aspect in Iranian and non-Iranian students were comparable, with non-Iranian students having the higher mean scores. Therefore, it can be said that the meta-cognitive and motivational aspects of cultural intelligence and social adaptability of non-Iranian students and the behavioral aspect of Iranian students’ cultural intelligence may be promoted by educational planning, thereby, taking effective steps towards their achievement in contexts with inter-cultural interaction . In this way, their mental health will be enhanced, as well. PMID:23678339

Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences.

PubMed

Soltani, Batoul; Keyvanara, Mahmoud

2013-01-01

At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012. The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students' sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang's Cultural Intelligence Questionnaire with the Cronbach's coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach's coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods. The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for Iranian students vs. 47.6% for non-Iranians), motivational aspect (59.0% vs. 42.6%), behavioral aspect (31.8% vs. 41.2%) as well as social adaptability as the other variable in question ( 68.9% vs. 56.2%) (p<0.001). The comparison of the mean scores gained for meta-cognitive and motivational aspects of cultural intelligence as well as social adaptability in Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences revealed that the Iranian students had the higher rank. On the other hand, the mean score acquired for the behavioral aspect in Iranian and non-Iranian students were comparable, with non-Iranian students having the higher mean scores. Therefore, it can be said that the meta-cognitive and motivational aspects of cultural intelligence and social adaptability of non-Iranian students and the behavioral aspect of Iranian students' cultural intelligence may be promoted by educational planning, thereby, taking effective steps towards their achievement in contexts with inter-cultural interaction . In this way, their mental health will be enhanced, as well.

Knowledge representation into Ada parallel processing

NASA Technical Reports Server (NTRS)

Masotto, Tom; Babikyan, Carol; Harper, Richard

1990-01-01

The Knowledge Representation into Ada Parallel Processing project is a joint NASA and Air Force funded project to demonstrate the execution of intelligent systems in Ada on the Charles Stark Draper Laboratory fault-tolerant parallel processor (FTPP). Two applications were demonstrated - a portion of the adaptive tactical navigator and a real time controller. Both systems are implemented as Activation Framework Objects on the Activation Framework intelligent scheduling mechanism developed by Worcester Polytechnic Institute. The implementations, results of performance analyses showing speedup due to parallelism and initial efficiency improvements are detailed and further areas for performance improvements are suggested.

The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

ERIC Educational Resources Information Center

Alahdadi, Shadi; Ghanizadeh, Afsaneh

2017-01-01

A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

Artificial Intelligence Methods in Computer-Based Instructional Design. The Minnesota Adaptive Instructional System.

ERIC Educational Resources Information Center

Tennyson, Robert

1984-01-01

Reviews educational applications of artificial intelligence and presents empirically-based design variables for developing a computer-based instruction management system. Taken from a programmatic research effort based on the Minnesota Adaptive Instructional System, variables include amount and sequence of instruction, display time, advisement,…

The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis

ERIC Educational Resources Information Center

Alexander, Ryan M.

2017-01-01

Intelligence tests and adaptive behavior scales measure vital aspects of the multidimensional nature of human functioning. Assessment of each is a required component in the diagnosis or identification of intellectual disability, and both are frequently used conjointly in the assessment and identification of other developmental disabilities. The…

Adaptive Educational Software by Applying Reinforcement Learning

ERIC Educational Resources Information Center

Bennane, Abdellah

2013-01-01

The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt…

Development of An Intelligent Flight Propulsion Control System

NASA Technical Reports Server (NTRS)

Calise, A. J.; Rysdyk, R. T.; Leonhardt, B. K.

1999-01-01

The initial design and demonstration of an Intelligent Flight Propulsion and Control System (IFPCS) is documented. The design is based on the implementation of a nonlinear adaptive flight control architecture. This initial design of the IFPCS enhances flight safety by using propulsion sources to provide redundancy in flight control. The IFPCS enhances the conventional gain scheduled approach in significant ways: (1) The IFPCS provides a back up flight control system that results in consistent responses over a wide range of unanticipated failures. (2) The IFPCS is applicable to a variety of aircraft models without redesign and,(3) significantly reduces the laborious research and design necessary in a gain scheduled approach. The control augmentation is detailed within an approximate Input-Output Linearization setting. The availability of propulsion only provides two control inputs, symmetric and differential thrust. Earlier Propulsion Control Augmentation (PCA) work performed by NASA provided for a trajectory controller with pilot command input of glidepath and heading. This work is aimed at demonstrating the flexibility of the IFPCS in providing consistency in flying qualities under a variety of failure scenarios. This report documents the initial design phase where propulsion only is used. Results confirm that the engine dynamics and associated hard nonlineaaities result in poor handling qualities at best. However, as demonstrated in simulation, the IFPCS is capable of results similar to the gain scheduled designs of the NASA PCA work. The IFPCS design uses crude estimates of aircraft behaviour. The adaptive control architecture demonstrates robust stability and provides robust performance. In this work, robust stability means that all states, errors, and adaptive parameters remain bounded under a wide class of uncertainties and input and output disturbances. Robust performance is measured in the quality of the tracking. The results demonstrate the flexibility of the IFPCS architecture and the ability to provide robust performance under a broad range of uncertainty. Robust stability is proved using Lyapunov like analysis. Future development of the IFPCS will include integration of conventional control surfaces with the use of propulsion augmentation, and utilization of available lift and drag devices, to demonstrate adaptive control capability under a greater variety of failure scenarios. Further work will specifically address the effects of actuator saturation.

Combining metric episodes with semantic event concepts within the Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS)

NASA Astrophysics Data System (ADS)

Kelley, Troy D.; McGhee, S.

2013-05-01

This paper describes the ongoing development of a robotic control architecture that inspired by computational cognitive architectures from the discipline of cognitive psychology. The Symbolic and Sub-Symbolic Robotics Intelligence Control System (SS-RICS) combines symbolic and sub-symbolic representations of knowledge into a unified control architecture. The new architecture leverages previous work in cognitive architectures, specifically the development of the Adaptive Character of Thought-Rational (ACT-R) and Soar. This paper details current work on learning from episodes or events. The use of episodic memory as a learning mechanism has, until recently, been largely ignored by computational cognitive architectures. This paper details work on metric level episodic memory streams and methods for translating episodes into abstract schemas. The presentation will include research on learning through novelty and self generated feedback mechanisms for autonomous systems.

Analysis of Bioactive Amino Acids from Fish Hydrolysates with a New Bioinformatic Intelligent System Approach.

PubMed

Elaziz, Mohamed Abd; Hemdan, Ahmed Monem; Hassanien, AboulElla; Oliva, Diego; Xiong, Shengwu

2017-09-07

The current economics of the fish protein industry demand rapid, accurate and expressive prediction algorithms at every step of protein production especially with the challenge of global climate change. This help to predict and analyze functional and nutritional quality then consequently control food allergies in hyper allergic patients. As, it is quite expensive and time-consuming to know these concentrations by the lab experimental tests, especially to conduct large-scale projects. Therefore, this paper introduced a new intelligent algorithm using adaptive neuro-fuzzy inference system based on whale optimization algorithm. This algorithm is used to predict the concentration levels of bioactive amino acids in fish protein hydrolysates at different times during the year. The whale optimization algorithm is used to determine the optimal parameters in adaptive neuro-fuzzy inference system. The results of proposed algorithm are compared with others and it is indicated the higher performance of the proposed algorithm.

Gray matter responsiveness to adaptive working memory training: a surface-based morphometry study

PubMed Central

Román, Francisco J.; Lewis, Lindsay B.; Chen, Chi-Hua; Karama, Sherif; Burgaleta, Miguel; Martínez, Kenia; Lepage, Claude; Jaeggi, Susanne M.; Evans, Alan C.; Kremen, William S.

2016-01-01

Here we analyze gray matter indices before and after completing a challenging adaptive cognitive training program based on the n-back task. The considered gray matter indices were cortical thickness (CT) and cortical surface area (CSA). Twenty-eight young women (age range 17–22 years) completed 24 training sessions over the course of 3 months (12 weeks, 24 sessions), showing expected performance improvements. CT and CSA values for the training group were compared with those of a matched control group. Statistical analyses were computed using a ROI framework defined by brain areas distinguished by their genetic underpinning. The interaction between group and time was analyzed. Middle temporal, ventral frontal, inferior parietal cortices, and pars opercularis were the regions where the training group showed conservation of gray matter with respect to the control group. These regions support working memory, resistance to interference, and inhibition. Furthermore, an interaction with baseline intelligence differences showed that the expected decreasing trend at the biological level for individuals showing relatively low intelligence levels at baseline was attenuated by the completed training. PMID:26701168

Revisiting the Psychology of Intelligence Analysis: From Rational Actors to Adaptive Thinkers

ERIC Educational Resources Information Center

Puvathingal, Bess J.; Hantula, Donald A.

2012-01-01

Intelligence analysis is a decision-making process rife with ambiguous, conflicting, irrelevant, important, and excessive information. The U.S. Intelligence Community is primed for psychology to lend its voice to the "analytic transformation" movement aimed at improving the quality of intelligence analysis. Traditional judgment and decision making…

Piezoceramic devices and artificial intelligence time varying concepts in smart structures

NASA Technical Reports Server (NTRS)

Hanagud, S.; Calise, A. J.; Glass, B. J.

1990-01-01

The problem of development of smart structures and their vibration control by the use of piezoceramic sensors and actuators have been discussed. In particular, these structures are assumed to have time varying model form and parameters. The model form may change significantly and suddenly. Combined identification of the model from parameters of these structures and model adaptive control of these structures are discussed in this paper.

Physical therapy applications of MR fluids and intelligent control

NASA Astrophysics Data System (ADS)

Dong, Shufang; Lu, Ke-Qian; Sun, J. Q.; Rudolph, Katherine

2005-05-01

Resistance exercise has been widely reported to have positive rehabilitation effects for patients with neuromuscular and orthopaedic conditions. This paper presents an optimal design of magneto-rheological fluid dampers for variable resistance exercise devices. Adaptive controls for regulating the resistive force or torque of the device as well as the joint motion are presented. The device provides both isometric and isokinetic strength training for various human joints.

New robotics: design principles for intelligent systems.

PubMed

Pfeifer, Rolf; Iida, Fumiya; Bongard, Josh

2005-01-01

New robotics is an approach to robotics that, in contrast to traditional robotics, employs ideas and principles from biology. While in the traditional approach there are generally accepted methods (e. g., from control theory), designing agents in the new robotics approach is still largely considered an art. In recent years, we have been developing a set of heuristics, or design principles, that on the one hand capture theoretical insights about intelligent (adaptive) behavior, and on the other provide guidance in actually designing and building systems. In this article we provide an overview of all the principles but focus on the principles of ecological balance, which concerns the relation between environment, morphology, materials, and control, and sensory-motor coordination, which concerns self-generated sensory stimulation as the agent interacts with the environment and which is a key to the development of high-level intelligence. As we argue, artificial evolution together with morphogenesis is not only "nice to have" but is in fact a necessary tool for designing embodied agents.

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

Robust Control Analysis of Hydraulic Turbine Speed

NASA Astrophysics Data System (ADS)

Jekan, P.; Subramani, C.

2018-04-01

An effective control strategy for the hydro-turbine governor in time scenario is adjective for this paper. Considering the complex dynamic characteristic and the uncertainty of the hydro-turbine governor model and taking the static and dynamic performance of the governing system as the ultimate goal, the designed logic combined the classical PID control theory with artificial intelligence used to obtain the desired output. The used controller will be a variable control techniques, therefore, its parameters can be adaptively adjusted according to the information about the control error signal.

Detection of antipersonnel (AP) mines using mechatronics approach

NASA Astrophysics Data System (ADS)

Shahri, Ali M.; Naghdy, Fazel

1998-09-01

At present there are approximately 110 million land-mines scattered around the world in 64 countries. The clearance of these mines takes place manually. Unfortunately, on average for every 5000 mines cleared one mine clearer is killed. A Mine Detector Arm (MDA) using mechatronics approach is under development in this work. The robot arm imitates manual hand- prodding technique for mine detection. It inserts a bayonet into the soil and models the dynamics of the manipulator and environment parameters, such as stiffness variation in the soil to control the impact caused by contacting a stiff object. An explicit impact control scheme is applied as the main control scheme, while two different intelligent control methods are designed to deal with uncertainties and varying environmental parameters. Firstly, a neuro-fuzzy adaptive gain controller (NFAGC) is designed to adapt the force gain control according to the estimated environment stiffness. Then, an adaptive neuro-fuzzy plus PID controller is employed to switch from a conventional PID controller to neuro-fuzzy impact control (NFIC), when an impact is detected. The developed control schemes are validated through computer simulation and experimental work.

Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system.

PubMed

Mumtaz, Sidra; Khan, Laiq

2017-01-01

The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm.

Adaptive control paradigm for photovoltaic and solid oxide fuel cell in a grid-integrated hybrid renewable energy system

PubMed Central

Khan, Laiq

2017-01-01

The hybrid power system (HPS) is an emerging power generation scheme due to the plentiful availability of renewable energy sources. Renewable energy sources are characterized as highly intermittent in nature due to meteorological conditions, while the domestic load also behaves in a quite uncertain manner. In this scenario, to maintain the balance between generation and load, the development of an intelligent and adaptive control algorithm has preoccupied power engineers and researchers. This paper proposes a Hermite wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control of photovoltaic (PV) systems to extract maximum power and a Hermite wavelet incorporated NeuroFuzzy indirect adaptive control of Solid Oxide Fuel Cells (SOFC) to obtain a swift response in a grid-connected hybrid power system. A comprehensive simulation testbed for a grid-connected hybrid power system (wind turbine, PV cells, SOFC, electrolyzer, battery storage system, supercapacitor (SC), micro-turbine (MT) and domestic load) is developed in Matlab/Simulink. The robustness and superiority of the proposed indirect adaptive control paradigm are evaluated through simulation results in a grid-connected hybrid power system testbed by comparison with a conventional PI (proportional and integral) control system. The simulation results verify the effectiveness of the proposed control paradigm. PMID:28329015

Inverting the Army Intelligence Pyramid

DTIC Science & Technology

2011-05-19

Intelligence for Counterinsurgency," Military Review 86, no. 5 (2006): 25. U.S. Army forces adapted well over the past nine years of the conflict and have...David H. Petraeus, "COMISAF’s Counterinsurgency Guidance,"(2010); Brian Burton and John Nagl, "Learning as We Go: The US Army Adapts to... adaptive and evolving enemies it faced by introducing the concept of “Every Soldier a Sensor.” With this concept, the Army sought to inculcate

A performance analysis of advanced I/O architectures for PC-based network file servers

NASA Astrophysics Data System (ADS)

Huynh, K. D.; Khoshgoftaar, T. M.

1994-12-01

In the personal computing and workstation environments, more and more I/O adapters are becoming complete functional subsystems that are intelligent enough to handle I/O operations on their own without much intervention from the host processor. The IBM Subsystem Control Block (SCB) architecture has been defined to enhance the potential of these intelligent adapters by defining services and conventions that deliver command information and data to and from the adapters. In recent years, a new storage architecture, the Redundant Array of Independent Disks (RAID), has been quickly gaining acceptance in the world of computing. In this paper, we would like to discuss critical system design issues that are important to the performance of a network file server. We then present a performance analysis of the SCB architecture and disk array technology in typical network file server environments based on personal computers (PCs). One of the key issues investigated in this paper is whether a disk array can outperform a group of disks (of same type, same data capacity, and same cost) operating independently, not in parallel as in a disk array.

A simultaneous examination of two forms of working memory training: Evidence for near transfer only.

PubMed

Minear, Meredith; Brasher, Faith; Guerrero, Claudia Brandt; Brasher, Mandy; Moore, Andrew; Sukeena, Joshua

2016-10-01

The efficacy of working-memory training is a topic of considerable debate, with some studies showing transfer to measures such as fluid intelligence while others have not. We report the results of a study designed to examine two forms of working-memory training, one using a spatial n-back and the other a verbal complex span. Thirty-one undergraduates completed 4 weeks of n-back training and 32 completed 4 weeks of verbal complex span training. We also included two active control groups. One group trained on a non-adaptive version of n-back and the other trained on a real-time strategy video game. All participants completed pre- and post-training measures of a large battery of transfer tasks used to create composite measures of short-term and working memory in both verbal and visuo-spatial domains as well as verbal reasoning and fluid intelligence. We only found clear evidence for near transfer from the spatial n-back training to new forms of n-back, and this was the case for both adaptive and non-adaptive n-back.

The Contributions of Emotional Intelligence and Social Support for Adaptive Career Progress among Italian Youth

ERIC Educational Resources Information Center

Di Fabio, Annamaria; Kenny, Maureen E.

2015-01-01

Drawing from career construction and positive youth development perspectives, this study explores, among 254 Italian high school students, the relationship between emotional intelligence (EI) and support from friends and teachers with indices of adaptive career development. Results from the full canonical correlational model revealed that…

Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field

ERIC Educational Resources Information Center

Magnisalis, I.; Demetriadis, S.; Karakostas, A.

2011-01-01

This study critically reviews the recently published scientific literature on the design and impact of adaptive and intelligent systems for collaborative learning support (AICLS) systems. The focus is threefold: 1) analyze critical design issues of AICLS systems and organize them under a unifying classification scheme, 2) present research evidence…

Position-adaptive explosive detection concepts for swarming micro-UAVs

NASA Astrophysics Data System (ADS)

Selmic, Rastko R.; Mitra, Atindra

2008-04-01

We have formulated a series of position-adaptive sensor concepts for explosive detection applications using swarms of micro-UAV's. These concepts are a generalization of position-adaptive radar concepts developed for challenging conditions such as urban environments. For radar applications, this concept is developed with platforms within a UAV swarm that spatially-adapt to signal leakage points on the perimeter of complex clutter environments to collect information on embedded objects-of-interest. The concept is generalized for additional sensors applications by, for example, considering a wooden cart that contains explosives. We can formulate system-of-systems concepts for a swarm of micro-UAV's in an effort to detect whether or not a given cart contains explosives. Under this new concept, some of the members of the UAV swarm can serve as position-adaptive "transmitters" by blowing air over the cart and some of the members of the UAV swarm can serve as position-adaptive "receivers" that are equipped with chem./bio sensors that function as "electronic noses". The final objective can be defined as improving the particle count for the explosives in the air that surrounds a cart via development of intelligent position-adaptive control algorithms in order to improve the detection and false-alarm statistics. We report on recent simulation results with regard to designing optimal sensor placement for explosive or other chemical agent detection. This type of information enables the development of intelligent control algorithms for UAV swarm applications and is intended for the design of future system-of-systems with adaptive intelligence for advanced surveillance of unknown regions. Results are reported as part of a parametric investigation where it is found that the probability of contaminant detection depends on the air flow that carries contaminant particles, geometry of the surrounding space, leakage areas, and other factors. We present a concept of position-adaptive detection (i.e. based on the example in the previous paragraph) consisting of position-adaptive fluid actuators (fans) and position-adaptive sensors. Based on these results, a preliminary analysis of sensor requirements for these fluid actuators and sensors is presented for small-UAVs in a field-enabled explosive detection environment. The computational fluid dynamics (CFD) simulation software Fluent is used to simulate the air flow in the corridor model containing a box with explosive particles. It is found that such flow is turbulent with Reynolds number greater than 106. Simulation methods and results are presented which show particle velocity and concentration distribution throughout the closed box. The results indicate that the CFD-based method can be used for other sensor placement and deployment optimization problems. These techniques and results can be applied towards the development of future system-of-system UAV swarms for defense, homeland defense, and security applications.

Sliding Mode Control (SMC) of Robot Manipulator via Intelligent Controllers

NASA Astrophysics Data System (ADS)

Kapoor, Neha; Ohri, Jyoti

2017-02-01

Inspite of so much research, key technical problem, naming chattering of conventional, simple and robust SMC is still a challenge to the researchers and hence limits its practical application. However, newly developed soft computing based techniques can provide solution. In order to have advantages of conventional and heuristic soft computing based control techniques, in this paper various commonly used intelligent techniques, neural network, fuzzy logic and adaptive neuro fuzzy inference system (ANFIS) have been combined with sliding mode controller (SMC). For validation, proposed hybrid control schemes have been implemented for tracking a predefined trajectory by robotic manipulator, incorporating structured and unstructured uncertainties in the system. After reviewing numerous papers, all the commonly occurring uncertainties like continuous disturbance, uniform random white noise, static friction like coulomb friction and viscous friction, dynamic friction like Dhal friction and LuGre friction have been inserted in the system. Various performance indices like norm of tracking error, chattering in control input, norm of input torque, disturbance rejection, chattering rejection have been used. Comparative results show that with almost eliminated chattering the intelligent SMC controllers are found to be more efficient over simple SMC. It has also been observed from results that ANFIS based controller has the best tracking performance with the reduced burden on the system. No paper in the literature has found to have all these structured and unstructured uncertainties together for motion control of robotic manipulator.

Evolutionary programming for goal-driven dynamic planning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Guest, Clark C.; Ross, David O.

2002-03-01

Many complex artificial intelligence (IA) problems are goal- driven in nature and the opportunity exists to realize the benefits of a goal-oriented solution. In many cases, such as in command and control, a goal-oriented approach may be the only option. One of many appropriate applications for such an approach is War Gaming. War Gaming is an important tool for command and control because it provides a set of alternative courses of actions so that military leaders can contemplate their next move in the battlefield. For instance, when making decisions that save lives, it is necessary to completely understand the consequences of a given order. A goal-oriented approach provides a slowly evolving tractably reasoned solution that inherently follows one of the principles of war: namely concentration on the objective. Future decision-making will depend not only on the battlefield, but also on a virtual world where military leaders can wage wars and determine their options by playing computer war games much like the real world. The problem with these games is that the built-in AI does not learn nor adapt and many times cheats, because the intelligent player has access to all the information, while the user has access to limited information provided on a display. These games are written for the purpose of entertainment and actions are calculated a priori and off-line, and are made prior or during their development. With these games getting more sophisticated in structure and less domain specific in scope, there needs to be a more general intelligent player that can adapt and learn in case the battlefield situations or the rules of engagement change. One such war game that might be considered is Risk. Risk incorporates the principles of war, is a top-down scalable model, and provides a good application for testing a variety of goal- oriented AI approaches. By integrating a goal-oriented hybrid approach, one can develop a program that plays the Risk game effectively and move one step closer to solving more difficult real-world AI problems. Using a hybrid approach that includes adaptation via evolutionary computation for the intelligent planning of a Risk player's turn provides better dynamic intelligent planning than more uniform approaches.

An intelligent agent for optimal river-reservoir system management

NASA Astrophysics Data System (ADS)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

NASA Technical Reports Server (NTRS)

Hanson, Curt; Schaefer, Jacob; Burken, John J.; Larson, David; Johnson, Marcus

2014-01-01

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

Knowledge Flow Mesh and Its Dynamics: A Decision Support Environment

DTIC Science & Technology

2008-06-01

paper was the ability of the United States military to achieve dominance through information superiority. The use of intelligent sensors and... Intelligence Agency, National Security Agency, Defense Intelligence Agency, and individual Service intelligence agencies). In fact, these edge entities would... intelligence , design, choice, and implementation. 6. Support variety of decision processes and styles. 7. DSS should be adaptable and flexible. 8. DSS

Teachers' perceptions of students with speech sound disorders: a quantitative and qualitative analysis.

PubMed

Overby, Megan; Carrell, Thomas; Bernthal, John

2007-10-01

This study examined 2nd-grade teachers' perceptions of the academic, social, and behavioral competence of students with speech sound disorders (SSDs). Forty-eight 2nd-grade teachers listened to 2 groups of sentences differing by intelligibility and pitch but spoken by a single 2nd grader. For each sentence group, teachers rated the speaker's academic, social, and behavioral competence using an adapted version of the Teacher Rating Scale of the Self-Perception Profile for Children (S. Harter, 1985) and completed 3 open-ended questions. The matched-guise design controlled for confounding speaker and stimuli variables that were inherent in prior studies. Statistically significant differences in teachers' expectations of children's academic, social, and behavioral performances were found between moderately intelligible and normal intelligibility speech. Teachers associated moderately intelligible low-pitched speech with more behavior problems than moderately intelligible high-pitched speech or either pitch with normal intelligibility. One third of the teachers reported that they could not accurately predict a child's school performance based on the child's speech skills, one third of the teachers causally related school difficulty to SSD, and one third of the teachers made no comment. Intelligibility and speaker pitch appear to be speech variables that influence teachers' perceptions of children's school performance.

Initial Evaluation of the Intelligent Multi-UxV Planner with Adaptive Collaborative/Control Technologies (IMPACT)

DTIC Science & Technology

2017-02-17

Psychology. Brooke, J. (1996). SUS: a ‘quick and dirty ’ usability scale. In P. Jordan, B. Thomas, I. McClelland, & B. Weerdmeester (Eds.), Usability...level modeling, International Journal of Human Computer Studies, Vol. 45(3). Menzies, T. (1996b). On the Practicality of Abductive Validation, ECAI...1). Shima, T., & Rasmussen, S. (2009). UAV Cooperative Decision and Control: Challenges and Practical Approaches, SIAM Publications, ISBN

Robotic intelligence kernel

DOEpatents

Bruemmer, David J [Idaho Falls, ID

2009-11-17

A robot platform includes perceptors, locomotors, and a system controller. The system controller executes a robot intelligence kernel (RIK) that includes a multi-level architecture and a dynamic autonomy structure. The multi-level architecture includes a robot behavior level for defining robot behaviors, that incorporate robot attributes and a cognitive level for defining conduct modules that blend an adaptive interaction between predefined decision functions and the robot behaviors. The dynamic autonomy structure is configured for modifying a transaction capacity between an operator intervention and a robot initiative and may include multiple levels with at least a teleoperation mode configured to maximize the operator intervention and minimize the robot initiative and an autonomous mode configured to minimize the operator intervention and maximize the robot initiative. Within the RIK at least the cognitive level includes the dynamic autonomy structure.

A new modelling approach for zooplankton behaviour

NASA Astrophysics Data System (ADS)

Keiyu, A. Y.; Yamazaki, H.; Strickler, J. R.

We have developed a new simulation technique to model zooplankton behaviour. The approach utilizes neither the conventional artificial intelligence nor neural network methods. We have designed an adaptive behaviour network, which is similar to BEER [(1990) Intelligence as an adaptive behaviour: an experiment in computational neuroethology, Academic Press], based on observational studies of zooplankton behaviour. The proposed method is compared with non- "intelligent" models—random walk and correlated walk models—as well as observed behaviour in a laboratory tank. Although the network is simple, the model exhibits rich behavioural patterns similar to live copepods.

Lessons learned in the development of the STOL intelligent tutoring system

NASA Technical Reports Server (NTRS)

Seamster, Thomas; Baker, Clifford; Ames, Troy

1991-01-01

Lessons learned during the development of the NASA Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS), being developed at NASA Goddard Space Flight Center are presented. The purpose of the intelligent tutor is to train STOL users by adapting tutoring based on inferred student strengths and weaknesses. This system has been under development for over one year and numerous lessons learned have emerged. These observations are presented in three sections, as follows. The first section addresses the methodology employed in the development of the STOL ITS and briefly presents the ITS architecture. The second presents lessons learned, in the areas of: intelligent tutor development; documentation and reporting; cost and schedule control; and tools and shells effectiveness. The third section presents recommendations which may be considered by other ITS developers, addressing: access, use and selection of subject matter experts; steps involved in ITS development; use of ITS interface design prototypes as part of knowledge engineering; and tools and shells effectiveness.

Effectiveness of a computerised working memory training in adolescents with mild to borderline intellectual disabilities.

PubMed

Van der Molen, M J; Van Luit, J E H; Van der Molen, M W; Klugkist, I; Jongmans, M J

2010-05-01

The goal of this study is to evaluate the effectiveness of a computerised working memory (WM) training on memory, response inhibition, fluid intelligence, scholastic abilities and the recall of stories in adolescents with mild to borderline intellectual disabilities attending special education. A total of 95 adolescents with mild to borderline intellectual disabilities were randomly assigned to either a training adaptive to each child's progress in WM, a non-adaptive WM training, or to a control group. Verbal short-term memory (STM) improved significantly from pre- to post-testing in the group who received the adaptive training compared with the control group. The beneficial effect on verbal STM was maintained at follow-up and other effects became clear at that time as well. Both the adaptive and non-adaptive WM training led to higher scores at follow-up than at post-intervention on visual STM, arithmetic and story recall compared with the control condition. In addition, the non-adaptive training group showed a significant increase in visuo-spatial WM capacity. The current study provides the first demonstration that WM can be effectively trained in adolescents with mild to borderline intellectual disabilities.

Emotional Intelligence and Adaptive Success of Nurses Caring for People with Mental Retardation and Severe Behavior Problems

ERIC Educational Resources Information Center

Gerits, Linda; Derksen, Jan J. L.; Verbruggen, Antoine B.

2004-01-01

The emotional intelligence profiles, gender differences, and adaptive success of 380 Dutch nurses caring for people with mental retardation and accompanying severe behavior problems are reported. Data were collected with the Bar-On Emotional Quotient Inventory, Utrecht-Coping List, Utrecht-Burnout Scale, MMPI-2, and GAMA. Absence due to illness…

Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

ERIC Educational Resources Information Center

Rastegarmoghadam, Mahin; Ziarati, Koorush

2017-01-01

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

Standing stability enhancement with an intelligent powered transfemoral prosthesis.

PubMed

Lawson, Brian Edward; Varol, Huseyin Atakan; Goldfarb, Michael

2011-09-01

The authors have developed a ground-adaptive standing controller for a powered knee and ankle prosthesis which is intended to enhance the standing stability of transfemoral amputees. The finite-state-based controller includes a ground-searching phase, a slope estimation phase, and a joint impedance modulation phase, which together enable the prosthesis to quickly conform to the ground and provide stabilizing assistance to the user. In order to assess the efficacy of the ground-adaptive standing controller, the control approach was implemented on a powered knee and ankle prosthesis, and experimental data were collected on an amputee subject for a variety of standing conditions. Results indicate that the controller can estimate the ground slope within ±1° over a range of ±15°, and that it can provide appropriate joint impedances for standing on slopes within this range.

Cerebellar neurocontroller project, for aerospace applications, in a civilian neurocomputing initiative in the 'decade of the brain'

NASA Technical Reports Server (NTRS)

Pellionisz, Andras J.; Jorgensen, Charles C.; Werbos, Paul J.

1992-01-01

A key question is how to utilize civilian government agencies along with an industrial consortium to successfully complement the so far primarily defense-oriented neural network research. Civilian artificial neural system projects, such as artificial cerebellar neurocontrollers aimed at duplicating nature's existing neural network solutions for adaptive sensorimotor coordination, are proposed by such a synthesis. The cerebellum provides an intelligent interface between higher possibly symbolic levels of human intelligence and repetitious demands of real world conventional controllers. The generation of such intelligent interfaces could be crucial to the economic feasibility of the human settlement of space and an improvement in telerobotics techniques to permit the cost-effective exploitation of nonterrestrial materials and planetary exploration and monitoring. The authors propose a scientific framework within which such interagency activities could effectively cooperate.

AvantGuard: An Instrument to Explore Autonomy

DTIC Science & Technology

2007-11-01

Machinexii (FSM) concept  was long ago borrowed from process control engineering by workers in the field of  artificial   intelligence .  The FSM proposes that...UAVs and their human supervisors are in high demand as the mission of the Armed Services adapts to  the challenges of asymmetric conflict.  Intelligence ...system records  intelligence . Some is historic, some is automatic and most is the result  of the human and UAVs cooperating in the mission.  Time A

[Do Current German-Language Intelligence Tests Take into Consideration the Special Needs of Children with Disabilities?].

PubMed

Mickley, Manfred; Renner, Gerolf

2015-01-01

Do Current German-Language Intelligence Tests Take into Consideration the Special Needs of Children with Disabilities? A review of 23 German intelligence test manuals shows that test-authors do not exclude the use of their tests for children with disabilities. However, these special groups play a minor role in the construction, standardization, and validation of intelligence tests. There is no sufficient discussion and reflection concerning the issue which construct-irrelevant requirements may reduce the validity of the test or which individual test-adaptations are allowed or recommended. Intelligence testing of children with disabilities needs more empirical evidence on objectivity, reliability, and validity of the assessment-procedures employed. Future test construction and validation should systematically analyze construct-irrelevant variance in item format, the special needs of handicapped children, and should give hints for useful test-adaptations.

Intelligent manipulation technique for multi-branch robotic systems

NASA Technical Reports Server (NTRS)

Chen, Alexander Y. K.; Chen, Eugene Y. S.

1990-01-01

New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

Clinical research on intelligence seven needle therapy treated infants with brain damage syndrome.

PubMed

Liu, Zhen-Huan; Li, Ye-Rong; Lu, Yong-Lin; Chen, Jie-Kui

2016-06-01

To assess whether the intelligence seven needle therapy administered in infants with perinatal brain damage syndrome (BDS) as early intervention would improve patients' neural development. A randomized controlled trial was conducted. Sixty-four infants with BDS were randomly assigned to two groups: the comprehensive group and the control group. Both groups received routine early intervention; in addition, the comprehensive group received intelligence seven needle therapy. Before and after treatment, the Bayley Scale of Infant Development (BSID), Gesell Developmental Schedules, Gross Motor Function Measure (GMFM), transcranial doppler ultrasound (TCD), and cranial imaging examination were tested for contrast. After treatment, the comprehensive group showed significant difference in the Mental Development Index (MDI) scores of BSID compared with the control group (P<0.05), however, no significant discrepancy in psychomotor development index (PDI,P>0.05) was observed. The children's development quotients (DQ) of the comprehensive group exhibited a significant superiority in improving the social adaptation DQ of Gesell Developmental Schedules compared with the control group (P<0.01), as well as GMFM and linguistic and social intercourse (P<0.05). Again, no discrepancy in the fine movement DQ was found (P>0.05). The total scores of GMFM in the comprehensive group were higher than those in the control group (P<0.05). Comparing the two groups, the comprehensive group showed a significantly greater recovery rate than the control group on TCD after treatment (P<0.05). After 6-month follow-up, some recovery in both groups, specifically on broadening of brain outside space by cranial imaging examination were observed. The comprehensive group demonstrated a significantly greater recovery rate than the control group (P<0.05). The developmental level of intelligence, motion function, linguistic competence and social intercourse can be promoted for infants with perinatal BDS by treating with the intelligence seven needle therapy. This approach can improve the brain blood supply and promote the growth of frontal and parietal lobes.

Evolutionary Psychology and Intelligence Research

ERIC Educational Resources Information Center

Kanazawa, Satoshi

2010-01-01

This article seeks to unify two subfields of psychology that have hitherto stood separately: evolutionary psychology and intelligence research/differential psychology. I suggest that general intelligence may simultaneously be an evolved adaptation and an individual-difference variable. Tooby and Cosmides's (1990a) notion of random quantitative…

Adaptive learning and control for MIMO system based on adaptive dynamic programming.

PubMed

Fu, Jian; He, Haibo; Zhou, Xinmin

2011-07-01

Adaptive dynamic programming (ADP) is a promising research field for design of intelligent controllers, which can both learn on-the-fly and exhibit optimal behavior. Over the past decades, several generations of ADP design have been proposed in the literature, which have demonstrated many successful applications in various benchmarks and industrial applications. While many of the existing researches focus on multiple-inputs-single-output system with steepest descent search, in this paper we investigate a generalized multiple-input-multiple-output (GMIMO) ADP design for online learning and control, which is more applicable to a wide range of practical real-world applications. Furthermore, an improved weight-updating algorithm based on recursive Levenberg-Marquardt methods is presented and embodied in the GMIMO approach to improve its performance. Finally, we test the performance of this approach based on a practical complex system, namely, the learning and control of the tension and height of the looper system in a hot strip mill. Experimental results demonstrate that the proposed approach can achieve effective and robust performance.

Overlap Between Autism Spectrum Disorders and Attention Deficit Hyperactivity Disorder: Searching for Distinctive/Common Clinical Features.

PubMed

Craig, Francesco; Lamanna, Anna Linda; Margari, Francesco; Matera, Emilia; Simone, Marta; Margari, Lucia

2015-06-01

Recent studies support several overlapping traits between autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD), assuming the existence of a combined phenotype. The aim of our study was to evaluate the common or distinctive clinical features between ASD and ADHD in order to identify possible different phenotypes that could have a clinical value. We enrolled 181 subjects divided into four diagnostic groups: ADHD group, ASD group, ASD+ADHD group (that met diagnostic criteria for both ASD and ADHD), and control group. Intelligent quotient (IQ), emotional and behavior problems, ADHD symptoms, ASD symptoms, and adaptive behaviors were investigated through the following test: Wechsler Intelligence Scale for Children, Wechsler Preschool and Primary Scale of Intelligence or Leiter International Performances Scale Revised, Child Behavior Checklist, Conners' Rating Scales-Revised, SNAP-IV Rating Scale, the Social Communication Questionnaire, Vineland Adaptive Behavior Scales. The ASD+ADHD group differs from ADHD or ASD in some domains such as lower IQ mean level and a higher autistic symptoms severity. However, the ASD+ADHD group shares inattention and hyperactivity deficit and some emotional and behavior problems with the ADHD group, while it shares adaptive behavior impairment with ASD group. These findings provide a new understanding of clinical manifestation of ASD+ADHD phenotype, they may also inform a novel treatment target. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research.

Wireless powering and data telemetry for biomedical implants.

PubMed

Young, Darrin J

2009-01-01

Wireless powering and data telemetry techniques for two biomedical implant studies based on (1) wireless in vivo EMG sensor for intelligent prosthetic control and (2) adaptively RF powered implantable bio-sensing microsystem for real-time genetically engineered mice monitoring are presented. Inductive-coupling-based RF powering and passive data telemetry is effective for wireless in vivo EMG sensing, where the internal and external RF coils are positioned with a small separation distance and fixed orientation. Adaptively controlled RF powering and active data transmission are critical for mobile implant application such as real-time physiological monitoring of untethered laboratory animals. Animal implant studies have been successfully completed to demonstrate the wireless and batteryless in vivo sensing capabilities.

An Approach for Autonomy: A Collaborative Communication Framework for Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Dufrene, Warren Russell, Jr.

2005-01-01

Research done during the last three years has studied the emersion properties of Complex Adaptive Systems (CAS). The deployment of Artificial Intelligence (AI) techniques applied to remote Unmanned Aerial Vehicles has led the author to investigate applications of CAS within the field of Autonomous Multi-Agent Systems. The core objective of current research efforts is focused on the simplicity of Intelligent Agents (IA) and the modeling of these agents within complex systems. This research effort looks at the communication, interaction, and adaptability of multi-agents as applied to complex systems control. The embodiment concept applied to robotics has application possibilities within multi-agent frameworks. A new framework for agent awareness within a virtual 3D world concept is possible where the vehicle is composed of collaborative agents. This approach has many possibilities for applications to complex systems. This paper describes the development of an approach to apply this virtual framework to the NASA Goddard Space Flight Center (GSFC) tetrahedron structure developed under the Autonomous Nano Technology Swarm (ANTS) program and the Super Miniaturized Addressable Reconfigurable Technology (SMART) architecture program. These projects represent an innovative set of novel concepts deploying adaptable, self-organizing structures composed of many tetrahedrons. This technology is pushing current applied Agents Concepts to new levels of requirements and adaptability.

Computer hardware and software for robotic control

NASA Technical Reports Server (NTRS)

Davis, Virgil Leon

1987-01-01

The KSC has implemented an integrated system that coordinates state-of-the-art robotic subsystems. It is a sensor based real-time robotic control system performing operations beyond the capability of an off-the-shelf robot. The integrated system provides real-time closed loop adaptive path control of position and orientation of all six axes of a large robot; enables the implementation of a highly configurable, expandable testbed for sensor system development; and makes several smart distributed control subsystems (robot arm controller, process controller, graphics display, and vision tracking) appear as intelligent peripherals to a supervisory computer coordinating the overall systems.

Active control strategy for the running attitude of high-speed train under strong crosswind condition

NASA Astrophysics Data System (ADS)

Li, Decang; Meng, Jianjun; Bai, Huan; Xu, Ruxun

2018-07-01

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host-target computer technology provided by Matlab/Simulink.

Developing Rational-Empirical Views of Intelligent Adaptive Behavior

DTIC Science & Technology

2004-08-01

biological frame to the information processing model and outline our understanding of intentions and beliefs that co-exist with rational and...notion that the evolution of cognition has produced memory/ knowledge systems that specialize in the processing of particular types of information ...1 PERMIS 2004 Developing Rational-Empirical Views of Intelligent Adaptive Behavior Gary Berg-Cross, Knowledge Strategies Potomac, Maryland

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

2nd & 3rd Generation Vehicle Subsystems

NASA Technical Reports Server (NTRS)

2000-01-01

This paper contains viewgraph presentation on the "2nd & 3rd Generation Vehicle Subsystems" project. The objective behind this project is to design, develop and test advanced avionics, power systems, power control and distribution components and subsystems for insertion into a highly reliable and low-cost system for a Reusable Launch Vehicles (RLV). The project is divided into two sections: 3rd Generation Vehicle Subsystems and 2nd Generation Vehicle Subsystems. The following topics are discussed under the first section, 3rd Generation Vehicle Subsystems: supporting the NASA RLV program; high-performance guidance & control adaptation for future RLVs; Evolvable Hardware (EHW) for 3rd generation avionics description; Scaleable, Fault-tolerant Intelligent Network or X(trans)ducers (SFINIX); advance electric actuation devices and subsystem technology; hybrid power sources and regeneration technology for electric actuators; and intelligent internal thermal control. Topics discussed in the 2nd Generation Vehicle Subsystems program include: design, development and test of a robust, low-maintenance avionics with no active cooling requirements and autonomous rendezvous and docking systems; design and development of a low maintenance, high reliability, intelligent power systems (fuel cells and battery); and design of a low cost, low maintenance high horsepower actuation systems (actuators).

Who Needs Innate Ability to Succeed in Math and Literacy? Academic-Domain-Specific Theories of Intelligence about Peers versus Adults

ERIC Educational Resources Information Center

Gunderson, Elizabeth A.; Hamdan, Noora; Sorhagen, Nicole S.; D'Esterre, Alexander P.

2017-01-01

Individuals' implicit theories of intelligence exist on a spectrum, from believing intelligence is fixed and unchangeable, to believing it is malleable and can be improved with effort. A belief in malleable intelligence leads to adaptive responses to challenge and higher achievement. However, surprisingly little is known about the development of…

Development of fault tolerant adaptive control laws for aerospace systems

NASA Astrophysics Data System (ADS)

Perez Rocha, Andres E.

The main topic of this dissertation is the design, development and implementation of intelligent adaptive control techniques designed to maintain healthy performance of aerospace systems subjected to malfunctions, external parameter changes and/or unmodeled dynamics. The dissertation is focused on the development of novel adaptive control configurations that rely on non-linear functions that appear in the immune system of living organisms as main source of adaptation. One of the main goals of this dissertation is to demonstrate that these novel adaptive control architectures are able to improve overall performance and protect the system while reducing control effort and maintaining adequate operation outside bounds of nominal design. This research effort explores several phases, ranging from theoretical stability analysis, simulation and hardware implementation on different types of aerospace systems including spacecraft, aircraft and quadrotor vehicles. The results presented in this dissertation are focused on two main adaptivity approaches, the first one is intended for aerospace systems that do not attain large angles and use exact feedback linearization of Euler angle kinematics. A proof of stability is presented by means of the circle Criterion and Lyapunov's direct method. The second approach is intended for aerospace systems that can attain large attitude angles (e.g. space systems in gravity-less environments), the adaptation is incorporated on a baseline architecture that uses partial feedback linearization of quaternions kinematics. In this case, the closed loop stability was analyzed using Lyapunov's direct method and Barbalat's Lemma. It is expected that some results presented in this dissertation can contribute towards the validation and certification of direct adaptive controllers.

Mission planning for autonomous systems

NASA Technical Reports Server (NTRS)

Pearson, G.

1987-01-01

Planning is a necessary task for intelligent, adaptive systems operating independently of human controllers. A mission planning system that performs task planning by decomposing a high-level mission objective into subtasks and synthesizing a plan for those tasks at varying levels of abstraction is discussed. Researchers use a blackboard architecture to partition the search space and direct the focus of attention of the planner. Using advanced planning techniques, they can control plan synthesis for the complex planning tasks involved in mission planning.

Adolescent adaptive behavior profiles in Williams-Beuren syndrome, Down syndrome, and autism spectrum disorder.

PubMed

Del Cole, Carolina Grego; Caetano, Sheila Cavalcante; Ribeiro, Wagner; Kümmer, Arthur Melo E E; Jackowski, Andrea Parolin

2017-01-01

Adaptive behavior can be impaired in different neurodevelopmental disorders and may be influenced by confounding factors, such as intelligence quotient (IQ) and socioeconomic classification. Our main objective was to verify whether adaptive behavior profiles differ in three conditions-Williams Beuren syndrome (WBS), Down syndrome (DS), and autism spectrum disorder (ASD), as compared with healthy controls (HC) and with each other. Although the literature points towards each disorder having a characteristic profile, no study has compared profiles to establish the specificity of each one. A secondary objective was to explore potential interactions between the conditions and socioeconomic status, and whether this had any effect on adaptive behavior profiles. One hundred and five adolescents were included in the study. All adolescents underwent the following evaluations: the Vineland Adaptive Behavior Scale (VABS), the Wechsler Intelligence Scale for Children (WISC), and the Brazilian Economic Classification Criteria. Our results demonstrated that the WBS group performed better than the DS group in the communication domain, β = -15.08, t(3.45), p = .005, and better than the ASD group in the socialization domain, β = 8.92, t(-2.08), p = .013. The DS group also performed better than the ASD group in socialization, β = 16.98, t(-2.32), p = .024. IQ was an important confounding factor, and socioeconomic status had an important effect on the adaptive behavior of all groups. There is a heterogeneity regarding adaptive behavior profiles in WBS, DS, and ASD. These data are important to better design specific strategies related to the health and social care of each particular group.

TEx-Sys Model for Building Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Stankov, Slavomir; Rosic, Marko; Zitko, Branko; Grubisic, Ani

2008-01-01

Special classes of asynchronous e-learning systems are the intelligent tutoring systems which represent an advanced learning and teaching environment adaptable to individual student's characteristics. Authoring shells have an environment that enables development of the intelligent tutoring systems. In this paper we present, in entirety, for the…

Sleep Disturbances, Behavioural Problems and Adaptive Skills in Children with Down's Syndrome

ERIC Educational Resources Information Center

Kelmanson, Igor A.

2017-01-01

The study was performed in St. Petersburg in 2015 and comprised 34 children with diagnosed Down's syndrome (DS) aged 9-15 (mean 11) years (17 boys, 17 girls) who attended special schools. Control group was made up of 34 clinically healthy normal intelligence schoolchildren matched for age, sex and geographical distribution. The mothers were…

The Relationship Between Emotional Intelligence and Leader Performance

DTIC Science & Technology

2002-03-01

independence, and self-actualization), (2) Interpersonal EQ (comprising empathy, social responsibility, and interpersonal relationships), (3) Stress ...management EQ (comprising stress tolerance and impulse control), (4) Adaptability EQ (comprising reality testing, flexibility, and problem solving), and (5...explain the significance of the model or its particular sub- scales or categories. Thus, mixed models, and the claims associated with them have been

A new approach for designing self-organizing systems and application to adaptive control

NASA Technical Reports Server (NTRS)

Ramamoorthy, P. A.; Zhang, Shi; Lin, Yueqing; Huang, Song

1993-01-01

There is tremendous interest in the design of intelligent machines capable of autonomous learning and skillful performance under complex environments. A major task in designing such systems is to make the system plastic and adaptive when presented with new and useful information and stable in response to irrelevant events. A great body of knowledge, based on neuro-physiological concepts, has evolved as a possible solution to this problem. Adaptive resonance theory (ART) is a classical example under this category. The system dynamics of an ART network is described by a set of differential equations with nonlinear functions. An approach for designing self-organizing networks characterized by nonlinear differential equations is proposed.

Adaptive variable structure hierarchical fuzzy control for a class of high-order nonlinear dynamic systems.

PubMed

Mansouri, Mohammad; Teshnehlab, Mohammad; Aliyari Shoorehdeli, Mahdi

2015-05-01

In this paper, a novel adaptive hierarchical fuzzy control system based on the variable structure control is developed for a class of SISO canonical nonlinear systems in the presence of bounded disturbances. It is assumed that nonlinear functions of the systems be completely unknown. Switching surfaces are incorporated into the hierarchical fuzzy control scheme to ensure the system stability. A fuzzy soft switching system decides the operation area of the hierarchical fuzzy control and variable structure control systems. All the nonlinearly appeared parameters of conclusion parts of fuzzy blocks located in different layers of the hierarchical fuzzy control system are adjusted through adaptation laws deduced from the defined Lyapunov function. The proposed hierarchical fuzzy control system reduces the number of rules and consequently the number of tunable parameters with respect to the ordinary fuzzy control system. Global boundedness of the overall adaptive system and the desired precision are achieved using the proposed adaptive control system. In this study, an adaptive hierarchical fuzzy system is used for two objectives; it can be as a function approximator or a control system based on an intelligent-classic approach. Three theorems are proven to investigate the stability of the nonlinear dynamic systems. The important point about the proposed theorems is that they can be applied not only to hierarchical fuzzy controllers with different structures of hierarchical fuzzy controller, but also to ordinary fuzzy controllers. Therefore, the proposed algorithm is more general. To show the effectiveness of the proposed method four systems (two mechanical, one mathematical and one chaotic) are considered in simulations. Simulation results demonstrate the validity, efficiency and feasibility of the proposed approach to control of nonlinear dynamic systems. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Healthons: errorless healthcare with bionic hugs and no need for quality control.

PubMed

Bushko, Renata G

2005-01-01

Errorless, invisible, continuous and infrastructure-free healthcare should become our goal. In order to achieve that goal, we need to rapidly move from current episodic and emergency-driven "healthcare delivery system" to an intelligent and extelligent health environment. That requires introduction of distributed affective Intelligent Caring Creatures (ICCs) consisting of healthons. Healthons are tools combining prevention with diagnosis and treatment based on continuous monitoring and analyzing of vital signs and biochemistry. Unlike humans, who posses only two or three dimensions of thinking, healthons can assure errorless health because of their adaptability, flexibility, and multidimensional reasoning capability. ICCs can do "the right thing" based on (1) state-of-art medical knowledge, (2) data about emotional, physiological, and genetic state of a consumer and (3) moral values of a consumer. The transition to the intelligent health environment based on ICCs requires the solutions to many currently unsolved healthcare problems. This paper lists the unsolved problems (by analogy to mathematical unsolved problems list) and explains why errorless healthcare with bionic hugs and no need for quality control is possible.

Fuzzy regulator design for wind turbine yaw control.

PubMed

Theodoropoulos, Stefanos; Kandris, Dionisis; Samarakou, Maria; Koulouras, Grigorios

2014-01-01

This paper proposes the development of an advanced fuzzy logic controller which aims to perform intelligent automatic control of the yaw movement of wind turbines. The specific fuzzy controller takes into account both the wind velocity and the acceptable yaw error correlation in order to achieve maximum performance efficacy. In this way, the proposed yaw control system is remarkably adaptive to the existing conditions. In this way, the wind turbine is enabled to retain its power output close to its nominal value and at the same time preserve its yaw system from pointless movement. Thorough simulation tests evaluate the proposed system effectiveness.

EDITORIAL: Adaptive and active materials: Selected papers from the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 10) (Philadelphia, PA, USA, 28 September-1 October 2010) Adaptive and active materials: Selected papers from the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 10) (Philadelphia, PA, USA, 28 September-1 October 2010)

NASA Astrophysics Data System (ADS)

Brei, Diann

2011-09-01

The third annual meeting of the AMSE/AIAA Smart Materials, Adaptive Structures and Intelligent Systems Conference (SMASIS) took place in the heart of historic Philadelphia's cultural district, and included a pioneer banquet in the National Constitutional Center. The applications emphasis of the 2010 conference was reflected in keynote talks by Dr Alan Taub, vice president of General Motors global research and development, 'Smart materials in the automotive industry'; Dr Charles R Farrar, engineering institute leader at Los Alamos National Laboratory, 'Future directions for structural health monitoring of civil engineering infrastructure'; and Professor Christopher S Lynch of the University of California Los Angeles, 'Ferroelectric materials and their applications'. The SMASIS conference was divided into six technical symposia each of which included basic research, applied technological design and development, and industrial and governmental integrated system and application demonstrations. The six symposia were: SYMP 1 Multifunctional Materials; SYMP 2 Active Materials, Mechanics and Behavior; SYMP 3 Modeling, Simulation and Control; SYMP 4 Enabling Technologies and Integrated System Design; SYMP 5 Structural Health Monitoring/NDE; and SYMP 6 Bio-inspired Smart Materials and Structures. In addition, the conference introduced a new student and young professional development symposium. Authors of papers in the materials areas (symposia 1, 2 and 6) were invited to write a full journal article on their presentation topic for publication in this special issue of Smart Materials and Structures. This set of papers demonstrates the exceptional quality and originality of the conference presentations. We are appreciative of their efforts in producing this collection of highly relevant articles on smart materials.

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

Deal or no deal: can incentives encourage widespread adoption of intelligent speed adaptation devices?

PubMed

Chorlton, Kathryn; Hess, Stephane; Jamson, Samantha; Wardman, Mark

2012-09-01

Given the burden of injury, economic, environmental and social consequences associated with speeding, reducing road traffic speed remains a major priority. Intelligent speed adaptation (ISA) is a promising but controversial new in-vehicle system that provides drivers with support on the speed-control task. In order to model potential system uptake, this paper explores drivers' preferences for two different types of ISA given a number of alternative fiscal incentives and non-fiscal measures, using a stated preference approach. As would be expected with such a contentious issue, the analysis revealed the presence of significant variations in sensitivities and preferences in the sample. While a non-negligible part of the sample population has such strong opposition to ISA that no reasonable discounts or incentives would lead to them buying or accepting such a system, there is also a large part of the population that, if given the right incentives, would be willing or even keen to equip their vehicle with an ISA device. Copyright © 2011. Published by Elsevier Ltd.

Three-camera stereo vision for intelligent transportation systems

NASA Astrophysics Data System (ADS)

Bergendahl, Jason; Masaki, Ichiro; Horn, Berthold K. P.

1997-02-01

A major obstacle in the application of stereo vision to intelligent transportation system is high computational cost. In this paper, a PC based three-camera stereo vision system constructed with off-the-shelf components is described. The system serves as a tool for developing and testing robust algorithms which approach real-time performance. We present an edge based, subpixel stereo algorithm which is adapted to permit accurate distance measurements to objects in the field of view using a compact camera assembly. Once computed, the 3D scene information may be directly applied to a number of in-vehicle applications, such as adaptive cruise control, obstacle detection, and lane tracking. Moreover, since the largest computational costs is incurred in generating the 3D scene information, multiple applications that leverage this information can be implemented in a single system with minimal cost. On-road applications, such as vehicle counting and incident detection, are also possible. Preliminary in-vehicle road trial results are presented.

Emotional intelligence and attentional bias for threat-related emotion under stress.

PubMed

Davis, Sarah K

2018-06-01

Emotional intelligence (EI) can buffer potentially harmful effects of situational and chronic stressors to safeguard psychological wellbeing (e.g., Mikolajczak, Petrides, Coumans & Luminet, ), yet understanding how and when EI operates to promote adaptation remains a research priority. We explored whether EI (both trait and ability) modulated early attentional processing of threat-related emotion under conditions of stress. Using a dot probe paradigm, eye movement (fixation to emotive facial stimuli, relative to neutral) and manual reaction time data were collected from 161 adults aged 18-57 years (mean age = 25.24; SD = 8.81) exposed to either a stressful (failure task) or non-stressful (control) situation. Whilst emotion management ability and trait wellbeing corresponded to avoidance of negative emotion (angry and sad respectively), high trait sociability and emotionality related to a bias for negative emotions. With most effects not restricted to stressful conditions, it is unclear whether EI underscores 'adaptive' processing, which carries implications for school-based social and emotional learning programs. © 2018 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Teaching the Perpendicular Bisector: A Kinesthetic Approach

ERIC Educational Resources Information Center

Touval, Ayana

2011-01-01

Kinesthetic intelligence is one of the seven kinds of intelligence identified by Gardner's multiple intelligence theory (1983). The kinesthetic approach to teaching has numerous pedagogical advantages and can be adapted to the teaching of mathematics. This article describes a series of kinesthetic activities designed to explore the properties of…

Mathematical Intelligence and Mathematical Creativity: A Causal Relationship

ERIC Educational Resources Information Center

Tyagi, Tarun Kumar

2017-01-01

This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…

Intelligent Augmented Reality Training for Motherboard Assembly

ERIC Educational Resources Information Center

Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

2015-01-01

We investigate the combination of Augmented Reality (AR) with Intelligent Tutoring Systems (ITS) to assist with training for manual assembly tasks. Our approach combines AR graphics with adaptive guidance from the ITS to provide a more effective learning experience. We have developed a modular software framework for intelligent AR training…

Leadership Institute: Building Leadership Capacity through Emotional Intelligence

ERIC Educational Resources Information Center

Argabright, Karen J.; King, Jeff; Cochran, Graham R.; Chen, Claire Yueh-Ti

2013-01-01

Given the changing dynamics of society and the pressures on Extension organizations to adapt, leadership effectiveness has become a crucial element of success. The program presented here is designed to enhance individual emotional intelligence. Through in-depth engagement of the participants, they learn to apply dynamics of emotional intelligence,…

Bridging the Gap: Enhancing SNA Within the Marine Corps Intelligence Community

DTIC Science & Technology

2015-06-01

ENHANCING SNA WITHIN THE MARINE CORPS INTELLIGENCE COMMUNITY by Robert C. Schotter June 2015 Thesis Advisor: Raymond Buettner Co-Advisor...INTELLIGENCE COMMUNITY 5. FUNDING NUMBERS 6. AUTHOR(S) Robert C. Schotter 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate...United States Marine Corps and the Marine Corps’ intelligence community recognize that future adversaries are likely to be adaptive and complex. Both

Distributed control systems with incomplete and uncertain information

NASA Astrophysics Data System (ADS)

Tang, Jingpeng

Scientific and engineering advances in wireless communication, sensors, propulsion, and other areas are rapidly making it possible to develop unmanned air vehicles (UAVs) with sophisticated capabilities. UAVs have come to the forefront as tools for airborne reconnaissance to search for, detect, and destroy enemy targets in relatively complex environments. They potentially reduce risk to human life, are cost effective, and are superior to manned aircraft for certain types of missions. It is desirable for UAVs to have a high level of intelligent autonomy to carry out mission tasks with little external supervision and control. This raises important issues involving tradeoffs between centralized control and the associated potential to optimize mission plans, and decentralized control with great robustness and the potential to adapt to changing conditions. UAV capabilities have been extended several ways through armament (e.g., Hellfire missiles on Predator UAVs), increased endurance and altitude (e.g., Global Hawk), and greater autonomy. Some known barriers to full-scale implementation of UAVs are increased communication and control requirements as well as increased platform and system complexity. One of the key problems is how UAV systems can handle incomplete and uncertain information in dynamic environments. Especially when the system is composed of heterogeneous and distributed UAVs, the overall system complexity is increased under such conditions. Presented through the use of published papers, this dissertation lays the groundwork for the study of methodologies for handling incomplete and uncertain information for distributed control systems. An agent-based simulation framework is built to investigate mathematical approaches (optimization) and emergent intelligence approaches. The first paper provides a mathematical approach for systems of UAVs to handle incomplete and uncertain information. The second paper describes an emergent intelligence approach for UAVs, again in handling incomplete and uncertain information. The third paper combines mathematical and emergent intelligence approaches.

[Methods of artificial intelligence: a new trend in pharmacy].

PubMed

Dohnal, V; Kuca, K; Jun, D

2005-07-01

Artificial neural networks (ANN) and genetic algorithms are one group of methods called artificial intelligence. The application of ANN on pharmaceutical data can lead to an understanding of the inner structure of data and a possibility to build a model (adaptation). In addition, for certain cases it is possible to extract rules from data. The adapted ANN is prepared for the prediction of properties of compounds which were not used in the adaptation phase. The applications of ANN have great potential in pharmaceutical industry and in the interpretation of analytical, pharmacokinetic or toxicological data.

Real time AI expert system for robotic applications

NASA Technical Reports Server (NTRS)

Follin, John F.

1987-01-01

A computer controlled multi-robot process cell to demonstrate advanced technologies for the demilitarization of obsolete chemical munitions was developed. The methods through which the vision system and other sensory inputs were used by the artificial intelligence to provide the information required to direct the robots to complete the desired task are discussed. The mechanisms that the expert system uses to solve problems (goals), the different rule data base, and the methods for adapting this control system to any device that can be controlled or programmed through a high level computer interface are discussed.

Flight Test of an Adaptive Controller and Simulated Failure/Damage on the NASA NF-15B

NASA Technical Reports Server (NTRS)

Buschbacher, Mark; Maliska, Heather

2006-01-01

The method of flight-testing the Intelligent Flight Control System (IFCS) Second Generation (Gen-2) project on the NASA NF-15B is herein described. The Gen-2 project objective includes flight-testing a dynamic inversion controller augmented by a direct adaptive neural network to demonstrate performance improvements in the presence of simulated failure/damage. The Gen-2 objectives as implemented on the NASA NF-15B created challenges for software design, structural loading limitations, and flight test operations. Simulated failure/damage is introduced by modifying control surface commands, therefore requiring structural loads measurements. Flight-testing began with the validation of a structural loads model. Flight-testing of the Gen-2 controller continued, using test maneuvers designed in a sequenced approach. Success would clear the new controller with respect to dynamic response, simulated failure/damage, and with adaptation on and off. A handling qualities evaluation was conducted on the capability of the Gen-2 controller to restore aircraft response in the presence of a simulated failure/damage. Control room monitoring of loads sensors, flight dynamics, and controller adaptation, in addition to postflight data comparison to the simulation, ensured a safe methodology of buildup testing. Flight-testing continued without major incident to accomplish the project objectives, successfully uncovering strengths and weaknesses of the Gen-2 control approach in flight.

Comparison of adaptive critic-based and classical wide-area controllers for power systems.

PubMed

Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

2008-08-01

An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

Intelligent emissions controller for substance injection in the post-primary combustion zone of fossil-fired boilers

DOEpatents

Reifman, Jaques; Feldman, Earl E.; Wei, Thomas Y. C.; Glickert, Roger W.

2003-01-01

The control of emissions from fossil-fired boilers wherein an injection of substances above the primary combustion zone employs multi-layer feedforward artificial neural networks for modeling static nonlinear relationships between the distribution of injected substances into the upper region of the furnace and the emissions exiting the furnace. Multivariable nonlinear constrained optimization algorithms use the mathematical expressions from the artificial neural networks to provide the optimal substance distribution that minimizes emission levels for a given total substance injection rate. Based upon the optimal operating conditions from the optimization algorithms, the incremental substance cost per unit of emissions reduction, and the open-market price per unit of emissions reduction, the intelligent emissions controller allows for the determination of whether it is more cost-effective to achieve additional increments in emission reduction through the injection of additional substance or through the purchase of emission credits on the open market. This is of particular interest to fossil-fired electrical power plant operators. The intelligent emission controller is particularly adapted for determining the economical control of such pollutants as oxides of nitrogen (NO.sub.x) and carbon monoxide (CO) emitted by fossil-fired boilers by the selective introduction of multiple inputs of substances (such as natural gas, ammonia, oil, water-oil emulsion, coal-water slurry and/or urea, and combinations of these substances) above the primary combustion zone of fossil-fired boilers.

A platform for evolving intelligently interactive adversaries.

PubMed

Fogel, David B; Hays, Timothy J; Johnson, Douglas R

2006-07-01

Entertainment software developers face significant challenges in designing games with broad appeal. One of the challenges concerns creating nonplayer (computer-controlled) characters that can adapt their behavior in light of the current and prospective situation, possibly emulating human behaviors. This adaptation should be inherently novel, unrepeatable, yet within the bounds of realism. Evolutionary algorithms provide a suitable method for generating such behaviors. This paper provides background on the entertainment software industry, and details a prior and current effort to create a platform for evolving nonplayer characters with genetic and behavioral traits within a World War I combat flight simulator.

Systems Intelligence Inventory

ERIC Educational Resources Information Center

Törmänen, Juha; Hämäläinen, Raimo P.; Saarinen, Esa

2016-01-01

Purpose: Systems intelligence (SI) (Saarinen and Hämäläinen, 2004) is a construct defined as a person's ability to act intelligently within complex systems involving interaction and feedback. SI relates to our ability to act in systems and reason about systems to adaptively carry out productive actions within and with respect to systems such as…

Present Status and Challenges of Intellectual Assessment in India

ERIC Educational Resources Information Center

Basu, Jayanti

2016-01-01

Intelligence testing was one of the earliest interests of psychologists in India. Adaptation of Western intelligence tests has been a focus of psychologists in the first half of the last century. Indigenous development of intelligence tests has been attempted, but diversity of language and culture, complexity of school systems, and infrastructural…

Emotions and trait emotional intelligence among ultra-endurance runners.

PubMed

Lane, Andrew M; Wilson, Mathew

2011-07-01

The aim of this study was to investigate relationships between trait emotional intelligence and emotional state changes over the course of an ultra-endurance foot race covering a route of approximately 175 miles (282 km) and held in set stages over six days. A repeated measures field design that sought to maintain ecological validity was used. Trait emotional intelligence was defined as a relatively stable concept that should predict adaptive emotional states experienced over the duration of the race and therefore associate with pleasant emotions during a 6-stage endurance event. Thirty-four runners completed a self-report measure of trait emotional intelligence before the event started. Participants reported emotional states before and after each of the six races. Repeated measures ANOVA results showed significant variations in emotions over time and a main effect for trait emotional intelligence. Runners high in self-report trait emotional intelligence also reported higher pleasant and lower unpleasant emotions than runners low in trait emotional intelligence. Findings lend support to the notion that trait emotional intelligence associates with adaptive psychological states, suggesting that it may be a key individual difference that explains why some athletes respond to repeated bouts of hard exercise better than others. Future research should test the effectiveness of interventions designed to enhance trait emotional intelligence and examine the attendant impact on emotional responses to intense exercise during multi-stage events. Copyright © 2011. Published by Elsevier Ltd.

Online human training of a myoelectric prosthesis controller via actor-critic reinforcement learning.

PubMed

Pilarski, Patrick M; Dawson, Michael R; Degris, Thomas; Fahimi, Farbod; Carey, Jason P; Sutton, Richard S

2011-01-01

As a contribution toward the goal of adaptable, intelligent artificial limbs, this work introduces a continuous actor-critic reinforcement learning method for optimizing the control of multi-function myoelectric devices. Using a simulated upper-arm robotic prosthesis, we demonstrate how it is possible to derive successful limb controllers from myoelectric data using only a sparse human-delivered training signal, without requiring detailed knowledge about the task domain. This reinforcement-based machine learning framework is well suited for use by both patients and clinical staff, and may be easily adapted to different application domains and the needs of individual amputees. To our knowledge, this is the first my-oelectric control approach that facilitates the online learning of new amputee-specific motions based only on a one-dimensional (scalar) feedback signal provided by the user of the prosthesis. © 2011 IEEE

Cross-modal reorganization in cochlear implant users: Auditory cortex contributes to visual face processing.

PubMed

Stropahl, Maren; Plotz, Karsten; Schönfeld, Rüdiger; Lenarz, Thomas; Sandmann, Pascale; Yovel, Galit; De Vos, Maarten; Debener, Stefan

2015-11-01

There is converging evidence that the auditory cortex takes over visual functions during a period of auditory deprivation. A residual pattern of cross-modal take-over may prevent the auditory cortex to adapt to restored sensory input as delivered by a cochlear implant (CI) and limit speech intelligibility with a CI. The aim of the present study was to investigate whether visual face processing in CI users activates auditory cortex and whether this has adaptive or maladaptive consequences. High-density electroencephalogram data were recorded from CI users (n=21) and age-matched normal hearing controls (n=21) performing a face versus house discrimination task. Lip reading and face recognition abilities were measured as well as speech intelligibility. Evaluation of event-related potential (ERP) topographies revealed significant group differences over occipito-temporal scalp regions. Distributed source analysis identified significantly higher activation in the right auditory cortex for CI users compared to NH controls, confirming visual take-over. Lip reading skills were significantly enhanced in the CI group and appeared to be particularly better after a longer duration of deafness, while face recognition was not significantly different between groups. However, auditory cortex activation in CI users was positively related to face recognition abilities. Our results confirm a cross-modal reorganization for ecologically valid visual stimuli in CI users. Furthermore, they suggest that residual takeover, which can persist even after adaptation to a CI is not necessarily maladaptive. Copyright © 2015 Elsevier Inc. All rights reserved.

IVHM Framework for Intelligent Integration for Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre; Trevino, Luis C.; Watson, Michael D.

2005-01-01

Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, is the process of assessing, preserving, and restoring system functionality across flight and techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of Integrated Intelligent Vehicle Management (IIVM). These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, this framework integrates technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear that IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives. These systems include the following: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle Mission Planning, Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations.

Artificial intelligence: Learning to see and act

NASA Astrophysics Data System (ADS)

Schölkopf, Bernhard

2015-02-01

An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

Vision Guided Intelligent Robot Design And Experiments

NASA Astrophysics Data System (ADS)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Intelligent multi-sensor integrations

NASA Technical Reports Server (NTRS)

Volz, Richard A.; Jain, Ramesh; Weymouth, Terry

1989-01-01

Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.

A Bioinspired Mineral Hydrogel as a Self-Healable, Mechanically Adaptable Ionic Skin for Highly Sensitive Pressure Sensing.

PubMed

Lei, Zhouyue; Wang, Quankang; Sun, Shengtong; Zhu, Wencheng; Wu, Peiyi

2017-06-01

In the past two decades, artificial skin-like materials have received increasing research interests for their broad applications in artificial intelligence, wearable devices, and soft robotics. However, profound challenges remain in terms of imitating human skin because of its unique combination of mechanical and sensory properties. In this work, a bioinspired mineral hydrogel is developed to fabricate a novel type of mechanically adaptable ionic skin sensor. Due to its unique viscoelastic properties, the hydrogel-based capacitive sensor is compliant, self-healable, and can sense subtle pressure changes, such as a gentle finger touch, human motion, or even small water droplets. It might not only show great potential in applications such as artificial intelligence, human/machine interactions, personal healthcare, and wearable devices, but also promote the development of next-generation mechanically adaptable intelligent skin-like devices. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Intelligent bandwith compression

NASA Astrophysics Data System (ADS)

Tseng, D. Y.; Bullock, B. L.; Olin, K. E.; Kandt, R. K.; Olsen, J. D.

1980-02-01

The feasibility of a 1000:1 bandwidth compression ratio for image transmission has been demonstrated using image-analysis algorithms and a rule-based controller. Such a high compression ratio was achieved by first analyzing scene content using auto-cueing and feature-extraction algorithms, and then transmitting only the pertinent information consistent with mission requirements. A rule-based controller directs the flow of analysis and performs priority allocations on the extracted scene content. The reconstructed bandwidth-compressed image consists of an edge map of the scene background, with primary and secondary target windows embedded in the edge map. The bandwidth-compressed images are updated at a basic rate of 1 frame per second, with the high-priority target window updated at 7.5 frames per second. The scene-analysis algorithms used in this system together with the adaptive priority controller are described. Results of simulated 1000:1 band width-compressed images are presented. A video tape simulation of the Intelligent Bandwidth Compression system has been produced using a sequence of video input from the data base.

ELM-ART--An Interactive and Intelligent Web-Based Electronic Textbook

ERIC Educational Resources Information Center

Weber, Gerhard; Brusilovsky, Peter

2016-01-01

This paper present provides a broader view on ELM-ART, one of the first Web-based Intelligent Educational systems that offered a creative combination of two different paradigms--Intelligent Tutoring and Adaptive Hypermedia technologies. The unique dual nature of ELM-ART contributed to its long life and research impact and was a result of…

Intelligibility of Noise-Adapted and Clear Speech in Child, Young Adult, and Older Adult Talkers

ERIC Educational Resources Information Center

Smiljanic, Rajka; Gilbert, Rachael C.

2017-01-01

Purpose: This study examined intelligibility of conversational and clear speech sentences produced in quiet and in noise by children, young adults, and older adults. Relative talker intelligibility was assessed across speaking styles. Method: Sixty-one young adult participants listened to sentences mixed with speech-shaped noise at -5 dB…

Problem-Based Learning Pedagogies: Psychological Processes and Enhancement of Intelligences

ERIC Educational Resources Information Center

Tan, Oon-Seng

2007-01-01

Education in this 21st century is concerned with developing intelligences. Problem solving in real-world contexts involves multiple ways of knowing and learning. Intelligence in the real world involves not only learning how to do things effectively but also more importantly the ability to deal with novelty and growing our capacity to adapt, select…

Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

PubMed

Moore, J H

1995-06-01

A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

Fuzzy Regulator Design for Wind Turbine Yaw Control

PubMed Central

Koulouras, Grigorios

2014-01-01

This paper proposes the development of an advanced fuzzy logic controller which aims to perform intelligent automatic control of the yaw movement of wind turbines. The specific fuzzy controller takes into account both the wind velocity and the acceptable yaw error correlation in order to achieve maximum performance efficacy. In this way, the proposed yaw control system is remarkably adaptive to the existing conditions. In this way, the wind turbine is enabled to retain its power output close to its nominal value and at the same time preserve its yaw system from pointless movement. Thorough simulation tests evaluate the proposed system effectiveness. PMID:24693237

A Survey of Intelligent Control and Health Management Technologies for Aircraft Propulsion Systems

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Simon, Donald L.; Garg, Sanjay; Guo, Ten-Heui; Mercer, Carolyn; Behbahani, Alireza; Bajwa, Anupa; Jensen, Daniel T.

2005-01-01

Intelligent Control and Health Management technology for aircraft propulsion systems is much more developed in the laboratory than in practice. With a renewed emphasis on reducing engine life cycle costs, improving fuel efficiency, increasing durability and life, etc., driven by various government programs, there is a strong push to move these technologies out of the laboratory and onto the engine. This paper describes the existing state of engine control and on-board health management, and surveys some specific technologies under development that will enable an aircraft propulsion system to operate in an intelligent way--defined as self-diagnostic, self-prognostic, self-optimizing, and mission adaptable. These technologies offer the potential for creating extremely safe, highly reliable systems. The technologies will help to enable a level of performance that far exceeds that of today s propulsion systems in terms of reduction of harmful emissions, maximization of fuel efficiency, and minimization of noise, while improving system affordability and safety. Technologies that are discussed include various aspects of propulsion control, diagnostics, prognostics, and their integration. The paper focuses on the improvements that can be achieved through innovative software and algorithms. It concentrates on those areas that do not require significant advances in sensors and actuators to make them achievable, while acknowledging the additional benefit that can be realized when those technologies become available. The paper also discusses issues associated with the introduction of some of the technologies.

Development and Flight Testing of a Neural Network Based Flight Control System on the NF-15B Aircraft

NASA Technical Reports Server (NTRS)

Bomben, Craig R.; Smolka, James W.; Bosworth, John T.; Silliams-Hayes, Peggy S.; Burken, John J.; Larson, Richard R.; Buschbacher, Mark J.; Maliska, Heather A.

2006-01-01

The Intelligent Flight Control System (IFCS) project at the NASA Dryden Flight Research Center, Edwards AFB, CA, has been investigating the use of neural network based adaptive control on a unique NF-15B test aircraft. The IFCS neural network is a software processor that stores measured aircraft response information to dynamically alter flight control gains. In 2006, the neural network was engaged and allowed to learn in real time to dynamically alter the aircraft handling qualities characteristics in the presence of actual aerodynamic failure conditions injected into the aircraft through the flight control system. The use of neural network and similar adaptive technologies in the design of highly fault and damage tolerant flight control systems shows promise in making future aircraft far more survivable than current technology allows. This paper will present the results of the IFCS flight test program conducted at the NASA Dryden Flight Research Center in 2006, with emphasis on challenges encountered and lessons learned.

Water Level Prediction of Lake Cascade Mahakam Using Adaptive Neural Network Backpropagation (ANNBP)

NASA Astrophysics Data System (ADS)

Mislan; Gaffar, A. F. O.; Haviluddin; Puspitasari, N.

2018-04-01

A natural hazard information and flood events are indispensable as a form of prevention and improvement. One of the causes is flooding in the areas around the lake. Therefore, forecasting the surface of Lake water level to anticipate flooding is required. The purpose of this paper is implemented computational intelligence method namely Adaptive Neural Network Backpropagation (ANNBP) to forecasting the Lake Cascade Mahakam. Based on experiment, performance of ANNBP indicated that Lake water level prediction have been accurate by using mean square error (MSE) and mean absolute percentage error (MAPE). In other words, computational intelligence method can produce good accuracy. A hybrid and optimization of computational intelligence are focus in the future work.

Family functioning and trait emotional intelligence among youth.

PubMed

Alavi, Masoumeh; Mehrinezhad, Seyed Abolghasem; Amini, Mansour; Parthaman Singh, Minder Kaur A/P

2017-01-01

This study explored the relationship between family functioning and trait emotional intelligence among 547 respondents, between the age of 16 and 24 years from Malaysia, Iran, China, Sudan, Somalia, Morocco, the United Kingdom, Germany and the Netherlands. The questionnaires were Family Adaptability and Cohesion Evaluation Scale III and Trait Emotional Intelligence Questionnaire Short Form. Pearson correlation analysis revealed a significant relationship between family functioning and trait emotional intelligence. The higher the family functioning, the higher the trait emotional intelligence among youths. The findings provide a deeper understanding in the field of family functioning and trait emotional intelligence and have implications for parents, administrators and child relationships dealing with trait emotional intelligence.

Implementation of an Adaptive Controller System from Concept to Flight Test

NASA Technical Reports Server (NTRS)

Larson, Richard R.; Burken, John J.; Butler, Bradley S.

2009-01-01

The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.

Distribution of Intelligence in Airborne Air-Defense Mission Systems

DTIC Science & Technology

2001-03-01

their ,,creator" has given them a structure - not only a program - allowing them to organize themselves, to learn and to adapt themselves to changing...self- organization capability. They are modelled on the structures of the unconscious mind. "• By contrast, fuzzy logic/fuzzy control has developed an...of these techniques as indicated in Fig. 3 is of particular importance for achieving unprecedented levels of self- organization capability and

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow

NASA Astrophysics Data System (ADS)

Yu, Shaowei; Zhao, Xiangmo; Xu, Zhigang; Zhang, Licheng

2016-11-01

To evaluate the effects of velocity difference changes with memory in the intelligent transportation environment on the dynamics and fuel consumptions of traffic flow, we first investigate the linkage between velocity difference changes with memory and car-following behaviors with the measured data in cities, and then propose an improved cooperative car-following model considering multiple velocity difference changes with memory in the cooperative adaptive cruise control strategy, finally carry out several numerical simulations under the periodic boundary condition and at signalized intersections to explore how velocity difference changes with memory affect car's velocity, velocity fluctuation, acceleration and fuel consumptions in the intelligent transportation environment. The results show that velocity difference changes with memory have obvious effects on car-following behaviors, that the improved cooperative car-following model can describe the phase transition of traffic flow and estimate the evolution of traffic congestion, that the stability and fuel economy of traffic flow simulated by the improved car-following model with velocity difference changes with memory is obviously superior to those without velocity difference changes, and that taking velocity difference changes with memory into account in designing the advanced adaptive cruise control strategy can significantly improve the stability and fuel economy of traffic flow.

Towards Machine Learning of Motor Skills

NASA Astrophysics Data System (ADS)

Peters, Jan; Schaal, Stefan; Schölkopf, Bernhard

Autonomous robots that can adapt to novel situations has been a long standing vision of robotics, artificial intelligence, and cognitive sciences. Early approaches to this goal during the heydays of artificial intelligence research in the late 1980s, however, made it clear that an approach purely based on reasoning or human insights would not be able to model all the perceptuomotor tasks that a robot should fulfill. Instead, new hope was put in the growing wake of machine learning that promised fully adaptive control algorithms which learn both by observation and trial-and-error. However, to date, learning techniques have yet to fulfill this promise as only few methods manage to scale into the high-dimensional domains of manipulator robotics, or even the new upcoming trend of humanoid robotics, and usually scaling was only achieved in precisely pre-structured domains. In this paper, we investigate the ingredients for a general approach to motor skill learning in order to get one step closer towards human-like performance. For doing so, we study two major components for such an approach, i.e., firstly, a theoretically well-founded general approach to representing the required control structures for task representation and execution and, secondly, appropriate learning algorithms which can be applied in this setting.

Artificial Intelligence for Controlling Robotic Aircraft

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje

2005-01-01

A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

Sleep deprivation reduces perceived emotional intelligence and constructive thinking skills.

PubMed

Killgore, William D S; Kahn-Greene, Ellen T; Lipizzi, Erica L; Newman, Rachel A; Kamimori, Gary H; Balkin, Thomas J

2008-07-01

Insufficient sleep can adversely affect a variety of cognitive abilities, ranging from simple alertness to higher-order executive functions. Although the effects of sleep loss on mood and cognition are well documented, there have been no controlled studies examining its effects on perceived emotional intelligence (EQ) and constructive thinking, abilities that require the integration of affect and cognition and are central to adaptive functioning. Twenty-six healthy volunteers completed the Bar-On Emotional Quotient Inventory (EQi) and the Constructive Thinking Inventory (CTI) at rested baseline and again after 55.5 and 58 h of continuous wakefulness, respectively. Relative to baseline, sleep deprivation was associated with lower scores on Total EQ (decreased global emotional intelligence), Intrapersonal functioning (reduced self-regard, assertiveness, sense of independence, and self-actualization), Interpersonal functioning (reduced empathy toward others and quality of interpersonal relationships), Stress Management skills (reduced impulse control and difficulty with delay of gratification), and Behavioral Coping (reduced positive thinking and action orientation). Esoteric Thinking (greater reliance on formal superstitions and magical thinking processes) was increased. These findings are consistent with the neurobehavioral model suggesting that sleep loss produces temporary changes in cerebral metabolism, cognition, emotion, and behavior consistent with mild prefrontal lobe dysfunction.

Comparing Binaural Pre-processing Strategies II: Speech Intelligibility of Bilateral Cochlear Implant Users.

PubMed

Baumgärtel, Regina M; Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-12-30

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. © The Author(s) 2015.

Intelligence as the plasticity of instinct: George J. Romanes and Darwin's earthworms.

PubMed

Morganti, Federico

2011-01-01

In the following article I provide a brief analysis of George J. Romanes' conception of intelligence and its relationship with instincts. Through a careful reading of some key-passages from Mental Evolution in Animals (1883)--Romanes' chief work on the subject--I endeavour to show how the very notion of intelligence was related, in Romanes' thought, to individual adaptation to the environmental novelty. Also, I attempt to clarify in what sense, according to Romanes, this capacity was to be included among the factors of organic evolution. Lastly, I compare Romanes' view with that expressed in Darwin's last book, i.e. The Formation of Vegetable Mould through the Action of Worms (1881). I contend that the two scientists basically shared the same conception of the relationship between instincts and intelligence, which accounted not only for the need of phylogenetic continuity, but also for that of discontinuity due to adaptive divergence.

The Teachers Level of Emotional Intelligence Some of the Demographic Variables for Investigation

ERIC Educational Resources Information Center

Adilogullari, Ilhan

2011-01-01

The study aims to examine the level of emotional intelligence of some of the demographic variables of the teachers working in the province of Gaziantep. Acar (2002) adapted to Turkish by Bar-On Emotional Intelligence Ability Scale 5-item scale used in grading and answered 87. The study evaluated data; descriptive statistical methods (frequency,…

Bidirectional clear speech perception benefit for native and high-proficiency non-native talkers and listeners: Intelligibility and accentednessa

PubMed Central

Smiljanić, Rajka; Bradlow, Ann R.

2011-01-01

This study investigated how native language background interacts with speaking style adaptations in determining levels of speech intelligibility. The aim was to explore whether native and high proficiency non-native listeners benefit similarly from native and non-native clear speech adjustments. The sentence-in-noise perception results revealed that fluent non-native listeners gained a large clear speech benefit from native clear speech modifications. Furthermore, proficient non-native talkers in this study implemented conversational-to-clear speaking style modifications in their second language (L2) that resulted in significant intelligibility gain for both native and non-native listeners. The results of the accentedness ratings obtained for native and non-native conversational and clear speech sentences showed that while intelligibility was improved, the presence of foreign accent remained constant in both speaking styles. This suggests that objective intelligibility and subjective accentedness are two independent dimensions of non-native speech. Overall, these results provide strong evidence that greater experience in L2 processing leads to improved intelligibility in both production and perception domains. These results also demonstrated that speaking style adaptations along with less signal distortion can contribute significantly towards successful native and non-native interactions. PMID:22225056

Smart pitch control strategy for wind generation system using doubly fed induction generator

NASA Astrophysics Data System (ADS)

Raza, Syed Ahmed

A smart pitch control strategy for a variable speed doubly fed wind generation system is presented in this thesis. A complete dynamic model of DFIG system is developed. The model consists of the generator, wind turbine, aerodynamic and the converter system. The strategy proposed includes the use of adaptive neural network to generate optimized controller gains for pitch control. This involves the generation of controller parameters of pitch controller making use of differential evolution intelligent technique. Training of the back propagation neural network has been carried out for the development of an adaptive neural network. This tunes the weights of the network according to the system states in a variable wind speed environment. Four cases have been taken to test the pitch controller which includes step and sinusoidal changes in wind speeds. The step change is composed of both step up and step down changes in wind speeds. The last case makes use of scaled wind data collected from the wind turbine installed at King Fahd University beach front. Simulation studies show that the differential evolution based adaptive neural network is capable of generating the appropriate control to deliver the maximum possible aerodynamic power available from wind to the generator in an efficient manner by minimizing the transients.

Ramp - Metering Algorithms Evaluated within Simplified Conditions

NASA Astrophysics Data System (ADS)

Janota, Aleš; Holečko, Peter; Gregor, Michal; Hruboš, Marián

2017-12-01

Freeway networks reach their limits, since it is usually impossible to increase traffic volumes by indefinitely extending transport infrastructure through adding new traffic lanes. One of the possible solutions is to use advanced intelligent transport systems, particularly ramp metering systems. The paper shows how two particular algorithms of local and traffic-responsive control (Zone, ALINEA) can be adapted to simplified conditions corresponding to Slovak freeways. Both control strategies are modelled and simulated using PTV Vissim software, including the module VisVAP. Presented results demonstrate the properties of both control strategies, which are compared mutually as well as with the initial situation in which no control strategy is applied

Task oriented nonlinear control laws for telerobotic assembly operations

NASA Technical Reports Server (NTRS)

Walker, R. A.; Ward, L. S.; Elia, C. F.

1987-01-01

The goal of this research is to achieve very intelligent telerobotic controllers which are capable of receiving high-level commands from the human operator and implementing them in an adaptive manner in the object/task/manipulator workspace. Initiatives by the authors at Integrated Systems, Inc. to identify and develop the key technologies necessary to create such a flexible, highly programmable, telerobotic controller are presented. The focus of the discussion is on the modeling of insertion tasks in three dimensions and nonlinear implicit force feedback control laws which incorporate tool/workspace constraints. Preliminary experiments with dual arm beam assembly in 2-D are presented.

Dynamic and structural control utilizing smart materials and structures

NASA Technical Reports Server (NTRS)

Rogers, C. A.; Robertshaw, H. H.

1989-01-01

An account is given of several novel 'smart material' structural control concepts that are currently under development. The thrust of these investigations is the evolution of intelligent materials and structures superceding the recently defined variable-geometry trusses and shape memory alloy-reinforced composites; the substances envisioned will be able to autonomously evaluate emergent environmental conditions and adapt to them, and even change their operational objectives. While until now the primary objective of the developmental efforts presently discussed has been materials that mimic biological functions, entirely novel concepts may be formulated in due course.

Adaptive temperature profile control of a multizone crystal growth furnace

NASA Technical Reports Server (NTRS)

Batur, C.; Sharpless, R. B.; Duval, W. M. B.; Rosenthal, B. N.

1991-01-01

An intelligent measurement system is described which is used to assess the shape of a crystal while it is growing inside a multizone transparent furnace. A color video imaging system observes the crystal in real time, and determines the position and the shape of the interface. This information is used to evaluate the crystal growth rate, and to analyze the effects of translational velocity and temperature profiles on the shape of the interface. Creation of this knowledge base is the first step to incorporate image processing into furnace control.

Incipient fault detection and power system protection for spaceborne systems

NASA Technical Reports Server (NTRS)

Russell, B. Don; Hackler, Irene M.

1987-01-01

A program was initiated to study the feasibility of using advanced terrestrial power system protection techniques for spacecraft power systems. It was designed to enhance and automate spacecraft power distribution systems in the areas of safety, reliability and maintenance. The proposed power management/distribution system is described as well as security assessment and control, incipient and low current fault detection, and the proposed spaceborne protection system. It is noted that the intelligent remote power controller permits the implementation of digital relaying algorithms with both adaptive and programmable characteristics.

Extended time-to-collision measures for road traffic safety assessment.

PubMed

Minderhoud, M M; Bovy, P H

2001-01-01

This article describes two new safety indicators based on the time-to-collision notion suitable for comparative road traffic safety analyses. Such safety indicators can be applied in the comparison of a do-nothing case with an adapted situation, e.g. the introduction of intelligent driver support systems. In contrast to the classical time-to-collision value, measured at a cross section, the improved safety indicators use vehicle trajectories collected over a specific time horizon for a certain roadway segment to calculate the overall safety indicator value. Vehicle-specific indicator values as well as safety-critical probabilities can easily be determined from the developed safety measures. Application of the derived safety indicators is demonstrated for the assessment of the potential safety impacts of driver support systems from which it appears that some Autonomous Intelligent Cruise Control (AICC) designs are more safety-critical than the reference case without these systems. It is suggested that the indicator threshold value to be applied in the safety assessment has to be adapted when advanced AICC-systems with safe characteristics are introduced.

On the integration of reinforcement learning and approximate reasoning for control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

The author discusses the importance of strengthening the knowledge representation characteristic of reinforcement learning techniques using methods such as approximate reasoning. The ARIC (approximate reasoning-based intelligent control) architecture is an example of such a hybrid approach in which the fuzzy control rules are modified (fine-tuned) using reinforcement learning. ARIC also demonstrates that it is possible to start with an approximately correct control knowledge base and learn to refine this knowledge through further experience. On the other hand, techniques such as the TD (temporal difference) algorithm and Q-learning establish stronger theoretical foundations for their use in adaptive control and also in stability analysis of hybrid reinforcement learning and approximate reasoning-based controllers.

Adaptive routing in wireless communication networks using swarm intelligence

NASA Technical Reports Server (NTRS)

Arabshahi, P.; Gray, A.; Kassabalidis, I.; Das, A.; Narayanan, S.; Sharkawi, M. El; Marks, R. J.

2001-01-01

In this paper we focus on the network routing problem, and survey swarm intelligent approaches for its efficient solution, after a brief overview of power-aware routing schemes, which are important in the network examples outlined above.

Mobile robot navigation modulated by artificial emotions.

PubMed

Lee-Johnson, C P; Carnegie, D A

2010-04-01

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

Recent developments of artificial intelligence in drying of fresh food: A review.

PubMed

Sun, Qing; Zhang, Min; Mujumdar, Arun S

2018-03-01

Intellectualization is an important direction of drying development and artificial intelligence (AI) technologies have been widely used to solve problems of nonlinear function approximation, pattern detection, data interpretation, optimization, simulation, diagnosis, control, data sorting, clustering, and noise reduction in different food drying technologies due to the advantages of self-learning ability, adaptive ability, strong fault tolerance and high degree robustness to map the nonlinear structures of arbitrarily complex and dynamic phenomena. This article presents a comprehensive review on intelligent drying technologies and their applications. The paper starts with the introduction of basic theoretical knowledge of ANN, fuzzy logic and expert system. Then, we summarize the AI application of modeling, predicting, and optimization of heat and mass transfer, thermodynamic performance parameters, and quality indicators as well as physiochemical properties of dried products in artificial biomimetic technology (electronic nose, computer vision) and different conventional drying technologies. Furthermore, opportunities and limitations of AI technique in drying are also outlined to provide more ideas for researchers in this area.

Research on intelligent algorithm of electro - hydraulic servo control system

NASA Astrophysics Data System (ADS)

Wang, Yannian; Zhao, Yuhui; Liu, Chengtao

2017-09-01

In order to adapt the nonlinear characteristics of the electro-hydraulic servo control system and the influence of complex interference in the industrial field, using a fuzzy PID switching learning algorithm is proposed and a fuzzy PID switching learning controller is designed and applied in the electro-hydraulic servo controller. The designed controller not only combines the advantages of the fuzzy control and PID control, but also introduces the learning algorithm into the switching function, which makes the learning of the three parameters in the switching function can avoid the instability of the system during the switching between the fuzzy control and PID control algorithms. It also makes the switch between these two control algorithm more smoother than that of the conventional fuzzy PID.

Pupil Diameter Tracks the Exploration-Exploitation Trade-off during Analogical Reasoning and Explains Individual Differences in Fluid Intelligence.

PubMed

Hayes, Taylor R; Petrov, Alexander A

2016-02-01

The ability to adaptively shift between exploration and exploitation control states is critical for optimizing behavioral performance. Converging evidence from primate electrophysiology and computational neural modeling has suggested that this ability may be mediated by the broad norepinephrine projections emanating from the locus coeruleus (LC) [Aston-Jones, G., & Cohen, J. D. An integrative theory of locus coeruleus-norepinephrine function: Adaptive gain and optimal performance. Annual Review of Neuroscience, 28, 403-450, 2005]. There is also evidence that pupil diameter covaries systematically with LC activity. Although imperfect and indirect, this link makes pupillometry a useful tool for studying the locus coeruleus norepinephrine system in humans and in high-level tasks. Here, we present a novel paradigm that examines how the pupillary response during exploration and exploitation covaries with individual differences in fluid intelligence during analogical reasoning on Raven's Advanced Progressive Matrices. Pupillometry was used as a noninvasive proxy for LC activity, and concurrent think-aloud verbal protocols were used to identify exploratory and exploitative solution periods. This novel combination of pupillometry and verbal protocols from 40 participants revealed a decrease in pupil diameter during exploitation and an increase during exploration. The temporal dynamics of the pupillary response was characterized by a steep increase during the transition to exploratory periods, sustained dilation for many seconds afterward, and followed by gradual return to baseline. Moreover, the individual differences in the relative magnitude of pupillary dilation accounted for 16% of the variance in Advanced Progressive Matrices scores. Assuming that pupil diameter is a valid index of LC activity, these results establish promising preliminary connections between the literature on locus coeruleus norepinephrine-mediated cognitive control and the literature on analogical reasoning and fluid intelligence.

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

Adaptive Behavior for Mobile Robots

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance

2009-01-01

The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.

The TurboLAN project. Phase 1: Protocol choices for high speed local area networks. Phase 2: TurboLAN Intelligent Network Adapter Card, (TINAC) architecture

NASA Technical Reports Server (NTRS)

Alkhatib, Hasan S.

1991-01-01

The hardware and the software architecture of the TurboLAN Intelligent Network Adapter Card (TINAC) are described. A high level as well as detailed treatment of the workings of various components of the TINAC are presented. The TINAC is divided into the following four major functional units: (1) the network access unit (NAU); (2) the buffer management unit; (3) the host interface unit; and (4) the node processor unit.

Growing up with Down syndrome: Development from 6 months to 10.7 years.

PubMed

Marchal, Jan Pieter; Maurice-Stam, Heleen; Houtzager, Bregje A; Rutgers van Rozenburg-Marres, Susanne L; Oostrom, Kim J; Grootenhuis, Martha A; van Trotsenburg, A S Paul

2016-12-01

We analysed developmental outcomes from a clinical trial early in life and its follow-up at 10.7 years in 123 children with Down syndrome. To determine 1) strengths and weaknesses in adaptive functioning and motor skills at 10.7 years, and 2) prognostic value of early-life characteristics (early developmental outcomes, parental and child characteristics, and comorbidity) for later intelligence, adaptive functioning and motor skills. We used standardized assessments of mental and motor development at ages 6, 12 and 24 months, and of intelligence, adaptive functioning and motor skills at 10.7 years. We compared strengths and weaknesses in adaptive functioning and motor skills by repeated-measures ANOVAs in the total group and in children scoring above-average versus below-average. The prognostic value of demographics, comorbidity and developmental outcomes was analysed by two-step regression. Socialisation was a stronger adaptive skill than Communication followed by Daily Living. Aiming and catching was a stronger motor skill than Manual dexterity, followed by Balance. Above-average and below-average scoring children showed different profiles of strengths and weaknesses. Gender, (the absence or presence of) infantile spasms and particularly 24-month mental functioning predicted later intelligence and adaptive functioning. Motor skills, however, appeared to be less well predicted by early life characteristics. These findings provide a reference for expected developmental levels and strengths and weaknesses in Down syndrome. Copyright © 2016 Elsevier Ltd. All rights reserved.

Materials learning from life: concepts for active, adaptive and autonomous molecular systems.

PubMed

Merindol, Rémi; Walther, Andreas

2017-09-18

Bioinspired out-of-equilibrium systems will set the scene for the next generation of molecular materials with active, adaptive, autonomous, emergent and intelligent behavior. Indeed life provides the best demonstrations of complex and functional out-of-equilibrium systems: cells keep track of time, communicate, move, adapt, evolve and replicate continuously. Stirred by the understanding of biological principles, artificial out-of-equilibrium systems are emerging in many fields of soft matter science. Here we put in perspective the molecular mechanisms driving biological functions with the ones driving synthetic molecular systems. Focusing on principles that enable new levels of functionalities (temporal control, autonomous structures, motion and work generation, information processing) rather than on specific material classes, we outline key cross-disciplinary concepts that emerge in this challenging field. Ultimately, the goal is to inspire and support new generations of autonomous and adaptive molecular devices fueled by self-regulating chemistry.

Adaptive Sniping for Volatile and Stable Continuous Double Auction Markets

NASA Astrophysics Data System (ADS)

Toft, I. E.; Bagnall, A. J.

This paper introduces a new adaptive sniping agent for the Continuous Double Auction. We begin by analysing the performance of the well known Kaplan sniper in two extremes of market conditions. We generate volatile and stable market conditions using the well known Zero Intelligence-Constrained agent and a new zero-intelligence agent Small Increment (SI). ZI-C agents submit random but profitable bids/offers and cause high volatility in prices and individual trader performance. Our new zero-intelligence agent, SI, makes small random adjustments to the outstanding bid/offer and hence is more cautious than ZI-C. We present results for SI in self-play and then analyse Kaplan in volatile and stable markets. We demonstrate that the non-adaptive Kaplan sniper can be configured to suit either market conditions, but no single configuration is performs well across both market types. We believe that in a dynamic auction environment where current or future market conditions cannot be predicted a viable sniping strategy should adapt its behaviour to suit prevailing market conditions. To this end, we propose the Adaptive Sniper (AS) agent for the CDA. AS traders classify sniping opportunities using a statistical model of market activity and adjust their classification thresholds using a Widrow-Hoff adapted search. Our AS agent requires little configuration, and outperforms the original Kaplan sniper in volatile and stable markets, and in a mixed trader type scenario that includes adaptive strategies from the literature.

Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

NASA Astrophysics Data System (ADS)

Ngoduy, D.

2013-10-01

This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.

E-Learning, Multiple Intelligences Theory (MI) and Learner-Centred Instruction: Adapting MI Learning Theoretical Principles to the Instruction of Health and Safety to Construction Managers

ERIC Educational Resources Information Center

McNamee, Paul; Madden, Dave; McNamee, Frank; Wall, John; Hurst, Alan; Vrasidas, Charalambos; Chanquoy, Lucile; Baccino, Thierry; Acar, Emrah; Onwy-Yazici, Ela; Jordan, Ann

2009-01-01

This paper describes an ongoing EU project concerned with developing an instructional design framework for virtual classes (VC) that is based on the theory of Multiple Intelligences (MI) (1983). The psychological theory of Multiple Intelligences (Gardner 1983) has received much credence within instructional design since its inception and has been…

Defining Adaptive Leadership in the Context of Mission Command

DTIC Science & Technology

2011-06-10

their best ( Goleman et al. 2002). The authors explain the connections between outstanding leaders and their emotional intelligence . 16 The...state,‖ having quick set intimacy and attaining personal elevation. The book Primal Leadership describes the importance of emotional intelligence in...their organizations succeed by using their emotional intelligence to create an atmosphere in which the organizations‘ members will want to do and be

Multi-objective decoupling algorithm for active distance control of intelligent hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Luo, Yugong; Chen, Tao; Li, Keqiang

2015-12-01

The paper presents a novel active distance control strategy for intelligent hybrid electric vehicles (IHEV) with the purpose of guaranteeing an optimal performance in view of the driving functions, optimum safety, fuel economy and ride comfort. Considering the complexity of driving situations, the objects of safety and ride comfort are decoupled from that of fuel economy, and a hierarchical control architecture is adopted to improve the real-time performance and the adaptability. The hierarchical control structure consists of four layers: active distance control object determination, comprehensive driving and braking torque calculation, comprehensive torque distribution and torque coordination. The safety distance control and the emergency stop algorithms are designed to achieve the safety and ride comfort goals. The optimal rule-based energy management algorithm of the hybrid electric system is developed to improve the fuel economy. The torque coordination control strategy is proposed to regulate engine torque, motor torque and hydraulic braking torque to improve the ride comfort. This strategy is verified by simulation and experiment using a forward simulation platform and a prototype vehicle. The results show that the novel control strategy can achieve the integrated and coordinated control of its multiple subsystems, which guarantees top performance of the driving functions and optimum safety, fuel economy and ride comfort.

Model Free iPID Control for Glycemia Regulation of Type-1 Diabetes.

PubMed

MohammadRidha, Taghreed; Ait-Ahmed, Mourad; Chaillous, Lucy; Krempf, Michel; Guilhem, Isabelle; Poirier, Jean-Yves; Moog, Claude H

2018-01-01

The objective is to design a fully automated glycemia controller of Type-1 Diabetes (T1D) in both fasting and postprandial phases on a large number of virtual patients. A model-free intelligent proportional-integral-derivative (iPID) is used to infuse insulin. The feasibility of iPID is tested in silico on two simulators with and without measurement noise. The first simulator is derived from a long-term linear time-invariant model. The controller is also validated on the UVa/Padova metabolic simulator on 10 adults under 25 runs/subject for noise robustness test. It was shown that without measurement noise, iPID mimicked the normal pancreatic secretion with a relatively fast reaction to meals as compared to a standard PID. With the UVa/Padova simulator, the robustness against CGM noise was tested. A higher percentage of time in target was obtained with iPID as compared to standard PID with reduced time spent in hyperglycemia. Two different T1D simulators tests showed that iPID detects meals and reacts faster to meal perturbations as compared to a classic PID. The intelligent part turns the controller to be more aggressive immediately after meals without neglecting safety. Further research is suggested to improve the computation of the intelligent part of iPID for such systems under actuator constraints. Any improvement can impact the overall performance of the model-free controller. The simple structure iPID is a step for PID-like controllers since it combines the classic PID nice properties with new adaptive features.

Cognitive Nonlinear Radar

DTIC Science & Technology

2013-01-01

intelligently selecting waveform parameters using adaptive algorithms. The adaptive algorithms optimize the waveform parameters based on (1) the EM...the environment. 15. SUBJECT TERMS cognitive radar, adaptive sensing, spectrum sensing, multi-objective optimization, genetic algorithms, machine...detection and classification block diagram. .........................................................6 Figure 5. Genetic algorithm block diagram

Genetic Fuzzy Trees for Intelligent Control of Unmanned Combat Aerial Vehicles

NASA Astrophysics Data System (ADS)

Ernest, Nicholas D.

Fuzzy Logic Control is a powerful tool that has found great success in a variety of applications. This technique relies less on complex mathematics and more "expert knowledge" of a system to bring about high-performance, resilient, and efficient control through linguistic classification of inputs and outputs and if-then rules. Genetic Fuzzy Systems (GFSs) remove the need of this expert knowledge and instead rely on a Genetic Algorithm (GA) and have similarly found great success. However, the combination of these methods suffer severely from scalability; the number of rules required to control the system increases exponentially with the number of states the inputs and outputs can take. Therefor GFSs have thus far not been applicable to complex, artificial intelligence type problems. The novel Genetic Fuzzy Tree (GFT) method breaks down complex problems hierarchically, makes sub-decisions when possible, and thus greatly reduces the burden on the GA. This development significantly changes the field of possible applications for GFSs. Within this study, this is demonstrated through applying this technique to a difficult air combat problem. Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) in the 2030 time-frame, it becomes apparent that the mission, flight, and ground controls will utilize the emerging paradigm of Intelligent Systems (IS); namely, the ability to learn, adapt, exhibit robustness in uncertain situations, make sense of the data collected in real-time and extrapolate when faced with scenarios significantly different from those used in training. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent controllers for these advanced unmanned craft as the first GFT. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs. Equipped with advanced sensors, a limited supply of Self-Defense Missiles (SDMs), and a recharging Laser Weapon System (LWS), these UCAVs can navigate a mission space, counter enemy threats, cope with losses in communications, and destroy mission-critical targets. Monte Carlo simulations of the resulting controllers were tested in mission scenarios that are distinct from the training scenarios to determine the training effectiveness in new environments and the presence of deep learning. Despite an incredibly large solution space, LETHA has demonstrated remarkable effectiveness in training intelligent controllers for the UCAV squadron and shown robustness to drastically changing states, uncertainty, and limited information while maintaining extreme levels of computational efficiency.

Mind the gap... in intelligence: re-examining the relationship between inequality and health.

PubMed

Kanazawa, Satoshi

2006-11-01

Wilkinson contends that economic inequality reduces the health and life expectancy of the whole population but his argument does not make sense within its own evolutionary framework. Recent evolutionary psychological theory suggests that the human brain, adapted to the ancestral environment, has difficulty comprehending and dealing with entities and situations that did not exist in the ancestral environment and that general intelligence evolved as a domain-specific adaptation to solve evolutionarily novel problems. Since most dangers to health in the contemporary society are evolutionarily novel, it follows that more intelligent individuals are better able to recognize and deal with such dangers and live longer. Consistent with the theory, the macro-level analyses show that income inequality and economic development have no effect on life expectancy at birth, infant mortality and age-specific mortality net of average intelligence quotient (IQ) in 126 countries. They also show that an average IQ has a very large and significant effect on population health but not in the evolutionarily familiar sub-Saharan Africa. At the micro level, the General Social Survey data show that, while both income and intelligence have independent positive effects on self-reported health, intelligence has a stronger effect than income. The data collectively suggest that individuals in wealthier and more egalitarian societies live longer and stay healthier, not because they are wealthier or more egalitarian but because they are more intelligent.

Sexual selection for indicators of intelligence.

PubMed

Miller, G

2000-01-01

Many traits in many species have evolved through sexual selection specifically to function as 'fitness indicators' that reveal good genes and good health. Sexually selected fitness indicators typically show (1) higher coefficients of phenotypic and genetic variation than survival traits, (2) at least moderate genetic heritabilities and (3) positive correlations with many aspects of an animal's general condition, including body size, body symmetry, parasite resistance, longevity and freedom from deleterious mutations. These diagnostic criteria also appear to describe human intelligence (the g factor). This paper argues that during human evolution, mate choice by both sexes focused increasingly on intelligence as a major heritable component of biological fitness. Many human-specific behaviours (such as conversation, music production, artistic ability and humour) may have evolved principally to advertise intelligence during courtship. Though these mental adaptations may be modular at the level of psychological functioning, their efficiencies may be tightly intercorrelated because they still tap into common genetic and neurophysiological variables associated with fitness itself. Although the g factor (like the superordinate factor of fitness itself) probably exists in all animal species, humans evolved an unusually high degree of interest in assessing each other's intelligence during courtship and other social interactions--and, consequently, a unique suite of highly g-loaded mental adaptations for advertising their intelligence to one another through linguistic and cultural interaction. This paper includes nine novel, testable predictions about human intelligence derived from sexual selection theory.

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.; Baker, Noel C.

2015-01-01

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Intelligent Instructional Systems in Military Training.

ERIC Educational Resources Information Center

Fletcher, J.D.; Zdybel, Frank

Intelligent instructional systems can be distinguished from more conventional approaches by the automation of instructional interaction and choice of strategy. This approach promises to reduce the costs of instructional materials preparation and to increase the adaptability and individualization of the instruction delivered. Tutorial simulation…

Three Billy Goats and Gardner.

ERIC Educational Resources Information Center

Merrefield, Gayle Emery

1997-01-01

Describes a Jewish Community Center's efforts to adapt Gardner's multiple-intelligences theory to a preschool special-education program. Since most students had moderate speech disorders, teachers decided to deemphasize linguistic expression in favor of the other seven intelligences. They created successful units exploring patterns and size…

A system for the delivery of programmable, adaptive stimulation intensity envelopes for drop foot correction applications.

PubMed

Breen, P P; O'Keeffe, D T; Conway, R; Lyons, G M

2006-03-01

We describe the design of an intelligent drop foot stimulator unit for use in conjunction with a commercial neuromuscular electrical nerve stimulation (NMES) unit, the NT2000. The developed micro-controller unit interfaces to a personal computer (PC) and a graphical user interface (GUI) allows the clinician to graphically specify the shape of the stimulation intensity envelope required for a subject undergoing drop foot correction. The developed unit is based on the ADuC812S micro-controller evaluation board from Analog Devices and uses two force sensitive resistor (FSR) based foot-switches to control application of stimulus. The unit has the ability to display to the clinician how the stimulus intensity envelope is being delivered during walking using a data capture capability. The developed system has a built-in algorithm to dynamically adjust the delivery of stimulus to reflect changes both within the gait cycle and from cycle to cycle. Thus, adaptive control of stimulus intensity is achieved.

Intelligent Sensors for Integrated Systems Health Management (ISHM)

NASA Technical Reports Server (NTRS)

Schmalzel, John L.

2008-01-01

IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

Assessment of Intelligent Tutoring Systems Technologies and Opportunities (Evaluation et opportunites des technologies des systemes de tutorat intelligents)

DTIC Science & Technology

2018-01-01

His research designs adaptive systems for online content, by integrating research in psychology and education, human- ANNEX A − INTELLIGENT TUTORING...related scientific activities that include systems engineering, operational research and analysis, synthesis, integration and validation of knowledge...System Analysis and Studies Panel • SCI Systems Concepts and Integration Panel • SET Sensors and Electronics Technology Panel These Panels and Group

Issues in Adaptive Planning

DTIC Science & Technology

1986-06-30

approach to the application of theorem proving to problem solving, Aritificial Intelligence 2 (1Q71), 18Q- 208. 4. Fikes, R., Hart, P. and Nilsson, N...by emphasizing the structure of knowledge. 1.2. Planning Literature The earliest work in planning in Artificial Intelligence grew out of the work on...References 1. Newell, A., Artificial Intelligence and the concept of mind, in Computer models of thought and language, Schank, R. and Colby, K. (editor

An embodied view of octopus neurobiology.

PubMed

Hochner, Binyamin

2012-10-23

Octopuses have a unique flexible body and unusual morphology, but nevertheless they are undoubtedly a great evolutionary success. They compete successfully with vertebrates in their ecological niche using a rich behavioral repertoire more typical of an intelligent predator which includes extremely effective defensive behavior--fast escape swimming and an astonishing ability to adapt their shape and color to their environment. The most obvious characteristic feature of an octopus is its eight long and flexible arms, but these pose a great challenge for achieving the level of motor and sensory information processing necessary for their behaviors. First, coordinating motion is a formidable task because of the infinite degrees of freedom that have to be controlled; and second, it is hard to use body coordinates in this flexible animal to represent sensory information in a central control system. Here I will review experimental results suggesting that these difficulties, arising from the animal's morphology, have imposed the evolution of unique brain/body/behavior relationships best explained as intelligent behavior which emerges from the octopus's embodied organization. The term 'intelligent embodiment' comes from robotics and refers to an approach to designing autonomous robots in which the behavior emerges from the dynamic physical and sensory interactions of the agent's materials, morphology and environment. Consideration of the unusual neurobiology of the octopus in the light of its unique morphology suggests that similar embodied principles are instrumental for understanding the emergence of intelligent behavior in all biological systems. Copyright © 2012 Elsevier Ltd. All rights reserved.

Adaptive Behavior of Young Urban Children with Developmental Disabilities.

ERIC Educational Resources Information Center

Vig, Susan; Jedrysek, Eleonora

1995-01-01

Assessment of 497 urban preschool children with developmental disabilities using the Vineland Adaptive Behavior Scales indicated a strong positive relationship between adaptive behavior and intelligence if measured globally. When Vineland domains were assessed separately, this relationship varied across domains and disability groups. With…

A Risk Management Architecture for Emergency Integrated Aircraft Control

NASA Technical Reports Server (NTRS)

McGlynn, Gregory E.; Litt, Jonathan S.; Lemon, Kimberly A.; Csank, Jeffrey T.

2011-01-01

Enhanced engine operation--operation that is beyond normal limits--has the potential to improve the adaptability and safety of aircraft in emergency situations. Intelligent use of enhanced engine operation to improve the handling qualities of the aircraft requires sophisticated risk estimation techniques and a risk management system that spans the flight and propulsion controllers. In this paper, an architecture that weighs the risks of the emergency and of possible engine performance enhancements to reduce overall risk to the aircraft is described. Two examples of emergency situations are presented to demonstrate the interaction between the flight and propulsion controllers to facilitate the enhanced operation.

Intelligent self-organization methods for wireless ad hoc sensor networks based on limited resources

NASA Astrophysics Data System (ADS)

Hortos, William S.

2006-05-01

A wireless ad hoc sensor network (WSN) is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. To a greater degree than the terminals found in mobile ad hoc networks (MANETs) for communications, sensor nodes are resource-constrained, with limited computational processing, bandwidth, memory, and power, and are typically unattended once in operation. Consequently, the level of information exchange among nodes, to support any complex adaptive algorithms to establish network connectivity and optimize throughput, not only deplete those limited resources and creates high overhead in narrowband communications, but also increase network vulnerability to eavesdropping by malicious nodes. Cooperation among nodes, critical to the mission of sensor networks, can thus be disrupted by the inappropriate choice of the method for self-organization. Recent published contributions to the self-configuration of ad hoc sensor networks, e.g., self-organizing mapping and swarm intelligence techniques, have been based on the adaptive control of the cross-layer interactions found in MANET protocols to achieve one or more performance objectives: connectivity, intrusion resistance, power control, throughput, and delay. However, few studies have examined the performance of these algorithms when implemented with the limited resources of WSNs. In this paper, self-organization algorithms for the initiation, operation and maintenance of a network topology from a collection of wireless sensor nodes are proposed that improve the performance metrics significant to WSNs. The intelligent algorithm approach emphasizes low computational complexity, energy efficiency and robust adaptation to change, allowing distributed implementation with the actual limited resources of the cooperative nodes of the network. Extensions of the algorithms from flat topologies to two-tier hierarchies of sensor nodes are presented. Results from a few simulations of the proposed algorithms are compared to the published results of other approaches to sensor network self-organization in common scenarios. The estimated network lifetime and extent under static resource allocations are computed.

Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control.

PubMed

Kim, Heekang; Kwon, Soon; Kim, Sungho

2016-07-08

This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen).

Fuzzy Adaptive Control for Intelligent Autonomous Space Exploration Problems

NASA Technical Reports Server (NTRS)

Esogbue, Augustine O.

1998-01-01

The principal objective of the research reported here is the re-design, analysis and optimization of our newly developed neural network fuzzy adaptive controller model for complex processes capable of learning fuzzy control rules using process data and improving its control through on-line adaption. The learned improvement is according to a performance objective function that provides evaluative feedback; this performance objective is broadly defined to meet long-range goals over time. Although fuzzy control had proven effective for complex, nonlinear, imprecisely-defined processes for which standard models and controls are either inefficient, impractical or cannot be derived, the state of the art prior to our work showed that procedures for deriving fuzzy control, however, were mostly ad hoc heuristics. The learning ability of neural networks was exploited to systematically derive fuzzy control and permit on-line adaption and in the process optimize control. The operation of neural networks integrates very naturally with fuzzy logic. The neural networks which were designed and tested using simulation software and simulated data, followed by realistic industrial data were reconfigured for application on several platforms as well as for the employment of improved algorithms. The statistical procedures of the learning process were investigated and evaluated with standard statistical procedures (such as ANOVA, graphical analysis of residuals, etc.). The computational advantage of dynamic programming-like methods of optimal control was used to permit on-line fuzzy adaptive control. Tests for the consistency, completeness and interaction of the control rules were applied. Comparisons to other methods and controllers were made so as to identify the major advantages of the resulting controller model. Several specific modifications and extensions were made to the original controller. Additional modifications and explorations have been proposed for further study. Some of these are in progress in our laboratory while others await additional support. All of these enhancements will improve the attractiveness of the controller as an effective tool for the on line control of an array of complex process environments.

An adaptive neuro fuzzy inference system controlled space cector pulse width modulation based HVDC light transmission system under AC fault conditions

NASA Astrophysics Data System (ADS)

Ajay Kumar, M.; Srikanth, N. V.

2014-03-01

In HVDC Light transmission systems, converter control is one of the major fields of present day research works. In this paper, fuzzy logic controller is utilized for controlling both the converters of the space vector pulse width modulation (SVPWM) based HVDC Light transmission systems. Due to its complexity in the rule base formation, an intelligent controller known as adaptive neuro fuzzy inference system (ANFIS) controller is also introduced in this paper. The proposed ANFIS controller changes the PI gains automatically for different operating conditions. A hybrid learning method which combines and exploits the best features of both the back propagation algorithm and least square estimation method is used to train the 5-layer ANFIS controller. The performance of the proposed ANFIS controller is compared and validated with the fuzzy logic controller and also with the fixed gain conventional PI controller. The simulations are carried out in the MATLAB/SIMULINK environment. The results reveal that the proposed ANFIS controller is reducing power fluctuations at both the converters. It also improves the dynamic performance of the test power system effectively when tested for various ac fault conditions.

Performance improvement of an active vibration absorber subsystem for an aircraft model using a bees algorithm based on multi-objective intelligent optimization

NASA Astrophysics Data System (ADS)

Zarchi, Milad; Attaran, Behrooz

2017-11-01

This study develops a mathematical model to investigate the behaviour of adaptable shock absorber dynamics for the six-degree-of-freedom aircraft model in the taxiing phase. The purpose of this research is to design a proportional-integral-derivative technique for control of an active vibration absorber system using a hydraulic nonlinear actuator based on the bees algorithm. This optimization algorithm is inspired by the natural intelligent foraging behaviour of honey bees. The neighbourhood search strategy is used to find better solutions around the previous one. The parameters of the controller are adjusted by minimizing the aircraft's acceleration and impact force as the multi-objective function. The major advantages of this algorithm over other optimization algorithms are its simplicity, flexibility and robustness. The results of the numerical simulation indicate that the active suspension increases the comfort of the ride for passengers and the fatigue life of the structure. This is achieved by decreasing the impact force, displacement and acceleration significantly.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

Is Intelligent Speed Adaptation ready for deployment?

PubMed

Carsten, Oliver

2012-09-01

There have been 30 years of research on Intelligent Speed Adaptation (ISA), the in-vehicle system that is designed to promote compliance with speed limits. Extensive trials of ISA in real-world driving have shown that ISA can significantly reduce speeding, users have been found to have generally positive attitudes and at least some sections of the public have been shown to be willing to purchase ISA systems. Yet large-scale deployment of a system that could deliver huge accident reductions is still by no means guaranteed. Copyright © 2012. Published by Elsevier Ltd.

Management Tools

NASA Technical Reports Server (NTRS)

1987-01-01

Manugistics, Inc. (formerly AVYX, Inc.) has introduced a new programming language for IBM and IBM compatible computers called TREES-pls. It is a resource management tool originating from the space shuttle, that can be used in such applications as scheduling, resource allocation project control, information management, and artificial intelligence. Manugistics, Inc. was looking for a flexible tool that can be applied to many problems with minimal adaptation. Among the non-government markets are aerospace, other manufacturing, transportation, health care, food and beverage and professional services.

Classification of intellectual disability using the Wechsler Intelligence Scale for Children: Full Scale IQ or General Abilities Index?

PubMed Central

KORIAKIN, TAYLOR A; MCCURDY, MARK D; PAPAZOGLOU, AIMILIA; PRITCHARD, ALISON E; ZABEL, T ANDREW; MAHONE, E MARK; JACOBSON, LISA A

2013-01-01

Aim We examined the implications of using the Full Scale Intelligence Quotient (FSIQ) versus the General Abilities Index (GAI) for determination of intellectual disability using the Wechsler Intelligence Scales for Children, fourth edition (WISC-IV). Method Children referred for neuropsychological assessment (543 males, 290 females; mean age 10y 5mo, SD 2y 9mo, range 6–16y) were administered the WISC-IV and the Adaptive Behavior Assessment System, Second Edition (ABAS-II). Results GAI and FSIQ were highly correlated; however, fewer children were identified as having intellectual disability using GAI (n=159) than when using FSIQ (n=196). Although the 44 children classified as having intellectual disability based upon FSIQ (but not GAI) had significantly higher adaptive functioning scores than those meeting intellectual disability criteria based upon both FSIQ and GAI, mean adaptive scores still fell within the impaired range. FSIQ and GAI were comparable in predicting impairments in adaptive functioning. Interpretation Using GAI rather than FSIQ in intellectual disability diagnostic decision making resulted in fewer individuals being diagnosed with intellectual disability; however, the mean GAI of the disqualified individuals was at the upper end of criteria for intellectual impairment (standard score 75), and these individuals remained adaptively impaired. As GAI and FSIQ were similarly predictive of overall adaptive functioning, the use of GAI for intellectual disability diagnostic decision making may be of limited value. PMID:23859669

Intelligent control for modeling of real-time reservoir operation, part II: artificial neural network with operating rule curves

NASA Astrophysics Data System (ADS)

Chang, Ya-Ting; Chang, Li-Chiu; Chang, Fi-John

2005-04-01

To bridge the gap between academic research and actual operation, we propose an intelligent control system for reservoir operation. The methodology includes two major processes, the knowledge acquired and implemented, and the inference system. In this study, a genetic algorithm (GA) and a fuzzy rule base (FRB) are used to extract knowledge based on the historical inflow data with a design objective function and on the operating rule curves respectively. The adaptive network-based fuzzy inference system (ANFIS) is then used to implement the knowledge, to create the fuzzy inference system, and then to estimate the optimal reservoir operation. To investigate its applicability and practicability, the Shihmen reservoir, Taiwan, is used as a case study. For the purpose of comparison, a simulation of the currently used M-5 operating rule curve is also performed. The results demonstrate that (1) the GA is an efficient way to search the optimal input-output patterns, (2) the FRB can extract the knowledge from the operating rule curves, and (3) the ANFIS models built on different types of knowledge can produce much better performance than the traditional M-5 curves in real-time reservoir operation. Moreover, we show that the model can be more intelligent for reservoir operation if more information (or knowledge) is involved.

The Evolutionary Origins of Hierarchy

PubMed Central

Huizinga, Joost; Clune, Jeff

2016-01-01

Hierarchical organization—the recursive composition of sub-modules—is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force–the cost of connections–promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics. PMID:27280881

The Evolutionary Origins of Hierarchy.

PubMed

Mengistu, Henok; Huizinga, Joost; Mouret, Jean-Baptiste; Clune, Jeff

2016-06-01

Hierarchical organization-the recursive composition of sub-modules-is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force-the cost of connections-promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.

"Group Intelligence": An Active Learning Exploration of Diversity in Evolution

ERIC Educational Resources Information Center

Parsons, Christopher J.; Salaita, Meisa K.; Hughes, Catherine H.; Lynn, David G.; Fristoe, Adam; Fristoe, Ariel; Grover, Martha A.

2017-01-01

"Group Intelligence" is an active learning, inquiry-based activity that introduces prebiotic chemistry, emergent complexity, and diversity's importance to adaptability across scales. Students explore the molecular emergence of order and function through theatrical exercises and games. Through 20 min of audio instruction and a discussion…

Soar: A Unified Theory of Cognition?

ERIC Educational Resources Information Center

Waldrop, M. Mitchell

1988-01-01

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

Intelligent Tutoring Systems for Literacy: Existing Technologies and Continuing Challenges

ERIC Educational Resources Information Center

Jacovina, Matthew E.; McNamara, Danielle S.

2017-01-01

In this chapter, we describe several intelligent tutoring systems (ITSs) designed to support student literacy through reading comprehension and writing instruction and practice. Although adaptive instruction can be a powerful tool in the literacy domain, developing these technologies poses significant challenges. For example, evaluating the…

Some Principles of Intelligent Tutoring.

ERIC Educational Resources Information Center

Ohlsson, Stellan

1986-01-01

Research on intelligent tutoring systems is discussed from the point of view of providing moment-by-moment adaptation of content and form of instruction to the changing cognitive needs of individual learners. Implications of this goal for cognitive diagnosis, subject matter analysis, teaching tactics, and teaching strategies are analyzed. (Author)

A New Look at NASA: Strategic Research In Information Technology

NASA Technical Reports Server (NTRS)

Alfano, David; Tu, Eugene (Technical Monitor)

2002-01-01

This viewgraph presentation provides information on research undertaken by NASA to facilitate the development of information technologies. Specific ideas covered here include: 1) Bio/nano technologies: biomolecular and nanoscale systems and tools for assembly and computing; 2) Evolvable hardware: autonomous self-improving, self-repairing hardware and software for survivable space systems in extreme environments; 3) High Confidence Software Technologies: formal methods, high-assurance software design, and program synthesis; 4) Intelligent Controls and Diagnostics: Next generation machine learning, adaptive control, and health management technologies; 5) Revolutionary computing: New computational models to increase capability and robustness to enable future NASA space missions.

Ventral striatal prediction error signaling is associated with dopamine synthesis capacity and fluid intelligence

PubMed Central

Schlagenhauf, Florian; Rapp, Michael A.; Huys, Quentin J. M.; Beck, Anne; Wüstenberg, Torsten; Deserno, Lorenz; Buchholz, Hans-Georg; Kalbitzer, Jan; Buchert, Ralph; Kienast, Thorsten; Cumming, Paul; Plotkin, Michail; Kumakura, Yoshitaka; Grace, Anthony A.; Dolan, Raymond J.; Heinz, Andreas

2013-01-01

Fluid intelligence represents the capacity for flexible problem solving and rapid behavioral adaptation. Rewards drive flexible behavioral adaptation, in part via a teaching signal expressed as reward prediction errors in the ventral striatum, which has been associated with phasic dopamine release in animal studies. We examined a sample of 28 healthy male adults using multimodal imaging and biological parametric mapping with 1) functional magnetic resonance imaging during a reversal learning task and 2) in a subsample of 17 subjects also with positron emission tomography using 6-[18F]fluoro-L-DOPA to assess dopamine synthesis capacity. Fluid intelligence was measured using a battery of nine standard neuropsychological tests. Ventral striatal BOLD correlates of reward prediction errors were positively correlated with fluid intelligence and, in the right ventral striatum, also inversely correlated with dopamine synthesis capacity (FDOPA Kinapp). When exploring aspects of fluid intelligence, we observed that prediction error signaling correlates with complex attention and reasoning. These findings indicate that individual differences in the capacity for flexible problem solving may be driven by ventral striatal activation during reward-related learning, which in turn proved to be inversely associated with ventral striatal dopamine synthesis capacity. PMID:22344813

Architecture of cognitive flexibility revealed by lesion mapping

PubMed Central

Barbey, Aron K.; Colom, Roberto; Grafman, Jordan

2013-01-01

Neuroscience has made remarkable progress in understanding the architecture of human intelligence, identifying a distributed network of brain structures that support goal-directed, intelligent behavior. However, the neural foundations of cognitive flexibility and adaptive aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 149) that investigates the neural bases of key competencies of cognitive flexibility (i.e., mental flexibility and the fluent generation of new ideas) and systematically examine their contributions to a broad spectrum of cognitive and social processes, including psychometric intelligence (Wechsler Adult Intelligence Scale), emotional intelligence (Mayer, Salovey, Caruso Emotional Intelligence Test), and personality (Neuroticism–Extraversion–Openness Personality Inventory). Latent variable modeling was applied to obtain error-free indices of each factor, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. Regression analyses revealed that latent scores for psychometric intelligence reliably predict latent scores for cognitive flexibility (adjusted R2 = 0.94). Lesion mapping results further indicated that these convergent processes depend on a shared network of frontal, temporal, and parietal regions, including white matter association tracts, which bind these areas into an integrated system. A targeted analysis of the unique variance explained by cognitive flexibility further revealed selective damage within the right superior temporal gyrus, a region known to support insight and the recognition of novel semantic relations. The observed findings motivate an integrative framework for understanding the neural foundations of adaptive behavior, suggesting that core elements of cognitive flexibility emerge from a distributed network of brain regions that support specific competencies for human intelligence. PMID:23721727

Adaptive Technologies for Training and Education

ERIC Educational Resources Information Center

Durlach, Paula J., Ed; Lesgold, Alan M., Ed.

2012-01-01

This edited volume provides an overview of the latest advancements in adaptive training technology. Intelligent tutoring has been deployed for well-defined and relatively static educational domains such as algebra and geometry. However, this adaptive approach to computer-based training has yet to come into wider usage for domains that are less…

Adaptive Profiles in Autism and Other Neurodevelopmental Disorders

ERIC Educational Resources Information Center

Mouga, Susana; Almeida, Joana; Café, Cátia; Duque, Frederico; Oliveira, Guiomar

2015-01-01

We investigated the influence of specific autism spectrum disorder (ASD) deficits in learning adaptive behaviour, besides intelligence quotient (IQ). Participated 217 school-aged: ASD (N = 115), and other neurodevelopmental disorders (OND) groups (N = 102) matched by Full-Scale IQ. We compared standard scores of Vineland Adaptive Behaviour Scale…

Application of Adaptive Decision Aiding Systems to Computer-Assisted Instruction. Final Report, January-December 1974.

ERIC Educational Resources Information Center

May, Donald M.; And Others

The minicomputer-based Computerized Diagnostic and Decision Training (CDDT) system described combines the principles of artificial intelligence, decision theory, and adaptive computer assisted instruction for training in electronic troubleshooting. The system incorporates an adaptive computer program which learns the student's diagnostic and…

Designing Adaptive Instruction for Teams: A Meta-Analysis

ERIC Educational Resources Information Center

Sottilare, Robert A.; Shawn Burke, C.; Salas, Eduardo; Sinatra, Anne M.; Johnston, Joan H.; Gilbert, Stephen B.

2018-01-01

The goal of this research was the development of a practical architecture for the computer-based tutoring of teams. This article examines the relationship of team behaviors as antecedents to successful team performance and learning during adaptive instruction guided by Intelligent Tutoring Systems (ITSs). Adaptive instruction is a training or…

Characterizing Speech Intelligibility in Noise After Wide Dynamic Range Compression.

PubMed

Rhebergen, Koenraad S; Maalderink, Thijs H; Dreschler, Wouter A

The effects of nonlinear signal processing on speech intelligibility in noise are difficult to evaluate. Often, the effects are examined by comparing speech intelligibility scores with and without processing measured at fixed signal to noise ratios (SNRs) or by comparing the adaptive measured speech reception thresholds corresponding to 50% intelligibility (SRT50) with and without processing. These outcome measures might not be optimal. Measuring at fixed SNRs can be affected by ceiling or floor effects, because the range of relevant SNRs is not know in advance. The SRT50 is less time consuming, has a fixed performance level (i.e., 50% correct), but the SRT50 could give a limited view, because we hypothesize that the effect of most nonlinear signal processing algorithms at the SRT50 cannot be generalized to other points of the psychometric function. In this article, we tested the value of estimating the entire psychometric function. We studied the effect of wide dynamic range compression (WDRC) on speech intelligibility in stationary, and interrupted speech-shaped noise in normal-hearing subjects, using a fast method-based local linear fitting approach and by two adaptive procedures. The measured performance differences for conditions with and without WDRC for the psychometric functions in stationary noise and interrupted speech-shaped noise show that the effects of WDRC on speech intelligibility are SNR dependent. We conclude that favorable and unfavorable effects of WDRC on speech intelligibility can be missed if the results are presented in terms of SRT50 values only.

Tera-OP Reliable Intelligently Adaptive Processing System (TRIPS) Implementation

DTIC Science & Technology

2008-09-01

38 6.8 Instruction Scheduling ...39 6.8.1 Spatial Path Scheduling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 6.8.2...oblivious scheduling for rapid application prototyping and deployment, environmental adaptivity for resilience in hostile environments, and dynamic

Who needs innate ability to succeed in math and literacy? Academic-domain-specific theories of intelligence about peers versus adults.

PubMed

Gunderson, Elizabeth A; Hamdan, Noora; Sorhagen, Nicole S; D'Esterre, Alexander P

2017-06-01

Individuals' implicit theories of intelligence exist on a spectrum, from believing intelligence is fixed and unchangeable, to believing it is malleable and can be improved with effort. A belief in malleable intelligence leads to adaptive responses to challenge and higher achievement. However, surprisingly little is known about the development of academic-domain-specific theories of intelligence (i.e., math vs. reading and writing). The authors examined this in a cross-section of students from 1st grade to college (N = 523). They also examined whether students hold different beliefs about the role of fixed ability in adult jobs versus their own grade. The authors' adult-specific beliefs hypothesis states that when children learn societally held beliefs from adults, they first apply these beliefs specifically to adults and later to students their own age. Consistent with this, even the youngest students (1st and 2nd graders) believed that success in an adult job requires more fixed ability in math than reading and writing. However, when asked about students in their own grade, only high school and college students reported that math involves more fixed ability than reading and writing. High school and college students' math-specific theories of intelligence were related to their motivation and achievement in math, controlling for reading and writing-specific theories. Reading and writing-specific theories did not predict reading and writing-specific motivations or achievement, perhaps because students perceive reading and writing as less challenging than math. In summary, academic-domain-specific theories of intelligence develop early but may not become self-relevant until adolescence, and math-specific beliefs may be especially important targets for intervention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

How Can Evolution Learn?

PubMed

Watson, Richard A; Szathmáry, Eörs

2016-02-01

The theory of evolution links random variation and selection to incremental adaptation. In a different intellectual domain, learning theory links incremental adaptation (e.g., from positive and/or negative reinforcement) to intelligent behaviour. Specifically, learning theory explains how incremental adaptation can acquire knowledge from past experience and use it to direct future behaviours toward favourable outcomes. Until recently such cognitive learning seemed irrelevant to the 'uninformed' process of evolution. In our opinion, however, new results formally linking evolutionary processes to the principles of learning might provide solutions to several evolutionary puzzles - the evolution of evolvability, the evolution of ecological organisation, and evolutionary transitions in individuality. If so, the ability for evolution to learn might explain how it produces such apparently intelligent designs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intelligent nonsingular terminal sliding-mode control using MIMO Elman neural network for piezo-flexural nanopositioning stage.

PubMed

Lin, Faa-Jeng; Lee, Shih-Yang; Chou, Po-Huan

2012-12-01

The objective of this study is to develop an intelligent nonsingular terminal sliding-mode control (INTSMC) system using an Elman neural network (ENN) for the threedimensional motion control of a piezo-flexural nanopositioning stage (PFNS). First, the dynamic model of the PFNS is derived in detail. Then, to achieve robust, accurate trajectory-tracking performance, a nonsingular terminal sliding-mode control (NTSMC) system is proposed for the tracking of the reference contours. The steady-state response of the control system can be improved effectively because of the addition of the nonsingularity in the NTSMC. Moreover, to relax the requirements of the bounds and discard the switching function in NTSMC, an INTSMC system using a multi-input-multioutput (MIMO) ENN estimator is proposed to improve the control performance and robustness of the PFNS. The ENN estimator is proposed to estimate the hysteresis phenomenon and lumped uncertainty, including the system parameters and external disturbance of the PFNS online. Furthermore, the adaptive learning algorithms for the training of the parameters of the ENN online are derived using the Lyapunov stability theorem. In addition, two robust compensators are proposed to confront the minimum reconstructed errors in INTSMC. Finally, some experimental results for the tracking of various contours are given to demonstrate the validity of the proposed INTSMC system for PFNS.

Multi-Armed Bandits for Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Clement, Benjamin; Roy, Didier; Oudeyer, Pierre-Yves; Lopes, Manuel

2015-01-01

We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by students, taking into account the limited time and motivational resources. At a given point in time, the system proposes to the students the activity which makes them progress faster. We introduce two…

Reasoning about Users' Actions in a Graphical User Interface.

ERIC Educational Resources Information Center

Virvou, Maria; Kabassi, Katerina

2002-01-01

Describes a graphical user interface called IFM (Intelligent File Manipulator) that provides intelligent help to users. Explains two underlying reasoning mechanisms, one an adaptation of human plausible reasoning and one that performs goal recognition based on the effects of users' commands; and presents results of an empirical study that…

Emotional Intelligence Abilities and Traits in Different Career Paths

ERIC Educational Resources Information Center

Kafetsios, Konstantinos; Maridaki-Kassotaki, Aikaterini; Zammuner, Vanda L.; Zampetakis, Leonidas A.; Vouzas, Fotios

2009-01-01

Two studies tested hypotheses about differences in emotional intelligence (EI) abilities and traits between followers of different career paths. Compared to their social science peers, science students had higher scores in adaptability and general mood traits measured with the Emotion Quotient Inventory, but lower scores in strategic EI abilities…

Rainbows of Intelligence. Exploring How Students Learn.

ERIC Educational Resources Information Center

Teele, Sue

This book offers practical applications for exploring multiple intelligences in the classroom to help each student express his or her own personal learning rainbow. Special features of the book include seven complete lesson plans ready to be adapted to any grade level; objectives, activities, and applications that meet U.S. and California…

Intelligent Adaptive Interface: A Design Tool for Enhancing Human-Machine System Performances

DTIC Science & Technology

2009-10-01

and customizable. Thus, an intelligent interface should tailor its parameters to certain prescribed specifications or convert itself and adjust to...Computer Interaction 3(2): 87-122. [51] Schereiber, G., Akkermans, H., Anjewierden, A., de Hoog , R., Shadbolt, N., Van de Velde, W., & Wielinga, W

How Can Intelligent CAL Better Adapt to Learners?

ERIC Educational Resources Information Center

Boyd, Gary McI.; Mitchell, P. David

1992-01-01

Discusses intelligent computer-aided learning (ICAL) support systems and considers learner characteristics as elements of ICAL student models. Cybernetic theory and attribute-treatment results are discussed, six components of a student model for tutoring are described, and methods for determining the student's model of the tutor are examined. (22…

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

Computational Intelligence in Web-Based Education: A Tutorial

ERIC Educational Resources Information Center

Vasilakos, Thanos; Devedzic, Vladan; Kinshuk; Pedrycz, Witold

2004-01-01

This article discusses some important aspects of Web Intelligence (WI) in the context of educational applications. Some of the key components of WI have already attracted developers of web-based educational systems for quite some time- ontologies, adaptivity and personalization, and agents. The paper focuses on the application of Computational…

Developing Emotion-Aware, Advanced Learning Technologies: A Taxonomy of Approaches and Features

ERIC Educational Resources Information Center

Harley, Jason M.; Lajoie, Susanne P.; Frasson, Claude; Hall, Nathan C.

2017-01-01

A growing body of work on intelligent tutoring systems, affective computing, and artificial intelligence in education is exploring creative, technology-driven approaches to enhance learners' experience of adaptive, positively-valenced emotions while interacting with advanced learning technologies. Despite this, there has been no published work to…

An Artificial Intelligence Tutor: A Supplementary Tool for Teaching and Practicing Braille

ERIC Educational Resources Information Center

McCarthy, Tessa; Rosenblum, L. Penny; Johnson, Benny G.; Dittel, Jeffrey; Kearns, Devin M.

2016-01-01

Introduction: This study evaluated the usability and effectiveness of an artificial intelligence Braille Tutor designed to supplement the instruction of students with visual impairments as they learned to write braille contractions. Methods: A mixed-methods design was used, which incorporated a single-subject, adapted alternating treatments design…

Modeling of biological intelligence for SCM system optimization.

PubMed

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms.

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

Chen, Shengyong; Zheng, Yujun; Cattani, Carlo; Wang, Wanliang

2012-01-01

This article summarizes some methods from biological intelligence for modeling and optimization of supply chain management (SCM) systems, including genetic algorithms, evolutionary programming, differential evolution, swarm intelligence, artificial immune, and other biological intelligence related methods. An SCM system is adaptive, dynamic, open self-organizing, which is maintained by flows of information, materials, goods, funds, and energy. Traditional methods for modeling and optimizing complex SCM systems require huge amounts of computing resources, and biological intelligence-based solutions can often provide valuable alternatives for efficiently solving problems. The paper summarizes the recent related methods for the design and optimization of SCM systems, which covers the most widely used genetic algorithms and other evolutionary algorithms. PMID:22162724

Conflict adaptation in positive and negative mood: Applying a success-failure manipulation.

PubMed

Schuch, Stefanie; Zweerings, Jana; Hirsch, Patricia; Koch, Iring

2017-05-01

Conflict adaptation is a cognitive mechanism denoting increased cognitive control upon detection of conflict. This mechanism can be measured by the congruency sequence effect, indicating the reduction of congruency effects after incongruent trials (where response conflict occurs) relative to congruent trials (without response conflict). Several studies have reported increased conflict adaptation under negative, as compared to positive, mood. In these studies, sustained mood states were induced by film clips or music combined with imagination techniques; these kinds of mood manipulations are highly obvious, possibly distorting the actual mood states experienced by the participants. Here, we report two experiments where mood states were induced in a less obvious way, and with higher ecological validity. Participants received success or failure feedback on their performance in a bogus intelligence test, and this mood manipulation proved highly effective. We largely replicated previous findings of larger conflict adaptation under negative mood than under positive mood, both with a Flanker interference paradigm (Experiment 1) and a Stroop-like interference paradigm (Experiment 2). Results are discussed with respect to current theories on affective influences on cognitive control. Copyright © 2017 Elsevier B.V. All rights reserved.

Human/autonomy collaboration for the automated generation of intelligence products

NASA Astrophysics Data System (ADS)

DiBona, Phil; Schlachter, Jason; Kuter, Ugur; Goldman, Robert

2017-05-01

Intelligence Analysis remains a manual process despite trends toward autonomy in information processing. Analysts need agile decision-­-support tools that can adapt to the evolving information needs of the mission, allowing the analyst to pose novel analytic questions. Our research enables the analysts to only provide a constrained English specification of what the intelligence product should be. Using HTN planning, the autonomy discovers, decides, and generates a workflow of algorithms to create the intelligence product. Therefore, the analyst can quickly and naturally communicate to the autonomy what information product is needed, rather than how to create it.

ERPs evidence for the relationship between fluid intelligence and cognitive control.

PubMed

Lu, Di; Zhang, Haoyun; Kang, Chunyan; Guo, Taomei

2016-04-13

The relationship between two components of cognitive control, that is, proactive control and reactive control, and fluid intelligence was investigated by measuring 75 participants' event-related potentials in the AX version of the continuous performance test. The results showed that the mean amplitudes of N2 associated with the two components of cognitive control are highly correlated with fluid intelligence. Specifically, a larger N2 was shown in participants with higher fluid intelligence scores. No significant correlation was found in the peak latencies of the N2 and fluid intelligence. These results enrich our understanding of the relationship between cognitive control and fluid intelligence by using the N2 component as an index and also indicate that cognitive control may be a component of intelligence.

Towards an intelligent wheelchair system for users with cerebral palsy.

PubMed

Montesano, Luis; Díaz, Marta; Bhaskar, Sonu; Minguez, Javier

2010-04-01

This paper describes and evaluates an intelligent wheelchair, adapted for users with cognitive disabilities and mobility impairment. The study focuses on patients with cerebral palsy, one of the most common disorders affecting muscle control and coordination, thereby impairing movement. The wheelchair concept is an assistive device that allows the user to select arbitrary local destinations through a tactile screen interface. The device incorporates an automatic navigation system that drives the vehicle, avoiding obstacles even in unknown and dynamic scenarios. It provides the user with a high degree of autonomy, independent from a particular environment, i.e., not restricted to predefined conditions. To evaluate the rehabilitation device, a study was carried out with four subjects with cognitive impairments, between 11 and 16 years of age. They were first trained so as to get acquainted with the tactile interface and then were recruited to drive the wheelchair. Based on the experience with the subjects, an extensive evaluation of the intelligent wheelchair was provided from two perspectives: 1) based on the technical performance of the entire system and its components and 2) based on the behavior of the user (execution analysis, activity analysis, and competence analysis). The results indicated that the intelligent wheelchair effectively provided mobility and autonomy to the target population.

Intelligent walkers for the elderly: performance and safety testing of VA-PAMAID robotic walker.

PubMed

Rentschler, Andrew J; Cooper, Rory A; Blasch, Bruce; Boninger, Michael L

2003-01-01

A walker that could help navigate and avoid collisions with obstacles could help reduce health costs and increase the quality of care and independence of thousands of people. This study evaluated the safety and performance of the Veterans Affairs Personal Adaptive Mobility Aid (VA-PAMAID). We performed engineering tests on the VA-PAMAID to determine safety factors, including stability, energy consumption, fatigue life, and sensor and control malfunctions. The VA-PAMAID traveled 10.9 km on a full charge and avoided obstacles while traveling at a speed of up to 1.2 m/s. No failures occurred during static stability, climatic, or fatigue testing. Some problems were encountered during obstacle climbing and sensor and control testing. The VA-PAMAID has good range, has adequate reaction time, and is structurally sound. Clinical trials are planned to compare the device to other low-technical adaptive mobility devices.

Vision-based algorithms for near-host object detection and multilane sensing

NASA Astrophysics Data System (ADS)

Kenue, Surender K.

1995-01-01

Vision-based sensing can be used for lane sensing, adaptive cruise control, collision warning, and driver performance monitoring functions of intelligent vehicles. Current computer vision algorithms are not robust for handling multiple vehicles in highway scenarios. Several new algorithms are proposed for multi-lane sensing, near-host object detection, vehicle cut-in situations, and specifying regions of interest for object tracking. These algorithms were tested successfully on more than 6000 images taken from real-highway scenes under different daytime lighting conditions.

A.I.-based real-time support for high performance aircraft operations

NASA Technical Reports Server (NTRS)

Vidal, J. J.

1985-01-01

Artificial intelligence (AI) based software and hardware concepts are applied to the handling system malfunctions during flight tests. A representation of malfunction procedure logic using Boolean normal forms are presented. The representation facilitates the automation of malfunction procedures and provides easy testing for the embedded rules. It also forms a potential basis for a parallel implementation in logic hardware. The extraction of logic control rules, from dynamic simulation and their adaptive revision after partial failure are examined. It uses a simplified 2-dimensional aircraft model with a controller that adaptively extracts control rules for directional thrust that satisfies a navigational goal without exceeding pre-established position and velocity limits. Failure recovery (rule adjusting) is examined after partial actuator failure. While this experiment was performed with primitive aircraft and mission models, it illustrates an important paradigm and provided complexity extrapolations for the proposed extraction of expertise from simulation, as discussed. The use of relaxation and inexact reasoning in expert systems was also investigated.

Is adaptation of the word accentuation test of premorbid intelligence necessary for use among older, Spanish-speaking immigrants in the United States?

PubMed

Schrauf, Robert W; Weintraub, Sandra; Navarro, Ellen

2006-05-01

Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages other than English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappings common in that language, and (b) subsequent validation against a cognitive battery normed on the population of interest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the Wechsler Adult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the Spanish Word Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against a cognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generation of 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The Batería Woodcock-Muñoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, was used to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-R and 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possesses adequate predictive validity as an indicator of intelligence. Regression equations are provided for estimating BWM-R and Ravens scores from WAT scores.

A Concept for Optimizing Behavioural Effectiveness & Efficiency

NASA Astrophysics Data System (ADS)

Barca, Jan Carlo; Rumantir, Grace; Li, Raymond

Both humans and machines exhibit strengths and weaknesses that can be enhanced by merging the two entities. This research aims to provide a broader understanding of how closer interactions between these two entities can facilitate more optimal goal-directed performance through the use of artificial extensions of the human body. Such extensions may assist us in adapting to and manipulating our environments in a more effective way than any system known today. To demonstrate this concept, we have developed a simulation where a semi interactive virtual spider can be navigated through an environment consisting of several obstacles and a virtual predator capable of killing the spider. The virtual spider can be navigated through the use of three different control systems that can be used to assist in optimising overall goal directed performance. The first two control systems use, an onscreen button interface and a touch sensor, respectively to facilitate human navigation of the spider. The third control system is an autonomous navigation system through the use of machine intelligence embedded in the spider. This system enables the spider to navigate and react to changes in its local environment. The results of this study indicate that machines should be allowed to override human control in order to maximise the benefits of collaboration between man and machine. This research further indicates that the development of strong machine intelligence, sensor systems that engage all human senses, extra sensory input systems, physical remote manipulators, multiple intelligent extensions of the human body, as well as a tighter symbiosis between man and machine, can support an upgrade of the human form.

Plant intelligence.

PubMed

Trewavas, Anthony

2005-09-01

Intelligent behavior is a complex adaptive phenomenon that has evolved to enable organisms to deal with variable environmental circumstances. Maximizing fitness requires skill in foraging for necessary resources (food) in competitive circumstances and is probably the activity in which intelligent behavior is most easily seen. Biologists suggest that intelligence encompasses the characteristics of detailed sensory perception, information processing, learning, memory, choice, optimisation of resource sequestration with minimal outlay, self-recognition, and foresight by predictive modeling. All these properties are concerned with a capacity for problem solving in recurrent and novel situations. Here I review the evidence that individual plant species exhibit all of these intelligent behavioral capabilities but do so through phenotypic plasticity, not movement. Furthermore it is in the competitive foraging for resources that most of these intelligent attributes have been detected. Plants should therefore be regarded as prototypical intelligent organisms, a concept that has considerable consequences for investigations of whole plant communication, computation and signal transduction.

Architecture of fluid intelligence and working memory revealed by lesion mapping.

PubMed

Barbey, Aron K; Colom, Roberto; Paul, Erick J; Grafman, Jordan

2014-03-01

Although cognitive neuroscience has made valuable progress in understanding the role of the prefrontal cortex in human intelligence, the functional networks that support adaptive behavior and novel problem solving remain to be well characterized. Here, we studied 158 human brain lesion patients to investigate the cognitive and neural foundations of key competencies for fluid intelligence and working memory. We administered a battery of neuropsychological tests, including the Wechsler Adult Intelligence Scale (WAIS) and the N-Back task. Latent variable modeling was applied to obtain error-free scores of fluid intelligence and working memory, followed by voxel-based lesion-symptom mapping to elucidate their neural substrates. The observed latent variable modeling and lesion results support an integrative framework for understanding the architecture of fluid intelligence and working memory and make specific recommendations for the interpretation and application of the WAIS and N-Back task to the study of fluid intelligence in health and disease.

Can enriching emotional intelligence improve medical students' proactivity and adaptability during OB/GYN clerkships?

PubMed

Guseh, Stephanie H; Chen, Xiaodong P; Johnson, Natasha R

2015-12-26

The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students' adaptability and proactivity on the Obstetrics and Gynecology clerkship. An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students' adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students' adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation.

Can enriching emotional intelligence improve medical students’ proactivity and adaptability during OB/GYN clerkships?

PubMed Central

Guseh, Stephanie H.; Chen, Xiaodong P.

2015-01-01

Objectives The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students’ adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. Results A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students’ adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Conclusions Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation. PMID:26708233

Prolonged Walking with a Wearable System Providing Intelligent Auditory Input in People with Parkinson's Disease.

PubMed

Ginis, Pieter; Heremans, Elke; Ferrari, Alberto; Dockx, Kim; Canning, Colleen G; Nieuwboer, Alice

2017-01-01

Rhythmic auditory cueing is a well-accepted tool for gait rehabilitation in Parkinson's disease (PD), which can now be applied in a performance-adapted fashion due to technological advance. This study investigated the immediate differences on gait during a prolonged, 30 min, walk with performance-adapted (intelligent) auditory cueing and verbal feedback provided by a wearable sensor-based system as alternatives for traditional cueing. Additionally, potential effects on self-perceived fatigue were assessed. Twenty-eight people with PD and 13 age-matched healthy elderly (HE) performed four 30 min walks with a wearable cue and feedback system. In randomized order, participants received: (1) continuous auditory cueing; (2) intelligent cueing (10 metronome beats triggered by a deviating walking rhythm); (3) intelligent feedback (verbal instructions triggered by a deviating walking rhythm); and (4) no external input. Fatigue was self-scored at rest and after walking during each session. The results showed that while HE were able to maintain cadence for 30 min during all conditions, cadence in PD significantly declined without input. With continuous cueing and intelligent feedback people with PD were able to maintain cadence ( p  = 0.04), although they were more physically fatigued than HE. Furthermore, cadence deviated significantly more in people with PD than in HE without input and particularly with intelligent feedback (both: p  = 0.04). In PD, continuous and intelligent cueing induced significantly less deviations of cadence ( p  = 0.006). Altogether, this suggests that intelligent cueing is a suitable alternative for the continuous mode during prolonged walking in PD, as it induced similar effects on gait without generating levels of fatigue beyond that of HE.

The Role of Intelligence in Social Learning.

PubMed

Vostroknutov, Alexander; Polonio, Luca; Coricelli, Giorgio

2018-05-02

Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.

An intelligent control system for rocket engines - Need, vision, and issues

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Merrill, Walter C.

1991-01-01

Several components of intelligence are defined. Within the context of these definitions an intelligent control system for rocket engines is described. The description includes a framework for development of an intelligent control system, including diagnostics, coordination, and direct control. Some current results and issues are presented.

Real-Time Smart Grids Control for Preventing Cascading Failures and Blackout using Neural Networks: Experimental Approach for N-1-1 Contingency

NASA Astrophysics Data System (ADS)

Zarrabian, Sina; Belkacemi, Rabie; Babalola, Adeniyi A.

2016-12-01

In this paper, a novel intelligent control is proposed based on Artificial Neural Networks (ANN) to mitigate cascading failure (CF) and prevent blackout in smart grid systems after N-1-1 contingency condition in real-time. The fundamental contribution of this research is to deploy the machine learning concept for preventing blackout at early stages of its occurrence and to make smart grids more resilient, reliable, and robust. The proposed method provides the best action selection strategy for adaptive adjustment of generators' output power through frequency control. This method is able to relieve congestion of transmission lines and prevent consecutive transmission line outage after N-1-1 contingency condition. The proposed ANN-based control approach is tested on an experimental 100 kW test system developed by the authors to test intelligent systems. Additionally, the proposed approach is validated on the large-scale IEEE 118-bus power system by simulation studies. Experimental results show that the ANN approach is very promising and provides accurate and robust control by preventing blackout. The technique is compared to a heuristic multi-agent system (MAS) approach based on communication interchanges. The ANN approach showed more accurate and robust response than the MAS algorithm.

Gender Differences in the Role of Emotional Intelligence during the Primary-Secondary School Transition

ERIC Educational Resources Information Center

Jordan, Julie-Ann; McRorie, Margaret; Ewing, Cathy

2010-01-01

The relationship between components of emotional intelligence (EI) (interpersonal ability, intrapersonal ability, adaptability and stress management) and academic performance in English, maths and science was examined in a sample of 86 children (49 males and 37 females) aged 11-12 years during the primary-secondary school transition period.…

Adapting Collaboration Dialogue in Response to Intelligent Tutoring System Feedback

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol

2015-01-01

To be able to provide better support for collaborative learning in Intelligent Tutoring Systems, it is important to understand how collaboration patterns change. Prior work has looked at the interdependencies between utterances and the change of dialogue over time, but it has not addressed how dialogue changes during a lesson, an analysis that…

A Conversational Intelligent Tutoring System to Automatically Predict Learning Styles

ERIC Educational Resources Information Center

Latham, Annabel; Crockett, Keeley; McLean, David; Edmonds, Bruce

2012-01-01

This paper proposes a generic methodology and architecture for developing a novel conversational intelligent tutoring system (CITS) called Oscar that leads a tutoring conversation and dynamically predicts and adapts to a student's learning style. Oscar aims to mimic a human tutor by implicitly modelling the learning style during tutoring, and…

Prospective EFL Teachers' Emotional Intelligence and Tablet Computer Use and Literacy

ERIC Educational Resources Information Center

Herguner, Sinem

2017-01-01

The aim of this study was to investigate whether there is a relationship between tablet computer use and literacy, and emotional intelligence of prospective English language teachers. The study used a survey approach. In the study, "Prospective Teachers Tablet Computer Use and Literacy Scale" and an adapted and translated version into…

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

NASA/ARC proposed training in intelligent control

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1990-01-01

Viewgraphs on NASA Ames Research Center proposed training in intelligent control was presented. Topics covered include: fuzzy logic control; neural networks in control; artificial intelligence in control; hybrid approaches; hands on experience; and fuzzy controllers.

Intelligent controller of novel design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou Qi Jian; Bai Jian Kuo

1983-01-01

This paper presents the authors attempt to combine the control engineering principle with human intelligence to form a new control algorithm. The hybrid system thus formed is both analogous and logical in actions and is called the intelligent controller (IC). With the help of cybernetics princple, the operator's intelligent action of control is programmed into the controller and the system is thus taught to act like an intelligent being within the prescribed range. Remarkable results were obtained from experiments conducted on an electronic model simulating the above mentioned system. Stability studies and system analysis are presented. 12 references.

Role of Language-Related Functional Connectivity in Patients with Benign Childhood Epilepsy with Centrotemporal Spikes

PubMed Central

Kim, Hyeon Jin; Lee, Jung Hwa; Park, Chang-hyun; Hong, Hye-Sun; Choi, Yun Seo; Yoo, Jeong Hyun

2018-01-01

Background and Purpose Benign childhood epilepsy with centrotemporal spikes (BECTS) does not always have a benign cognitive outcome. We investigated the relationship between cognitive performance and altered functional connectivity (FC) in the resting-state brain networks of BECTS patients. Methods We studied 42 subjects, comprising 19 BECTS patients and 23 healthy controls. Cognitive performance was assessed using the Korean version of the Wechsler Intelligence Scale for Children-III, in addition to verbal and visuospatial memory tests and executive function tests. Resting-state functional magnetic resonance imaging was acquired in addition to high-resolution structural data. We selected Rolandic and language-related areas as regions of interest (ROIs) and analyzed the seed-based FC to voxels throughout the brain. We evaluated the correlations between the neuropsychological test scores and seed-based FC values using the same ROIs. Results The verbal intelligence quotient (VIQ) and full-scale intelligence quotient (FSIQ) were lower in BECTS patients than in healthy controls (p<0.001). The prevalence of subjects with a higher performance IQ than VIQ was significantly higher in BECTS patients than in healthy controls (73.7% vs. 26.1%, respectively; p=0.002). Both the Rolandic and language-related ROIs exhibited more enhanced FC to voxels in the left inferior temporal gyrus in BECTS patients than in healthy controls. A particularly interestingly finding was that the enhanced FC was correlated with lower cognitive performance as measured by the VIQ and the FSIQ in both patients and control subjects. Conclusions Our findings suggest that the FC alterations in resting-state brain networks related to the seizure onset zone and language processing areas could be related to adaptive plasticity for coping with cognitive dysfunction. PMID:29629540

Intelligence.

PubMed

Sternberg, Robert J

2012-03-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

Intelligence

PubMed Central

Sternberg, Robert J.

2012-01-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

The Effect of Timing and Frequency of Push Notifications on Usage of a Smartphone-Based Stress Management Intervention: An Exploratory Trial.

PubMed

Morrison, Leanne G; Hargood, Charlie; Pejovic, Veljko; Geraghty, Adam W A; Lloyd, Scott; Goodman, Natalie; Michaelides, Danius T; Weston, Anna; Musolesi, Mirco; Weal, Mark J; Yardley, Lucy

2017-01-01

Push notifications offer a promising strategy for enhancing engagement with smartphone-based health interventions. Intelligent sensor-driven machine learning models may improve the timeliness of notifications by adapting delivery to a user's current context (e.g. location). This exploratory mixed-methods study examined the potential impact of timing and frequency on notification response and usage of Healthy Mind, a smartphone-based stress management intervention. 77 participants were randomised to use one of three versions of Healthy Mind that provided: intelligent notifications; daily notifications within pre-defined time frames; or occasional notifications within pre-defined time frames. Notification response and Healthy Mind usage were automatically recorded. Telephone interviews explored participants' experiences of using Healthy Mind. Participants in the intelligent and daily conditions viewed (d = .47, .44 respectively) and actioned (d = .50, .43 respectively) more notifications compared to the occasional group. Notification group had no meaningful effects on percentage of notifications viewed or usage of Healthy Mind. No meaningful differences were indicated between the intelligent and non-intelligent groups. Our findings suggest that frequent notifications may encourage greater exposure to intervention content without deterring engagement, but adaptive tailoring of notification timing does not always enhance their use. Hypotheses generated from this study require testing in future work. ISRCTN67177737.

A comparative study of artificial intelligent-based maximum power point tracking for photovoltaic systems

NASA Astrophysics Data System (ADS)

Hussain Mutlag, Ammar; Mohamed, Azah; Shareef, Hussain

2016-03-01

Maximum power point tracking (MPPT) is normally required to improve the performance of photovoltaic (PV) systems. This paper presents artificial intelligent-based maximum power point tracking (AI-MPPT) by considering three artificial intelligent techniques, namely, artificial neural network (ANN), adaptive neuro fuzzy inference system with seven triangular fuzzy sets (7-tri), and adaptive neuro fuzzy inference system with seven gbell fuzzy sets. The AI-MPPT is designed for the 25 SolarTIFSTF-120P6 PV panels, with the capacity of 3 kW peak. A complete PV system is modelled using 300,000 data samples and simulated in the MATLAB/SIMULINK. The AI-MPPT has been tested under real environmental conditions for two days from 8 am to 18 pm. The results showed that the ANN based MPPT gives the most accurate performance and then followed by the 7-tri-based MPPT.

Adaptive Systems in Education: A Review and Conceptual Unification

ERIC Educational Resources Information Center

Wilson, Chunyu; Scott, Bernard

2017-01-01

Purpose: The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader. Design/methodology/approach: A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and…

Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Looi, Chee-Kit

2012-01-01

The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

Using Adaptive Learning Technologies to Personalize Instruction to Student Interests: The Impact of Relevant Contexts on Performance and Learning Outcomes

ERIC Educational Resources Information Center

Walkington, Candace A.

2013-01-01

Adaptive learning technologies are emerging in educational settings as a means to customize instruction to learners' background, experiences, and prior knowledge. Here, a technology-based personalization intervention within an intelligent tutoring system (ITS) for secondary mathematics was used to adapt instruction to students' personal interests.…

The Neural Mechanism Exploration of Adaptive Motor Control: Dynamical Economic Cell Allocation in the Primary Motor Cortex.

PubMed

Li, Wei; Guo, Yangyang; Fan, Jing; Ma, Chaolin; Ma, Xuan; Chen, Xi; He, Jiping

2017-05-01

Adaptive flexibility is of significance for the smooth and efficient movements in goal attainment. However, the underlying work mechanism of the cerebral cortex in adaptive motor control still remains unclear. How does the cerebral cortex organize and coordinate the activity of a large population of cells in the implementation of various motor strategies? To explore this issue, single-unit activities from the M1 region and kinematic data were recorded simultaneously in monkeys performing 3D reach-to-grasp tasks with different perturbations. Varying motor control strategies were employed and achieved in different perturbed tasks, via the dynamic allocation of cells to modulate specific movement parameters. An economic principle was proposed for the first time to describe a basic rule for cell allocation in the primary motor cortex. This principle, defined as the Dynamic Economic Cell Allocation Mechanism (DECAM), guarantees benefit maximization in cell allocation under limited neuronal resources, and avoids committing resources to uneconomic investments for unreliable factors with no or little revenue. That is to say, the cells recruited are always preferentially allocated to those factors with reliable return; otherwise, the cells are dispatched to respond to other factors about task. The findings of this study might partially reveal the working mechanisms underlying the role of the cerebral cortex in adaptive motor control, wherein is also of significance for the design of future intelligent brain-machine interfaces and rehabilitation device.

Use of artificial intelligence in the production of high quality minced meat

NASA Astrophysics Data System (ADS)

Kapovsky, B. R.; Pchelkina, V. A.; Plyasheshnik, P. I.; Dydykin, A. S.; Lazarev, A. A.

2017-09-01

A design for an automatic line for minced meat production according to new production technology based on an innovative meat milling method is proposed. This method allows the necessary degree of raw material comminution at the stage of raw material preparation to be obtained, which leads to production intensification due to the traditional meat mass comminution equipment being unnecessary. To ensure consistent quality of the product obtained, the use of on-line automatic control of the technological process for minced meat production is envisaged. This system has been developed using artificial intelligence methods and technologies. The system is trainable during the operation process, adapts to changes in processed raw material characteristics and to external impacts that affect the system operation, and manufactures meat shavings with minimal dispersion of the typical particle size. The control system includes equipment for express analysis of the chemical composition of the minced meat and its temperature after comminution. In this case, the minced meat production process can be controlled strictly as a function of time, which excludes subjective factors for assessing the degree of finished product readiness. This will allow finished meat products with consistent, targeted high quality to be produced.

Laser rangefinders for autonomous intelligent cruise control systems

NASA Astrophysics Data System (ADS)

Journet, Bernard A.; Bazin, Gaelle

1998-01-01

THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.

Systems and WBANs for Controlling Obesity

PubMed Central

Mohammed, Maali Said; Sendra, Sandra

2018-01-01

According to World Health Organization (WHO) estimations, one out of five adults worldwide will be obese by 2025. Worldwide obesity has doubled since 1980. In fact, more than 1.9 billion adults (39%) of 18 years and older were overweight and over 600 million (13%) of these were obese in 2014. 42 million children under the age of five were overweight or obese in 2014. Obesity is a top public health problem due to its associated morbidity and mortality. This paper reviews the main techniques to measure the level of obesity and body fat percentage, and explains the complications that can carry to the individual's quality of life, longevity and the significant cost of healthcare systems. Researchers and developers are adapting the existing technology, as intelligent phones or some wearable gadgets to be used for controlling obesity. They include the promoting of healthy eating culture and adopting the physical activity lifestyle. The paper also shows a comprehensive study of the most used mobile applications and Wireless Body Area Networks focused on controlling the obesity and overweight. Finally, this paper proposes an intelligent architecture that takes into account both, physiological and cognitive aspects to reduce the degree of obesity and overweight. PMID:29599941

Systems and WBANs for Controlling Obesity.

PubMed

Mohammed, Maali Said; Sendra, Sandra; Lloret, Jaime; Bosch, Ignacio

2018-01-01

According to World Health Organization (WHO) estimations, one out of five adults worldwide will be obese by 2025. Worldwide obesity has doubled since 1980. In fact, more than 1.9 billion adults (39%) of 18 years and older were overweight and over 600 million (13%) of these were obese in 2014. 42 million children under the age of five were overweight or obese in 2014. Obesity is a top public health problem due to its associated morbidity and mortality. This paper reviews the main techniques to measure the level of obesity and body fat percentage, and explains the complications that can carry to the individual's quality of life, longevity and the significant cost of healthcare systems. Researchers and developers are adapting the existing technology, as intelligent phones or some wearable gadgets to be used for controlling obesity. They include the promoting of healthy eating culture and adopting the physical activity lifestyle. The paper also shows a comprehensive study of the most used mobile applications and Wireless Body Area Networks focused on controlling the obesity and overweight. Finally, this paper proposes an intelligent architecture that takes into account both, physiological and cognitive aspects to reduce the degree of obesity and overweight.

Hyperspectral Image-Based Night-Time Vehicle Light Detection Using Spectral Normalization and Distance Mapper for Intelligent Headlight Control

PubMed Central

Kim, Heekang; Kwon, Soon; Kim, Sungho

2016-01-01

This paper proposes a vehicle light detection method using a hyperspectral camera instead of a Charge-Coupled Device (CCD) or Complementary metal-Oxide-Semiconductor (CMOS) camera for adaptive car headlamp control. To apply Intelligent Headlight Control (IHC), the vehicle headlights need to be detected. Headlights are comprised from a variety of lighting sources, such as Light Emitting Diodes (LEDs), High-intensity discharge (HID), and halogen lamps. In addition, rear lamps are made of LED and halogen lamp. This paper refers to the recent research in IHC. Some problems exist in the detection of headlights, such as erroneous detection of street lights or sign lights and the reflection plate of ego-car from CCD or CMOS images. To solve these problems, this study uses hyperspectral images because they have hundreds of bands and provide more information than a CCD or CMOS camera. Recent methods to detect headlights used the Spectral Angle Mapper (SAM), Spectral Correlation Mapper (SCM), and Euclidean Distance Mapper (EDM). The experimental results highlight the feasibility of the proposed method in three types of lights (LED, HID, and halogen). PMID:27399720

Field Guide for Designing Human Interaction with Intelligent Systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Thronesbery, Carroll G.

1998-01-01

The characteristics of this Field Guide approach address the problems of designing innovative software to support user tasks. The requirements for novel software are difficult to specify a priori, because there is not sufficient understanding of how the users' tasks should be supported, and there are not obvious pre-existing design solutions. When the design team is in unfamiliar territory, care must be taken to avoid rushing into detailed design, requirements specification, or implementation of the wrong product. The challenge is to get the right design and requirements in an efficient, cost-effective manner. This document's purpose is to describe the methods we are using to design human interactions with intelligent systems which support Space Shuttle flight controllers in the Mission Control Center at NASA/Johnson Space Center. Although these software systems usually have some intelligent features, the design challenges arise primarily from the innovation needed in the software design. While these methods are tailored to our specific context, they should be extensible, and helpful to designers of human interaction with other types of automated systems. We review the unique features of this context so that you can determine how to apply these methods to your project Throughout this Field Guide, goals of the design methods are discussed. This should help designers understand how a specific method might need to be adapted to the project at hand.

An overview on STEP-NC compliant controller development

NASA Astrophysics Data System (ADS)

Othman, M. A.; Minhat, M.; Jamaludin, Z.

2017-10-01

The capabilities of conventional Computer Numerical Control (CNC) machine tools as termination organiser to fabricate high-quality parts promptly, economically and precisely are undeniable. To date, most CNCs follow the programming standard of ISO 6983, also called G & M code. However, in fluctuating shop floor environment, flexibility and interoperability of current CNC system to react dynamically and adaptively are believed still limited. This outdated programming language does not explicitly relate to each other to have control of arbitrary locations other than the motion of the block-by-block. To address this limitation, new standard known as STEP-NC was developed in late 1990s and is formalized as an ISO 14649. It adds intelligence to the CNC in term of interoperability, flexibility, adaptability and openness. This paper presents an overview of the research work that have been done in developing a STEP-NC controller standard and the capabilities of STEP-NC to overcome modern manufacturing demands. Reviews stated that most existing STEP-NC controller prototypes are based on type 1 and type 2 implementation levels. There are still lack of effort being done to develop type 3 and type 4 STEP-NC compliant controller.

Academic and emotional functioning in middle school: the role of implicit theories.

PubMed

Romero, Carissa; Master, Allison; Paunesku, Dave; Dweck, Carol S; Gross, James J

2014-04-01

Adolescents face many academic and emotional challenges in middle school, but notable differences are evident in how well they adapt. What predicts adolescents' academic and emotional outcomes during this period? One important factor might be adolescents' implicit theories about whether intelligence and emotions can change. The current study examines how these theories affect academic and emotional outcomes. One hundred fifteen students completed surveys throughout middle school, and their grades and course selections were obtained from school records. Students who believed that intelligence could be developed earned higher grades and were more likely to move to advanced math courses over time. Students who believed that emotions could be controlled reported fewer depressive symptoms and, if they began middle school with lower well-being, were more likely to feel better over time. These findings illustrate the power of adolescents' implicit theories, suggesting exciting new pathways for intervention.

Complete diagnostics of pyroactive structures for smart systems of optoelectronics

NASA Astrophysics Data System (ADS)

Bravina, Svetlana L.; Morozovsky, Nicholas V.

1998-04-01

The results of study of pyroelectric phenomena in ferroelectric materials for evidence of the possibility to embody the functions promising for creation of smart systems for optoelectronic applications are presented. Designing such systems requires the development of methods for non- destructive complete diagnostics preferably by developing the self-diagnostic ability inherent in materials with the features of smart/intelligent ones. The complex method of complete non-destructive qualification of pyroactive materials based on the method of dynamic photopyroelectric effect allows the determination of pyroelectric, piezoelectric, ferroelectric, dielectric and thermophysical characteristics. The measuring system which allows the study of these characteristics and also memory effects, switching effects, fatigue and degradation process, self-repair process and others is presented. Sample pyroactive system with increased intelligence, such as systems with built-in adaptive controllable domain structure promising for functional optics are developed and peculiarities of their characterization are discussed.

Analyzing User Interaction to Design an Intelligent e-Learning Environment

ERIC Educational Resources Information Center

Sharma, Richa

2011-01-01

Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…

Cross-Cultural Adaptation of the Intelligibility in Context Scale for South Africa

ERIC Educational Resources Information Center

Pascoe, Michelle; McLeod, Sharynne

2016-01-01

The Intelligibility in Context Scale (ICS) is a screening questionnaire that focuses on parents' perceptions of children's speech in different contexts. Originally developed in English, it has been translated into 60 languages and the validity and clinical utility of the scale has been documented in a range of countries. In South Africa, there are…

Modeling Expert Behavior in Support of an Adaptive Psychomotor Training Environment: A Marksmanship Use Case

ERIC Educational Resources Information Center

Goldberg, Benjamin; Amburn, Charles; Ragusa, Charlie; Chen, Dar-Wei

2018-01-01

The U.S. Army is interested in extending the application of intelligent tutoring systems (ITS) beyond cognitive problem spaces and into psychomotor skill domains. In this paper, we present a methodology and validation procedure for creating expert model representations in the domain of rifle marksmanship. GIFT (Generalized Intelligent Framework…

Identification and real-time position control of a servo-hydraulic rotary actuator by means of a neurobiologically motivated algorithm.

PubMed

Sadeghieh, Ali; Sazgar, Hadi; Goodarzi, Kamyar; Lucas, Caro

2012-01-01

This paper presents a new intelligent approach for adaptive control of a nonlinear dynamic system. A modified version of the brain emotional learning based intelligent controller (BELBIC), a bio-inspired algorithm based upon a computational model of emotional learning which occurs in the amygdala, is utilized for position controlling a real laboratorial rotary electro-hydraulic servo (EHS) system. EHS systems are known to be nonlinear and non-smooth due to many factors such as leakage, friction, hysteresis, null shift, saturation, dead zone, and especially fluid flow expression through the servo valve. The large value of these factors can easily influence the control performance in the presence of a poor design. In this paper, a mathematical model of the EHS system is derived, and then the parameters of the model are identified using the recursive least squares method. In the next step, a BELBIC is designed based on this dynamic model and utilized to control the real laboratorial EHS system. To prove the effectiveness of the modified BELBIC's online learning ability in reducing the overall tracking error, results have been compared to those obtained from an optimal PID controller, an auto-tuned fuzzy PI controller (ATFPIC), and a neural network predictive controller (NNPC) under similar circumstances. The results demonstrate not only excellent improvement in control action, but also less energy consumption. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

Toward a new task assignment and path evolution (TAPE) for missile defense system (MDS) using intelligent adaptive SOM with recurrent neural networks (RNNs).

PubMed

Wang, Chi-Hsu; Chen, Chun-Yao; Hung, Kun-Neng

2015-06-01

In this paper, a new adaptive self-organizing map (SOM) with recurrent neural network (RNN) controller is proposed for task assignment and path evolution of missile defense system (MDS). We address the problem of N agents (defending missiles) and D targets (incoming missiles) in MDS. A new RNN controller is designed to force an agent (or defending missile) toward a target (or incoming missile), and a monitoring controller is also designed to reduce the error between RNN controller and ideal controller. A new SOM with RNN controller is then designed to dispatch agents to their corresponding targets by minimizing total damaging cost. This is actually an important application of the multiagent system. The SOM with RNN controller is the main controller. After task assignment, the weighting factors of our new SOM with RNN controller are activated to dispatch the agents toward their corresponding targets. Using the Lyapunov constraints, the weighting factors for the proposed SOM with RNN controller are updated to guarantee the stability of the path evolution (or planning) system. Excellent simulations are obtained using this new approach for MDS, which show that our RNN has the lowest average miss distance among the several techniques.

Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

NASA Technical Reports Server (NTRS)

Williams-Hayes, Peggy S.

2004-01-01

The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

Comparing Binaural Pre-processing Strategies II

PubMed Central

Hu, Hongmei; Krawczyk-Becker, Martin; Marquardt, Daniel; Herzke, Tobias; Coleman, Graham; Adiloğlu, Kamil; Bomke, Katrin; Plotz, Karsten; Gerkmann, Timo; Doclo, Simon; Kollmeier, Birger; Hohmann, Volker; Dietz, Mathias

2015-01-01

Several binaural audio signal enhancement algorithms were evaluated with respect to their potential to improve speech intelligibility in noise for users of bilateral cochlear implants (CIs). 50% speech reception thresholds (SRT50) were assessed using an adaptive procedure in three distinct, realistic noise scenarios. All scenarios were highly nonstationary, complex, and included a significant amount of reverberation. Other aspects, such as the perfectly frontal target position, were idealized laboratory settings, allowing the algorithms to perform better than in corresponding real-world conditions. Eight bilaterally implanted CI users, wearing devices from three manufacturers, participated in the study. In all noise conditions, a substantial improvement in SRT50 compared to the unprocessed signal was observed for most of the algorithms tested, with the largest improvements generally provided by binaural minimum variance distortionless response (MVDR) beamforming algorithms. The largest overall improvement in speech intelligibility was achieved by an adaptive binaural MVDR in a spatially separated, single competing talker noise scenario. A no-pre-processing condition and adaptive differential microphones without a binaural link served as the two baseline conditions. SRT50 improvements provided by the binaural MVDR beamformers surpassed the performance of the adaptive differential microphones in most cases. Speech intelligibility improvements predicted by instrumental measures were shown to account for some but not all aspects of the perceptually obtained SRT50 improvements measured in bilaterally implanted CI users. PMID:26721921

An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

NASA Astrophysics Data System (ADS)

Karizi, Nasim

An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.'s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition.

PubMed

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-03-27

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K -nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction.

Power quality control of an autonomous wind-diesel power system based on hybrid intelligent controller.

PubMed

Ko, Hee-Sang; Lee, Kwang Y; Kang, Min-Jae; Kim, Ho-Chan

2008-12-01

Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a cost-effective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

NASA Glenn Research in Controls and Diagnostics for Intelligent Aerospace Propulsion Systems

NASA Technical Reports Server (NTRS)

Garg, Sanjay

2007-01-01

With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Branch (CDB) at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of Intelligent Propulsion Systems. This presentation describes the current CDB activities in support of the NASA Aeronautics Research Mission, with an emphasis on activities under the Integrated Vehicle Health Management (IVHM) and Integrated Resilient Aircraft Control (IRAC) projects of the Aviation Safety Program. Under IVHM, CDB focus is on developing advanced techniques for monitoring the health of the aircraft engine gas path with a focus on reliable and early detection of sensor, actuator and engine component faults. Under IRAC, CDB focus is on developing adaptive engine control technologies which will increase the probability of survival of aircraft in the presence of damage to flight control surfaces or to one or more engines. The technology development plans are described as well as results from recent research accomplishments.

Design of modular control system for grain dryers

NASA Astrophysics Data System (ADS)

He, Gaoqing; Liu, Yanhua; Zu, Yuan

In order to effectively control the temperature of grain drying bin, grain ,air outlet as well as the grain moisture, it designed the control system of 5HCY-35 which is based on MCU to adapt to all grains drying conditions, high drying efficiency, long life usage and less manually. The system includes: the control module of the constant temperature and the temperature difference control in drying bin, the constant temperature control of heating furnace, on-line testing of moisture, variety of grain-circulation speed control and human-computer interaction interface. Spatial curve simulation, which takes moisture as control objectives, controls the constant temperature and the temperature difference in drying bin according to preset parameter by the user or a list to reduce the grains explosive to ensure the seed germination percentage. The system can realize the intelligent control of high efficiency and various drying, the good scalability and the high quality.

Designing a spoken dialogue interface to an intelligent cognitive assistant for people with dementia.

PubMed

Wolters, Maria Klara; Kelly, Fiona; Kilgour, Jonathan

2016-12-01

Intelligent cognitive assistants support people who need help performing everyday tasks by detecting when problems occur and providing tailored and context-sensitive assistance. Spoken dialogue interfaces allow users to interact with intelligent cognitive assistants while focusing on the task at hand. In order to establish requirements for voice interfaces to intelligent cognitive assistants, we conducted three focus groups with people with dementia, carers, and older people without a diagnosis of dementia. Analysis of the focus group data showed that voice and interaction style should be chosen based on the preferences of the user, not those of the carer. For people with dementia, the intelligent cognitive assistant should act like a patient, encouraging guide, while for older people without dementia, assistance should be to the point and not patronising. The intelligent cognitive assistant should be able to adapt to cognitive decline. © The Author(s) 2015.

Intelligent Vehicle Health Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Michael D.

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of INM. These real-time responses allow the IIVM to modify the affected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the INM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project and the integration of these technologies forms the framework for IIVM.

Smart Electrochemical Energy Storage Devices with Self-Protection and Self-Adaptation Abilities.

PubMed

Yang, Yun; Yu, Dandan; Wang, Hua; Guo, Lin

2017-12-01

Currently, with booming development and worldwide usage of rechargeable electrochemical energy storage devices, their safety issues, operation stability, service life, and user experience are garnering special attention. Smart and intelligent energy storage devices with self-protection and self-adaptation abilities aiming to address these challenges are being developed with great urgency. In this Progress Report, we highlight recent achievements in the field of smart energy storage systems that could early-detect incoming internal short circuits and self-protect against thermal runaway. Moreover, intelligent devices that are able to take actions and self-adapt in response to external mechanical disruption or deformation, i.e., exhibiting self-healing or shape-memory behaviors, are discussed. Finally, insights into the future development of smart rechargeable energy storage devices are provided. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lavia – an Evaluation of the Potential Safety Benefits of the French Intelligent Speed Adaptation Project

PubMed Central

Driscoll, R.; Page, Y.; Lassarre, S.; Ehrlich, J.

2007-01-01

This paper presents the potential safety benefits of the experimental French LAVIA Intelligent Speed Adaptation system, according to road network and system mode, based on observed driving speeds, distributions of crash severity and crash injury risk. Results are given for car frontal and side impacts that together, represent 80% of all serious and fatal injuries in France. Of the three system modes tested (advisory, driver select, mandatory), our results suggest that driver select would most significantly reduce serious injuries and death. We estimate this 100% utilization of cars equipped with this type of speed adaptation system would decrease injury rates by 6% to 16% over existing conditions depending on the type of crash (frontal or side) and road environment considered. Some limitations associated with the analysis are also identified. PMID:18184509

The Gap between Adaptive Behavior and Intelligence in Autism Persists into Young Adulthood and is Linked to Psychiatric Co-Morbidities

ERIC Educational Resources Information Center

Kraper, Catherine K.; Kenworthy, Lauren; Popal, Haroon; Martin, Alex; Wallace, Gregory L.

2017-01-01

For individuals with autism spectrum disorder (ASD), long-term outcomes have been troubling, and intact IQ has not been shown to be protective. Nevertheless, relatively little research into adaptive functioning among adults with ASD has been completed to date. Therefore, both adaptive functioning and comorbid psychopathology were assessed among 52…

Individualized Special Education with Cognitive Skill Assessment.

ERIC Educational Resources Information Center

Kurhila, Jaakko; Laine, Tei

2000-01-01

Describes AHMED (Adaptive and Assistive Hypermedia in Education), a computer learning environment which supports the evaluation of disabled children's cognitive skills in addition to supporting openness in learning materials and adaptivity in learning events. Discusses cognitive modeling and compares it to previous intelligent tutoring systems.…

Termination Criteria for Computerized Classification Testing

ERIC Educational Resources Information Center

Thompson, Nathan A.

2011-01-01

Computerized classification testing (CCT) is an approach to designing tests with intelligent algorithms, similar to adaptive testing, but specifically designed for the purpose of classifying examinees into categories such as "pass" and "fail." Like adaptive testing for point estimation of ability, the key component is the…

A phone-assistive device based on Bluetooth technology for cochlear implant users.

PubMed

Qian, Haifeng; Loizou, Philipos C; Dorman, Michael F

2003-09-01

Hearing-impaired people, and particularly hearing-aid and cochlear-implant users, often have difficulty communicating over the telephone. The intelligibility of telephone speech is considerably lower than the intelligibility of face-to-face speech. This is partly because of lack of visual cues, limited telephone bandwidth, and background noise. In addition, cellphones may cause interference with the hearing aid or cochlear implant. To address these problems that hearing-impaired people experience with telephones, this paper proposes a wireless phone adapter that can be used to route the audio signal directly to the hearing aid or cochlear implant processor. This adapter is based on Bluetooth technology. The favorable features of this new wireless technology make the adapter superior to traditional assistive listening devices. A hardware prototype was built and software programs were written to implement the headset profile in the Bluetooth specification. Three cochlear implant users were tested with the proposed phone-adapter and reported good speech quality.

Intelligence with representation.

PubMed

Steels, Luc

2003-10-15

Behaviour-based robotics has always been inspired by earlier cybernetics work such as that of W. Grey Walter. It emphasizes that intelligence can be achieved without the kinds of representations common in symbolic AI systems. The paper argues that such representations might indeed not be needed for many aspects of sensory-motor intelligence but become a crucial issue when bootstrapping to higher levels of cognition. It proposes a scenario in the form of evolutionary language games by which embodied agents develop situated grounded representations adapted to their needs and the conventions emerging in the population.

Top-down causation and emergence: some comments on mechanisms

PubMed Central

Ellis, George F. R.

2012-01-01

Both bottom-up and top-down causation occur in the hierarchy of structure and causation. A key feature is multiple realizability of higher level functions, and consequent existence of equivalence classes of lower level variables that correspond to the same higher level state. Five essentially different classes of top-down influence can be identified, and their existence demonstrated by many real-world examples. They are: algorithmic top-down causation; top-down causation via non-adaptive information control, top-down causation via adaptive selection, top-down causation via adaptive information control and intelligent top-down causation (the effect of the human mind on the physical world). Through the mind, abstract entities such as mathematical structures have causal power. The causal slack enabling top-down action to take place lies in the structuring of the system so as to attain higher level functions; in the way the nature of lower level elements is changed by context, and in micro-indeterminism combined with adaptive selection. Understanding top-down causation can have important effects on society. Two cases will be mentioned: medical/healthcare issues, and education—in particular, teaching reading and writing. In both cases, an ongoing battle between bottom-up and top-down approaches has important consequences for society. PMID:23386967

An adaptive signal-processing approach to online adaptive tutoring.

PubMed

Bergeron, Bryan; Cline, Andrew

2011-01-01

Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need for the construction of explicit expert and student models. A key advantage of our method over conventional approaches is a lower barrier to entry for educators who want to develop adaptive online learning materials.

Smart Prosthetic Hand Technology - Phase 2

DTIC Science & Technology

2011-05-01

identification and estimation, hand motion estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The...Smart Prosthetics, Bio- Robotics , Intelligent EMG Signal Processing, Embedded Systems and Intelligent Control, Inflammatory Responses of Cells, Toxicity...estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The developed identification algorithm using a new

Fault tolerant and lifetime control architecture for autonomous vehicles

NASA Astrophysics Data System (ADS)

Bogdanov, Alexander; Chen, Yi-Liang; Sundareswaran, Venkataraman; Altshuler, Thomas

2008-04-01

Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.

An efficient representation of spatial information for expert reasoning in robotic vehicles

NASA Technical Reports Server (NTRS)

Scott, Steven; Interrante, Mark

1987-01-01

The previous generation of robotic vehicles and drones was designed for a specific task, with limited flexibility in executing their mission. This limited flexibility arises because the robotic vehicles do not possess the intelligence and knowledge upon which to make significant tactical decisions. Current development of robotic vehicles is toward increased intelligence and capabilities, adapting to a changing environment and altering mission objectives. The latest techniques in artificial intelligence (AI) are being employed to increase the robotic vehicle's intelligent decision-making capabilities. This document describes the design of the SARA spatial database tool, which is composed of request parser, reasoning, computations, and database modules that collectively manage and derive information useful for robotic vehicles.

A design philosophy for multi-layer neural networks with applications to robot control

NASA Technical Reports Server (NTRS)

Vadiee, Nader; Jamshidi, MO

1989-01-01

A system is proposed which receives input information from many sensors that may have diverse scaling, dimension, and data representations. The proposed system tolerates sensory information with faults. The proposed self-adaptive processing technique has great promise in integrating the techniques of artificial intelligence and neural networks in an attempt to build a more intelligent computing environment. The proposed architecture can provide a detailed decision tree based on the input information, information stored in a long-term memory, and the adapted rule-based knowledge. A mathematical model for analysis will be obtained to validate the cited hypotheses. An extensive software program will be developed to simulate a typical example of pattern recognition problem. It is shown that the proposed model displays attention, expectation, spatio-temporal, and predictory behavior which are specific to the human brain. The anticipated results of this research project are: (1) creation of a new dynamic neural network structure, and (2) applications to and comparison with conventional multi-layer neural network structures. The anticipated benefits from this research are vast. The model can be used in a neuro-computer architecture as a building block which can perform complicated, nonlinear, time-varying mapping from a multitude of input excitory classes to an output or decision environment. It can be used for coordinating different sensory inputs and past experience of a dynamic system and actuating signals. The commercial applications of this project can be the creation of a special-purpose neuro-computer hardware which can be used in spatio-temporal pattern recognitions in such areas as air defense systems, e.g., target tracking, and recognition. Potential robotics-related applications are trajectory planning, inverse dynamics computations, hierarchical control, task-oriented control, and collision avoidance.

Intelligent correction of laser beam propagation through turbulent media using adaptive optics

NASA Astrophysics Data System (ADS)

Ko, Jonathan; Wu, Chensheng; Davis, Christopher C.

2014-10-01

Adaptive optics methods have long been used by researchers in the astronomy field to retrieve correct images of celestial bodies. The approach is to use a deformable mirror combined with Shack-Hartmann sensors to correct the slightly distorted image when it propagates through the earth's atmospheric boundary layer, which can be viewed as adding relatively weak distortion in the last stage of propagation. However, the same strategy can't be easily applied to correct images propagating along a horizontal deep turbulence path. In fact, when turbulence levels becomes very strong (Cn 2>10-13 m-2/3), limited improvements have been made in correcting the heavily distorted images. We propose a method that reconstructs the light field that reaches the camera, which then provides information for controlling a deformable mirror. An intelligent algorithm is applied that provides significant improvement in correcting images. In our work, the light field reconstruction has been achieved with a newly designed modified plenoptic camera. As a result, by actively intervening with the coherent illumination beam, or by giving it various specific pre-distortions, a better (less turbulence affected) image can be obtained. This strategy can also be expanded to much more general applications such as correcting laser propagation through random media and can also help to improve designs in free space optical communication systems.

4-D COMMON OPERATIONAL PICTURE (COP) FOR MISSION ASSURANCE (4D COP) Task Order 0001: Air Force Research Laboratory (AFRL) Autonomy Collaboration in Intelligence, Surveillance, and Reconnaissance (ISR), Electronic Warfare (EW)/Cyber and Combat Identification (CID)

DTIC Science & Technology

2016-10-27

Domain C2, Adaptive Domain Control, Global Integrated ISR, Rapid Global Mobility , and Global Precision Strike, orgnanized within a framework of...mission needs. (Among the dozen implications) A more transparent, networked infrastructure that integrates ubiquitous sensors, automated systems...Conclusion 5.1 Common Technical Trajectory One of the most significant opportunities for AFRL is to develop and mobilize the qualitative roadmap

IEEE 1982. Proceedings of the international conference on cybernetics and society

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1982-01-01

The following topics were dealt with: knowledge-based systems; risk analysis; man-machine interactions; human information processing; metaphor, analogy and problem-solving; manual control modelling; transportation systems; simulation; adaptive and learning systems; biocybernetics; cybernetics; mathematical programming; robotics; decision support systems; analysis, design and validation of models; computer vision; systems science; energy systems; environmental modelling and policy; pattern recognition; nuclear warfare; technological forecasting; artificial intelligence; the Turin shroud; optimisation; workloads. Abstracts of individual papers can be found under the relevant classification codes in this or future issues.

A Framework for Integration of IVHM Technologies for Intelligent Integration for Vehicle Management

NASA Technical Reports Server (NTRS)

Paris, Deidre E.; Trevino, Luis; Watson, Mike

2005-01-01

As a part of the overall goal of developing Integrated Vehicle Health Management (IVHM) systems for aerospace vehicles, the NASA Faculty Fellowship Program (NFFP) at Marshall Space Flight Center has performed a pilot study on IVHM principals which integrates researched IVHM technologies in support of Integrated Intelligent Vehicle Management (IIVM). IVHM is the process of assessing, preserving, and restoring system functionality across flight and ground systems (NASA NGLT 2004). The framework presented in this paper integrates advanced computational techniques with sensor and communication technologies for spacecraft that can generate responses through detection, diagnosis, reasoning, and adapt to system faults in support of IIVM. These real-time responses allow the IIVM to modify the effected vehicle subsystem(s) prior to a catastrophic event. Furthermore, the objective of this pilot program is to develop and integrate technologies which can provide a continuous, intelligent, and adaptive health state of a vehicle and use this information to improve safety and reduce costs of operations. Recent investments in avionics, health management, and controls have been directed towards IIVM. As this concept has matured, it has become clear the IIVM requires the same sensors and processing capabilities as the real-time avionics functions to support diagnosis of subsystem problems. New sensors have been proposed, in addition, to augment the avionics sensors to support better system monitoring and diagnostics. As the designs have been considered, a synergy has been realized where the real-time avionics can utilize sensors proposed for diagnostics and prognostics to make better real-time decisions in response to detected failures. IIVM provides for a single system allowing modularity of functions and hardware across the vehicle. The framework that supports IIVM consists of 11 major on-board functions necessary to fully manage a space vehicle maintaining crew safety and mission objectives: Guidance and Navigation; Communications and Tracking; Vehicle Monitoring; Information Transport and Integration; Vehicle Diagnostics; Vehicle Prognostics; Vehicle mission Planning; Automated Repair and Replacement; Vehicle Control; Human Computer Interface; and Onboard Verification and Validation. Furthermore, the presented framework provides complete vehicle management which not only allows for increased crew safety and mission success through new intelligence capabilities, but also yields a mechanism for more efficient vehicle operations. The representative IVHM technologies for IIVH includes: 1) robust controllers for use in re-usable launch vehicles, 2) scaleable/flexible computer platform using heterogeneous communication, 3) coupled electromagnetic oscillators for enhanced communications, 4) Linux-based real-time systems, 5) genetic algorithms, 6) Bayesian Networks, 7) evolutionary algorithms, 8) dynamic systems control modeling, and 9) advanced sensing capabilities. This paper presents IVHM technologies developed under NASA's NFFP pilot project. The integration of these IVHM technologies forms the framework for IIVM.

The Role of Emotional Intelligence in the Decision to Persist with Academic Studies in HE

ERIC Educational Resources Information Center

Qualter, Pamela; Whiteley, Helen; Morley, Andy; Dudiak, Helen

2009-01-01

Failure to adapt to the demands of higher education (HE) is often cited as a cause of withdrawal from the course. Parker and others (Parker, J.D.A., L.J. Summerfeldt, M.J. Hogan, and S.A. Majeski. 2004. "Emotional intelligence and academic success: Examining the transition from high school to university." "Personality and Individual…

The Intelligent e-Therapy System: A New Paradigm for Telepsychology and Cybertherapy

ERIC Educational Resources Information Center

Alcaniz, M.; Botella, C.; Banos, R. M.; Zaragoza, I.; Guixeres, J.

2009-01-01

One of the main drawbacks of computer-assisted psychology tools developed up to now is related to the real time customisation and adaptation of the content to each patient depending on his/her activity. In this paper we propose a new approach for mental e-health treatments named Intelligent e-Therapy (eIT) with capabilities for ambient…

Understanding the Gap between Cognitive Abilities and Daily Living Skills in Adolescents with Autism Spectrum Disorders with Average Intelligence

ERIC Educational Resources Information Center

Duncan, Amie W.; Bishop, Somer L.

2015-01-01

Daily living skills standard scores on the Vineland Adaptive Behavior Scales-2nd edition were examined in 417 adolescents from the Simons Simplex Collection. All participants had at least average intelligence and a diagnosis of autism spectrum disorder. Descriptive statistics and binary logistic regressions were used to examine the prevalence and…

The Influence of Emotional Intelligence (EI) on Coping and Mental Health in Adolescence: Divergent Roles for Trait and Ability EI

ERIC Educational Resources Information Center

Davis, Sarah K.; Humphrey, Neil

2012-01-01

Theoretically, trait and ability emotional intelligence (EI) should mobilise coping processes to promote adaptation, plausibly operating as personal resources determining choice and/or implementation of coping style. However, there is a dearth of research deconstructing if/how EI impacts mental health via multiple coping strategies in adolescence.…

Ambient agents: embedded agents for remote control and monitoring using the PANGEA platform.

PubMed

Villarrubia, Gabriel; De Paz, Juan F; Bajo, Javier; Corchado, Juan M

2014-07-31

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation.

Ambient Agents: Embedded Agents for Remote Control and Monitoring Using the PANGEA Platform

PubMed Central

Villarrubia, Gabriel; De Paz, Juan F.; Bajo, Javier; Corchado, Juan M.

2014-01-01

Ambient intelligence has advanced significantly during the last few years. The incorporation of image processing and artificial intelligence techniques have opened the possibility for such aspects as pattern recognition, thus allowing for a better adaptation of these systems. This study presents a new model of an embedded agent especially designed to be implemented in sensing devices with resource constraints. This new model of an agent is integrated within the PANGEA (Platform for the Automatic Construction of Organiztions of Intelligent Agents) platform, an organizational-based platform, defining a new sensor role in the system and aimed at providing contextual information and interacting with the environment. A case study was developed over the PANGEA platform and designed using different agents and sensors responsible for providing user support at home in the event of incidents or emergencies. The system presented in the case study incorporates agents in Arduino hardware devices with recognition modules and illuminated bands; it also incorporates IP cameras programmed for automatic tracking, which can connect remotely in the event of emergencies. The user wears a bracelet, which contains a simple vibration sensor that can receive notifications about the emergency situation. PMID:25090416

Primary nocturnal enuresis is associated with lower intelligence quotient scores in boys from poorer socioeconomic status families.

PubMed

Basiri, Abbas; Bahrainian, Seyed Abdolmajid; Khoshdel, Alireza; Jalaly, Niloofar; Golshan, Shabnam; Pakmanesh, Hamid

2017-03-01

To explore intelligence quotient in boys with primary nocturnal enuresis compared with normal boys considering their socioeconomic status. A total of 152 school-aged boys (including 55 boys with primary nocturnal enuresis and 97 matched normal controls) were assessed. Boys with a history of any neurological or urological disease were excluded. Two different districts of Tehran: Khani-Abad (a poor district) and Pirouzi (a middle class district) districts were enrolled according to socioeconomic status data reported by the World Health Organization. Intelligence tests were carried out using a validated Iranian translation of the Wechsler Intelligence Scale for Children Revised. Total, as well as performance intelligence quotient and verbal intelligence quotient scores and verbal-performance discrepancy (the difference between verbal and performance intelligence quotient scores for each individual) were compared using a t-test between boys with primary nocturnal enuresis in each district and their matched controls. Considering each district separately, the total intelligence quotient score was lower in primary nocturnal enuresis cases than controls only in the lower income district (90.7 ± 23.3 vs 104.8 ± 14.7, P = 0.002). Similarly, boys with primary nocturnal enuresis ranked lower in verbal intelligence quotient (P = 0.002) and performance intelligence quotient (P = 0.004) compared with their matched normal controls only in lower income district, whereas in the higher income district, boys with primary nocturnal enuresis ranked similar in total intelligence quotient to their matched controls. Boys with primary nocturnal enuresis had a lower intelligence quotient compared with the control participants only in low-income district. It seems important to adjust the results of the intelligence quotient assessment in these children according to their socioeconomic status. © 2017 The Japanese Urological Association.

The Effect of Timing and Frequency of Push Notifications on Usage of a Smartphone-Based Stress Management Intervention: An Exploratory Trial

PubMed Central

Hargood, Charlie; Pejovic, Veljko; Geraghty, Adam W. A.; Lloyd, Scott; Goodman, Natalie; Michaelides, Danius T.; Weston, Anna; Musolesi, Mirco; Weal, Mark J.; Yardley, Lucy

2017-01-01

Push notifications offer a promising strategy for enhancing engagement with smartphone-based health interventions. Intelligent sensor-driven machine learning models may improve the timeliness of notifications by adapting delivery to a user’s current context (e.g. location). This exploratory mixed-methods study examined the potential impact of timing and frequency on notification response and usage of Healthy Mind, a smartphone-based stress management intervention. 77 participants were randomised to use one of three versions of Healthy Mind that provided: intelligent notifications; daily notifications within pre-defined time frames; or occasional notifications within pre-defined time frames. Notification response and Healthy Mind usage were automatically recorded. Telephone interviews explored participants’ experiences of using Healthy Mind. Participants in the intelligent and daily conditions viewed (d = .47, .44 respectively) and actioned (d = .50, .43 respectively) more notifications compared to the occasional group. Notification group had no meaningful effects on percentage of notifications viewed or usage of Healthy Mind. No meaningful differences were indicated between the intelligent and non-intelligent groups. Our findings suggest that frequent notifications may encourage greater exposure to intervention content without deterring engagement, but adaptive tailoring of notification timing does not always enhance their use. Hypotheses generated from this study require testing in future work. Trial registration number: ISRCTN67177737 PMID:28046034

The influence of active vision on the exoskeleton of intelligent agents

NASA Astrophysics Data System (ADS)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

The role of intelligence and feedback in children's strategy competence.

PubMed

Luwel, Koen; Foustana, Ageliki; Papadatos, Yiannis; Verschaffel, Lieven

2011-01-01

A test-intervention-test study was conducted investigating the role of intelligence on four parameters of strategy competence in the context of a numerosity judgment task. Moreover, the effectiveness of two feedback types on these four parameters was tested. In the two test sessions, the choice/no-choice method was used to assess the strategy repertoire, frequency, efficiency, and adaptivity of a group of low-, average-, and high-intelligence children. During the intervention, half of the participants from each intelligence group were given outcome feedback (OFB), whereas the other half received strategy feedback (SFB). The pretest data showed large differences among the three intelligence groups on all four strategy parameters. These differences had disappeared at the posttest due to a particularly strong improvement on all strategy parameters in the low-intelligence group. Furthermore, it was found that SFB was more beneficial than OFB for all parameters involving strategy selection. These results indicate that intelligence plays an important role in children's strategy use and suggest that strategy feedback can be a powerful instructional tool, especially for low-intelligence children. Copyright © 2010 Elsevier Inc. All rights reserved.

Performance benefits of adaptive, multimicrophone, interference-canceling systems in everyday environments

NASA Astrophysics Data System (ADS)

Desloge, Joseph G.; Zimmer, Martin J.; Zurek, Patrick M.

2004-05-01

Adaptive multimicrophone systems are currently used for a variety of noise-cancellation applications (such as hearing aids) to preserve signals arriving from a particular (target) direction while canceling other (jammer) signals in the environment. Although the performance of these systems is known to degrade with increasing reverberation, there are few measurements of adaptive performance in everyday reverberant environments. In this study, adaptive performance was compared to that of a simple, nonadaptive cardioid microphone to determine a measure of adaptive benefit. Both systems used recordings (at an Fs of 22050 Hz) from the same two omnidirectional microphones, which were separated by 1 cm. Four classes of environment were considered: outdoors, household, parking garage, and public establishment. Sources were either environmental noises (e.g., household appliances, restaurant noise) or a controlled noise source. In all situations, no target was present (i.e., all signals were jammers) to obtain maximal jammer cancellation. Adaptive processing was based upon the Griffiths-Jim generalized sidelobe canceller using filter lengths up to 400 points. Average intelligibility-weighted adaptive benefit levels at a source distance of 1 m were, at most, 1.5 dB for public establishments, 2 dB for household rooms and the parking garage, and 3 dB outdoors. [Work supported by NIOSH.

Appearing smart: the impression management of intelligence, person perception accuracy, and behavior in social interaction.

PubMed

Murphy, Nora A

2007-03-01

Intelligence is an important trait that affects everyday social interaction. The present research utilized the ecological perspective of social perception to investigate the impression management of intelligence and strangers' evaluations of targets' intelligence levels. The ability to effectively portray an impression of intelligence to outside judges as well as interaction partners was appraised and the effect of impression management on the accurate judgment of intelligence was assessed. In addition, targets' behavior was studied in relation to impression management, perceived intelligence, and actual measured intelligence. Impression-managing targets appeared more intelligent to video judges but not to their interaction partner as compared to controls. The intelligence quotient (IQ) of impression-managing targets was more accurately judged than controls' IQ. Impression-managing targets displayed distinct nonverbal behavioral patterns that differed from controls. Looking while speaking was a key behavior: It significantly correlated with IQ, was successfully manipulated by impression-managing targets, and contributed to higher perceived intelligence ratings.

Adaptation of Chain Event Graphs for use with Case-Control Studies in Epidemiology.

PubMed

Keeble, Claire; Thwaites, Peter Adam; Barber, Stuart; Law, Graham Richard; Baxter, Paul David

2017-09-26

Case-control studies are used in epidemiology to try to uncover the causes of diseases, but are a retrospective study design known to suffer from non-participation and recall bias, which may explain their decreased popularity in recent years. Traditional analyses report usually only the odds ratio for given exposures and the binary disease status. Chain event graphs are a graphical representation of a statistical model derived from event trees which have been developed in artificial intelligence and statistics, and only recently introduced to the epidemiology literature. They are a modern Bayesian technique which enable prior knowledge to be incorporated into the data analysis using the agglomerative hierarchical clustering algorithm, used to form a suitable chain event graph. Additionally, they can account for missing data and be used to explore missingness mechanisms. Here we adapt the chain event graph framework to suit scenarios often encountered in case-control studies, to strengthen this study design which is time and financially efficient. We demonstrate eight adaptations to the graphs, which consist of two suitable for full case-control study analysis, four which can be used in interim analyses to explore biases, and two which aim to improve the ease and accuracy of analyses. The adaptations are illustrated with complete, reproducible, fully-interpreted examples, including the event tree and chain event graph. Chain event graphs are used here for the first time to summarise non-participation, data collection techniques, data reliability, and disease severity in case-control studies. We demonstrate how these features of a case-control study can be incorporated into the analysis to provide further insight, which can help to identify potential biases and lead to more accurate study results.

Automated Intelligent Training with a Tactical Decision Making Serious Game

DTIC Science & Technology

2014-01-01

tactical skills, but only if experiential events are accompanied with guided feedback. Practice alone is not sufficient for learning; it must be...micro-adaptation occurs within events (Shute, 1993). Micro-adaptation is a major component of InGEAR’s pedagogical strategy, with feedback tailored

Adolescent Depression: Relationships of Self-Report to Intellectual and Adaptive Functioning.

ERIC Educational Resources Information Center

Manikam, Ramasamy; And Others

1995-01-01

Self-report measures of depression, general psychopathology, and social skills were administered to 100 adolescents ranging from moderate mental retardation to above normal intelligence. Adolescents with mental retardation reported more depression and general psychopathology symptoms. Adaptive behavior functioned as a moderator variable, mediating…

Intelligent Signal Processing for Active Control

DTIC Science & Technology

1992-06-17

FUNDING NUMSI Intelligent Signal Processing for Active Control C-NO001489-J-1633 G. AUTHOR(S) P.A. Ramamoorthy 7. P2RFORMING ORGANIZATION NAME(S) AND...unclassified .unclassified unclassified L . I mu-. W UNIVERSITY OF CINCINNATI COLLEGE OF ENGINEERING Intelligent Signal Processing For Rctiue Control...NAURI RESEARCH Conkact No: NO1489-J-1633 P.L: P.A.imoodh Intelligent Signal Processing For Active Control 1 Executive Summary The thrust of this

The implementation of intelligent home controller

NASA Astrophysics Data System (ADS)

Li, Biqing; Li, Zhao

2018-04-01

This paper mainly talks about the working way of smart home terminal controller and the design of hardware and software. Controlling the lights and by simulating the lamp and the test of the curtain, destroy the light of lamp ON-OFF and the curtain's UP-DOWN by simulating the lamp and the test of the cuetain. Through the sensor collects the ambient information and sends to the network, such as light, temperature and humidity. Besides, it can realise the control of intelligent home control by PCS. Terminal controller of intelligent home which is based on ZiBee technology has into the intelligent home system, it provides people with convenient, safe and intelligent household experience.

An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

DOT National Transportation Integrated Search

1996-01-01

An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

Psychological Gender and Emotional Intelligence in Youth Female Soccer Players.

PubMed

Rutkowska, Katarzyna; Bergier, Józef

2015-09-29

Many sports (for instance soccer) are stereotypically perceived as a male activity. Even so, more and more women decide to become competitive athletes. Since the theory of sport requires comprehensive explanations and the practice of sport needs clear guidelines, interdisciplinary studies into the nature of sport, including its psychological aspects, are necessary. Analysing the psychological profile of female soccer players, particularly those who are about to become professional athletes, can provide many interesting insights into the specific character of female youth sport and show where improvements can be made in athletic training programmes (especially in mental training). It is therefore important to study psychological gender that determines social behaviours and to analyse female athletes' emotional intelligence. Emotional intelligence is defined as a set of emotional competencies that determine the effectiveness of human behaviours. Psychological gender and emotional intelligence have a significant effect on human adaptability and the efficiency of psychosocial functioning. This research was undertaken with the dual purpose of identifying the psychological gender and emotional intelligence of female soccer players. It involved 54 secondary-school girls, some of whom attended a sports class and others played on the Polish national team. The following tools were used to carry out the research: the Gender Assessment Inventory (IPP [This and the other acronyms derive from the Polish language]-developed by Kuczyńska) and the Emotional Intelligence Questionnaire (INTE; created by Jaworowska and Matczak). As shown by the analysis of the results, most female soccer players in the study were androgynous and the level of their emotional intelligence was significantly higher than in other participants. This also seems to point to their significantly greater adaptability. At the same time, the level of emotional intelligence in many players was average or low, which seems insufficient and calls for adequate intervention measures to be taken.

Psychological Gender and Emotional Intelligence in Youth Female Soccer Players

PubMed Central

Rutkowska, Katarzyna; Bergier, Józef

2015-01-01

Many sports (for instance soccer) are stereotypically perceived as a male activity. Even so, more and more women decide to become competitive athletes. Since the theory of sport requires comprehensive explanations and the practice of sport needs clear guidelines, interdisciplinary studies into the nature of sport, including its psychological aspects, are necessary. Analysing the psychological profile of female soccer players, particularly those who are about to become professional athletes, can provide many interesting insights into the specific character of female youth sport and show where improvements can be made in athletic training programmes (especially in mental training). It is therefore important to study psychological gender that determines social behaviours and to analyse female athletes’ emotional intelligence. Emotional intelligence is defined as a set of emotional competencies that determine the effectiveness of human behaviours. Psychological gender and emotional intelligence have a significant effect on human adaptability and the efficiency of psychosocial functioning. This research was undertaken with the dual purpose of identifying the psychological gender and emotional intelligence of female soccer players. It involved 54 secondary-school girls, some of whom attended a sports class and others played on the Polish national team. The following tools were used to carry out the research: the Gender Assessment Inventory (IPP [This and the other acronyms derive from the Polish language]-developed by Kuczyńska) and the Emotional Intelligence Questionnaire (INTE; created by Jaworowska and Matczak). As shown by the analysis of the results, most female soccer players in the study were androgynous and the level of their emotional intelligence was significantly higher than in other participants. This also seems to point to their significantly greater adaptability. At the same time, the level of emotional intelligence in many players was average or low, which seems insufficient and calls for adequate intervention measures to be taken. PMID:26673062

Research on intelligent machine self-perception method based on LSTM

NASA Astrophysics Data System (ADS)

Wang, Qiang; Cheng, Tao

2018-05-01

In this paper, we use the advantages of LSTM in feature extraction and processing high-dimensional and complex nonlinear data, and apply it to the autonomous perception of intelligent machines. Compared with the traditional multi-layer neural network, this model has memory, can handle time series information of any length. Since the multi-physical domain signals of processing machines have a certain timing relationship, and there is a contextual relationship between states and states, using this deep learning method to realize the self-perception of intelligent processing machines has strong versatility and adaptability. The experiment results show that the method proposed in this paper can obviously improve the sensing accuracy under various working conditions of the intelligent machine, and also shows that the algorithm can well support the intelligent processing machine to realize self-perception.

Adaptive Behaviors in High-Functioning Taiwanese Children with Autism Spectrum Disorders: An Investigation of the Mediating Roles of Symptom Severity and Cognitive Ability

ERIC Educational Resources Information Center

Chang, Chen-Lin; Lung, For-Wey; Yen, Cheng-Fang; Yang, Pinchen

2013-01-01

We investigated the relationship among cognitive level, autistic severity and adaptive function in a Taiwanese sample of 94 high-functioning children with autism spectrum disorders (ASD) (mean full scale intelligent quotients FSIQ = 84.8). Parents and teachers both completed the Adaptive Behavior Assessment System-II and the Social Responsiveness…

Embodying a cognitive model in a mobile robot

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Lonsdale, Deryle

2006-10-01

The ADAPT project is a collaboration of researchers in robotics, linguistics and artificial intelligence at three universities to create a cognitive architecture specifically designed to be embodied in a mobile robot. There are major respects in which existing cognitive architectures are inadequate for robot cognition. In particular, they lack support for true concurrency and for active perception. ADAPT addresses these deficiencies by modeling the world as a network of concurrent schemas, and modeling perception as problem solving. Schemas are represented using the RS (Robot Schemas) language, and are activated by spreading activation. RS provides a powerful language for distributed control of concurrent processes. Also, The formal semantics of RS provides the basis for the semantics of ADAPT's use of natural language. We have implemented the RS language in Soar, a mature cognitive architecture originally developed at CMU and used at a number of universities and companies. Soar's subgoaling and learning capabilities enable ADAPT to manage the complexity of its environment and to learn new schemas from experience. We describe the issues faced in developing an embodied cognitive architecture, and our implementation choices.

A Step Towards Developing Adaptive Robot-Mediated Intervention Architecture (ARIA) for Children With Autism

PubMed Central

Bekele, Esubalew T; Lahiri, Uttama; Swanson, Amy R.; Crittendon, Julie A.; Warren, Zachary E.; Sarkar, Nilanjan

2013-01-01

Emerging technology, especially robotic technology, has been shown to be appealing to children with autism spectrum disorders (ASD). Such interest may be leveraged to provide repeatable, accurate and individualized intervention services to young children with ASD based on quantitative metrics. However, existing robot-mediated systems tend to have limited adaptive capability that may impact individualization. Our current work seeks to bridge this gap by developing an adaptive and individualized robot-mediated technology for children with ASD. The system is composed of a humanoid robot with its vision augmented by a network of cameras for real-time head tracking using a distributed architecture. Based on the cues from the child’s head movement, the robot intelligently adapts itself in an individualized manner to generate prompts and reinforcements with potential to promote skills in the ASD core deficit area of early social orienting. The system was validated for feasibility, accuracy, and performance. Results from a pilot usability study involving six children with ASD and a control group of six typically developing (TD) children are presented. PMID:23221831

Learning and tuning fuzzy logic controllers through reinforcements.

PubMed

Berenji, H R; Khedkar, P

1992-01-01

A method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. It is shown that: the generalized approximate-reasoning-based intelligent control (GARIC) architecture learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

Light Robots: Bridging the Gap between Microrobotics and Photomechanics in Soft Materials.

PubMed

Zeng, Hao; Wasylczyk, Piotr; Wiersma, Diederik S; Priimagi, Arri

2018-06-01

For decades, roboticists have focused their efforts on rigid systems that enable programmable, automated action, and sophisticated control with maximal movement precision and speed. Meanwhile, material scientists have sought compounds and fabrication strategies to devise polymeric actuators that are small, soft, adaptive, and stimuli-responsive. Merging these two fields has given birth to a new class of devices-soft microrobots that, by combining concepts from microrobotics and stimuli-responsive materials research, provide several advantages in a miniature form: external, remotely controllable power supply, adaptive motion, and human-friendly interaction, with device design and action often inspired by biological systems. Herein, recent progress in soft microrobotics is highlighted based on light-responsive liquid-crystal elastomers and polymer networks, focusing on photomobile devices such as walkers, swimmers, and mechanical oscillators, which may ultimately lead to flying microrobots. Finally, self-regulated actuation is proposed as a new pathway toward fully autonomous, intelligent light robots of the future. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

NASA Astrophysics Data System (ADS)

El-Zoghby, Helmy M.; Bendary, Ahmed F.

2016-10-01

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Multichannel spatial auditory display for speech communications

NASA Technical Reports Server (NTRS)

Begault, D. R.; Erbe, T.; Wenzel, E. M. (Principal Investigator)

1994-01-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

Multi-channel spatial auditory display for speech communications

NASA Astrophysics Data System (ADS)

Begault, Durand; Erbe, Tom

1993-10-01

A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Multichannel spatial auditory display for speech communications.

PubMed

Begault, D R; Erbe, T

1994-10-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degrees azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degrees azimuth positions.

Multichannel Spatial Auditory Display for Speed Communications

NASA Technical Reports Server (NTRS)

Begault, Durand R.; Erbe, Tom

1994-01-01

A spatial auditory display for multiple speech communications was developed at NASA/Ames Research Center. Input is spatialized by the use of simplifiedhead-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four-letter call signs used by launch personnel at NASA against diotic speech babble. Spatial positions at 30 degree azimuth increments were evaluated. The results from eight subjects showed a maximum intelligibility improvement of about 6-7 dB when the signal was spatialized to 60 or 90 degree azimuth positions.

Wearable real-time and adaptive feedback device to face the stuttering: a knowledge-based telehealthcare proposal.

PubMed

Prado, Manuel; Roa, Laura M

2007-01-01

Despite first written references to permanent developmental stuttering occurred more than 2500 years ago, the mechanisms underlying this disorder are still unknown. This paper briefly reviews stuttering causal hypothesis and treatments, and presents the requirements that a new stuttering therapeutic device should verify. As a result of the analysis, an adaptive altered auditory feedback device based on a multimodal intelligent monitor, within the framework of a knowledge-based telehealthcare system, is presented. The subsequent discussion, based partly on the successful outcomes of a similar intelligent monitor, suggests that this novel device is feasible and could help to fill the gap between research and clinic.

Multi-channel spatial auditory display for speech communications

NASA Technical Reports Server (NTRS)

Begault, Durand; Erbe, Tom

1993-01-01

A spatial auditory display for multiple speech communications was developed at NASA-Ames Research Center. Input is spatialized by use of simplified head-related transfer functions, adapted for FIR filtering on Motorola 56001 digital signal processors. Hardware and firmware design implementations are overviewed for the initial prototype developed for NASA-Kennedy Space Center. An adaptive staircase method was used to determine intelligibility levels of four letter call signs used by launch personnel at NASA, against diotic speech babble. Spatial positions at 30 deg azimuth increments were evaluated. The results from eight subjects showed a maximal intelligibility improvement of about 6 to 7 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Approaches to optimal aquifer management and intelligent control in a multiresolutional decision support system

NASA Astrophysics Data System (ADS)

Orr, Shlomo; Meystel, Alexander M.

2005-03-01

Despite remarkable new developments in stochastic hydrology and adaptations of advanced methods from operations research, stochastic control, and artificial intelligence, solutions of complex real-world problems in hydrogeology have been quite limited. The main reason is the ultimate reliance on first-principle models that lead to complex, distributed-parameter partial differential equations (PDE) on a given scale. While the addition of uncertainty, and hence, stochasticity or randomness has increased insight and highlighted important relationships between uncertainty, reliability, risk, and their effect on the cost function, it has also (a) introduced additional complexity that results in prohibitive computer power even for just a single uncertain/random parameter; and (b) led to the recognition in our inability to assess the full uncertainty even when including all uncertain parameters. A paradigm shift is introduced: an adaptation of new methods of intelligent control that will relax the dependency on rigid, computer-intensive, stochastic PDE, and will shift the emphasis to a goal-oriented, flexible, adaptive, multiresolutional decision support system (MRDS) with strong unsupervised learning (oriented towards anticipation rather than prediction) and highly efficient optimization capability, which could provide the needed solutions of real-world aquifer management problems. The article highlights the links between past developments and future optimization/planning/control of hydrogeologic systems. Malgré de remarquables nouveaux développements en hydrologie stochastique ainsi que de remarquables adaptations de méthodes avancées pour les opérations de recherche, le contrôle stochastique, et l'intelligence artificielle, solutions pour les problèmes complexes en hydrogéologie sont restées assez limitées. La principale raison est l'ultime confiance en les modèles qui conduisent à des équations partielles complexes aux paramètres distribués (PDE) à une échelle donnée. Alors que l'accumulation d'incertitudes et, par conséquent, la stockasticité ou l'aléat a augmenté la perspicacité et amis en lumière d'importantes relations entre l'incertitude, la fiabilité, le risque, et leur effet sur les coûts de fonctionnement, il a également (a) introduit une complexité additionnelle qui résulte dans un pouvoir prohibitif des moyens de calcul informatique même pour une simple estimation de l'incertitude; et (b) a conduita une reconnaissance de notre manque d'aptitude à maîtriser l'incertitude totale même en introduisant tous les paramètres connus de l'incertitude. La représentation du changement est introduit: une adaptation de nouvelles méthodes de contrôle intelligent qui va relâcher la dépendance à la rigidité des algorithmes, aux calculs informatiques intensifs, à la PDE stockastique, et qui modifiera l'emphase entre les MRDS—systèmes interactifs d'aide à la décision de multiresolutionelle (flexibles, adaptables et orientables selon les objectifs)—avec un fort apprentissage non (orienté vers l'anticipation plutôt que la prédiction), et une capacité d'optimisation efficiente très élevée, qui pourrait apporter le besoin de solutions pour la modélisation des problèmes de management des aquifères réalistes. Cet article met en lumière les liens entre les développements passés et les futurs moyens d'optimisation, de gestion et de contrôle des systèmes hydrogéologiques. A pesar de nuevos avances notables en hidrología estocástica y las adaptaciones de métodos avanzados de investigación de operaciones, control estocástico, e inteligencia artificial, las soluciones de problemas complejos del mundo real en hidrogeología han sido bastante limitadas. La principal razón es la dependencia definitiva en modelos de primer-principio que conducen a ecuaciones parciales diferencias de parámetro distribuido complejas (PDE) a una escala dada. Mientras que la adición de incertidumbre, y por lo tanto, estocasticidad o aleatoriedad ha incrementado la profundidad y resaltado relaciones importantes entre la incertidumbre, confiabilidad, riesgo, y su efecto en la función de costo, la adición también ha permitido (a) introducir complejidad adicional que resulta en potencia computacional excesiva aún para un solo parámetro incierto/aleatorio; y (b) llevar a reconocer nuestra discapacidad para evaluar la incertidumbre completa aún cuando se incluyen todos los parámetros inciertos. Se introduce un cambio paradigmático: una adaptación de nuevos métodos de control de inteligencia que relajarála dependencia en PDE estocásticas, rígidas y de uso computacional intensivo, cambiando el énfasis hacia un sistema de apoyo de decisiones de propósitos múltiples (MRDS) adaptivo, flexible, y orientadoa objetivos con fuerte aprendizaje sin supervisión (orientado a la anticipación más que a la predicción) con fuerte capacidad de optimización eficiente, lo cual podría aportar las soluciones necesarias a los problemas de manejo reales con los acuíferos. El artículo resalta los vínculos entre desarrollos pasados y control/planificación/optimización futura de sistemas hidrogeológicos.

Scaffolding and Integrated Assessment in Computer Assisted Learning (CAL) for Children with Learning Disabilities

ERIC Educational Resources Information Center

Beale, Ivan L.

2005-01-01

Computer assisted learning (CAL) can involve a computerised intelligent learning environment, defined as an environment capable of automatically, dynamically and continuously adapting to the learning context. One aspect of this adaptive capability involves automatic adjustment of instructional procedures in response to each learner's performance,…

Does Artificial Tutoring Foster Inquiry Based Learning?

ERIC Educational Resources Information Center

Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro

2014-01-01

This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…

Adaptive Dialogue Systems for Assistive Living Environments

ERIC Educational Resources Information Center

Papangelis, Alexandros

2013-01-01

Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

Using Intelligent Tutor Technology to Implement Adaptive Support for Student Collaboration

ERIC Educational Resources Information Center

Diziol, Dejana; Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2010-01-01

Research on computer-supported collaborative learning has shown that students need support to benefit from collaborative activities. While classical collaboration scripts have been effective in providing such support, they have also been criticized for being coercive and not allowing students to self-regulate their learning. Adaptive collaboration…

A Survey of School Psychologists' Practices for Identifying Mentally Retarded Students.

ERIC Educational Resources Information Center

Wodrich, David L.; Barry, Christine T.

1991-01-01

Surveyed school psychologists regarding identification of mentally retarded students. The Wechsler scales were the most frequently used tests for deriving intelligence quotient scores, which together with adaptive behavior scale scores were rated as most influential in identification-placement decisions. The Vineland Adaptive Behavior Scales were…

Preschooler Sleep Patterns Related to Cognitive and Adaptive Functioning

ERIC Educational Resources Information Center

Keefe-Cooperman, Kathleen; Brady-Amoon, Peggy

2014-01-01

Research Findings: Preschoolers' sleep patterns were examined related to cognitive and adaptive functioning. The sample consisted of 874 typically developing preschool children with a mean age of 40.01 months. Parent/caregiver reports of children's sleep pattern factors, Stanford-Binet 5 intelligence scale scores, and Behavior Assessment System…

Dynamic User Modeling within a Game-Based ITS

ERIC Educational Resources Information Center

Snow, Erica L.

2015-01-01

Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…

StairStepper: An Adaptive Remedial iSTART Module

ERIC Educational Resources Information Center

Perret, Cecile A.; Johnson, Amy M.; McCarthy, Kathryn S.; Guerrero, Tricia A.; Dai, Jianmin; McNamara, Danielle S.

2017-01-01

This paper introduces StairStepper, a new addition to Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system (ITS) that provides adaptive self-explanation training and practice. Whereas iSTART focuses on improving comprehension at levels geared toward answering challenging questions associated with…

Behavioral personal digital assistants: The seventh generation of computing

PubMed Central

Stephens, Kenneth R.; Hutchison, William R.

1992-01-01

Skinner (1985) described two divergent approaches to developing computer systems that would behave with some approximation to intelligence. The first approach, which corresponds to the mainstream of artificial intelligence and expert systems, models intelligence as a set of production rules that incorporate knowledge and a set of heuristics for inference and symbol manipulation. The alternative is a system that models the behavioral repertoire as a network of associations between antecedent stimuli and operants, and adapts when supplied with reinforcement. The latter approach is consistent with developments in the field of “neural networks.” The authors describe how an existing adaptive network software system, based on behavior analysis and developed since 1983, can be extended to provide a new generation of software systems capable of acquiring verbal behavior. This effort will require the collaboration of the academic and commercial sectors of the behavioral community, but the end result will enable a generational change in computer systems and support for behavior analytic concepts. PMID:22477053

Multi Sensor Fusion Using Fitness Adaptive Differential Evolution

NASA Astrophysics Data System (ADS)

Giri, Ritwik; Ghosh, Arnob; Chowdhury, Aritra; Das, Swagatam

The rising popularity of multi-source, multi-sensor networks supports real-life applications calls for an efficient and intelligent approach to information fusion. Traditional optimization techniques often fail to meet the demands. The evolutionary approach provides a valuable alternative due to its inherent parallel nature and its ability to deal with difficult problems. We present a new evolutionary approach based on a modified version of Differential Evolution (DE), called Fitness Adaptive Differential Evolution (FiADE). FiADE treats sensors in the network as distributed intelligent agents with various degrees of autonomy. Existing approaches based on intelligent agents cannot completely answer the question of how their agents could coordinate their decisions in a complex environment. The proposed approach is formulated to produce good result for the problems that are high-dimensional, highly nonlinear, and random. The proposed approach gives better result in case of optimal allocation of sensors. The performance of the proposed approach is compared with an evolutionary algorithm coordination generalized particle model (C-GPM).

CATS-based Air Traffic Controller Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

PubMed

Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

2018-03-23

Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.

Perceived Task-Difficulty Recognition from Log-File Information for the Use in Adaptive Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars

2016-01-01

Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

Adaptive Modeling and Real-Time Simulation

DTIC Science & Technology

1984-01-01

34 Artificial Inteligence , Vol. 13, pp. 27-39 (1980). Describes circumscription which is just the assumption that everything that is known to have a particular... Artificial Intelligence Truth Maintenance Planning Resolution Modeling Wcrld Models ~ .. ~2.. ASSTR AT (Coninue n evrse sieIf necesaran Identfy by...represents a marriage of (1) the procedural-network st, planning technology developed in artificial intelligence with (2) the PERT/CPM technology developed in

Defense Logistics Standard Systems Functional Requirements.

DTIC Science & Technology

1987-03-01

Artificial Intelligence - the development of a machine capability to perform functions normally concerned with human intelligence, such as learning , adapting...Basic Data Base Machine Configurations .... ......... D- 18 xx ~ ?f~~~vX PART I: MODELS - DEFENSE LOGISTICS STANDARD SYSTEMS FUNCTIONAL REQUIREMENTS...On-line, Interactive Access. Integrating user input and machine output in a dynamic, real-time, give-and- take process is considered the optimum mode

Intelligence-based anti-doping from an equine biological passport.

PubMed

Cawley, Adam T; Keledjian, John

2017-09-01

The move towards personalized medicine derived from individually focused clinical chemistry measurements has been translated by the human anti-doping movement over the past decade into developing the athlete biological passport. There is considerable potential for animal sports to adapt this model to facilitate an intelligence-based anti-doping system. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Test Review: Wechsler, D. (2005). "Wechsler Intelligence Scale for Children-Fourth Edition Spanish." San Antonio, TX: Harcourt Assessment

ERIC Educational Resources Information Center

Braden, Jeffery P.; Iribarren, Jacqueline A.

2007-01-01

In this article, the authors review the Wechsler Intelligence Scale for Children-Fourth Edition Spanish (WISC-IV Spanish), a Spanish translation and adaptation of the WISC-IV. The test was developed to measure the intellectual ability of Spanish-speaking children in the United States ages 6 years, 0 months, through 16 years, 11 months. These…

Improving the Performance of AI Algorithms.

DTIC Science & Technology

1987-09-01

favorably -6 influenced by s uch progranmning practices as the intellige +nt selt,(-rion .%V ’%. ot’ data formats; to) minimize th~e n,,-ed for...GROUP SUB-GROUP Artifcial Intelgence (Al) Algorithms, Improving Software .’ u- 12 05 Performance, Program Behavior, Predicting Performance, % 12 07...tions in communications, threat assessment, res(orce availability, and so forth. This need for intelligent and adaptable behavior indicates that the

Swarm intelligence. A whole new way to think about business.

PubMed

Bonabeau, E; Meyer, C

2001-05-01

What do ants and bees have to do with business? A great deal, it turns out. Individually, social insects are only minimally intelligent, and their work together is largely self-organized and unsupervised. Yet collectively they're capable of finding highly efficient solutions to difficult problems and can adapt automatically to changing environments. Over the past 20 years, the authors and other researchers have developed rigorous mathematical models to describe this phenomenon, which has been dubbed "swarm intelligence," and they are now applying them to business. Their research has already helped several companies develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy. Emulating the way ants find the shortest path to a new food supply, for example, has led researchers at Hewlett-Packard to develop software programs that can find the most efficient way to route phone traffic over a telecommunications network. South-west Airlines has used a similar model to efficiently route cargo. To allocate labor, honeybees appear to follow one simple but powerful rule--they seem to specialize in a particular activity unless they perceive an important need to perform another function. Using that model, researchers at Northwestern University have devised a system for painting trucks that can automatically adapt to changing conditions. In the future, the authors speculate, a company might structure its entire business using the principles of swarm intelligence. The result, they believe, would be the ultimate self-organizing enterprise--one that could adapt quickly and instinctively to fast-changing markets.

F-15 Intelligent Flight Control System and Aeronautics Research at NASA Dryden

NASA Technical Reports Server (NTRS)

Brown, Nelson A.

2009-01-01

This viewgraph presentation reviews the F-15 Intelligent Flight Control System and Aeronautics including Autonomous Aerial Refueling Demonstrations, X-48B Blended Wing Body, F-15 Quiet Spike, and NF-15 Intelligent Flight Controls.

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

NASA Astrophysics Data System (ADS)

Jiang, Hongkai; Li, Xingqiu; Shao, Haidong; Zhao, Ke

2018-06-01

Traditional intelligent fault diagnosis methods for rolling bearings heavily depend on manual feature extraction and feature selection. For this purpose, an intelligent deep learning method, named the improved deep recurrent neural network (DRNN), is proposed in this paper. Firstly, frequency spectrum sequences are used as inputs to reduce the input size and ensure good robustness. Secondly, DRNN is constructed by the stacks of the recurrent hidden layer to automatically extract the features from the input spectrum sequences. Thirdly, an adaptive learning rate is adopted to improve the training performance of the constructed DRNN. The proposed method is verified with experimental rolling bearing data, and the results confirm that the proposed method is more effective than traditional intelligent fault diagnosis methods.

Individual Differences in Adaptability to Isolated, Confined, and Extreme Environments.

PubMed

Bartone, Paul T; Krueger, Gerald P; Bartone, Jocelyn V

2018-06-01

Future deep space missions will expose astronauts to more intense stressors than previously encountered. Isolation will be greater and more prolonged, living and work areas more confined, and communications and resupply channels to Earth longer and less reliable. Astronauts will need to function more autonomously, with less guidance and support from Earth. Thus, it is important to select and train astronauts who can adapt and function effectively under extreme and variable conditions. In order to identify factors linked to individual adaptability, we conducted a systematic review of the literature on cognitive and behavioral adaptation to isolated, confined, and extreme (ICE) environments. We searched PubMed, Embase, Web of Science, and PsychINFO databases for studies addressing individual adaptability to ICE environments. Studies were rated for quality and fidelity to long-duration space missions and key results extracted. There were 73 studies that met all inclusion criteria. Adaptability attributes for ICE environments include intelligence, emotional stability, self-control, openness, achievement facets of conscientiousness, optimism, mastery, introversion, hardiness, task-oriented coping, past experience, low need for social support, and adequate sleep. This review identifies individual factors linked to adaptability under ICE conditions. Further studies are needed to verify causal directions and determine the relative importance of these factors.Bartone PT, Krueger GP, Bartone JV. Individual differences in adaptability to isolated, confined, and extreme environments. Aerosp Med Hum Perform. 2018; 89(6):536-546.

Intelligent Diagnosis Method for Rotating Machinery Using Dictionary Learning and Singular Value Decomposition

PubMed Central

Han, Te; Jiang, Dongxiang; Zhang, Xiaochen; Sun, Yankui

2017-01-01

Rotating machinery is widely used in industrial applications. With the trend towards more precise and more critical operating conditions, mechanical failures may easily occur. Condition monitoring and fault diagnosis (CMFD) technology is an effective tool to enhance the reliability and security of rotating machinery. In this paper, an intelligent fault diagnosis method based on dictionary learning and singular value decomposition (SVD) is proposed. First, the dictionary learning scheme is capable of generating an adaptive dictionary whose atoms reveal the underlying structure of raw signals. Essentially, dictionary learning is employed as an adaptive feature extraction method regardless of any prior knowledge. Second, the singular value sequence of learned dictionary matrix is served to extract feature vector. Generally, since the vector is of high dimensionality, a simple and practical principal component analysis (PCA) is applied to reduce dimensionality. Finally, the K-nearest neighbor (KNN) algorithm is adopted for identification and classification of fault patterns automatically. Two experimental case studies are investigated to corroborate the effectiveness of the proposed method in intelligent diagnosis of rotating machinery faults. The comparison analysis validates that the dictionary learning-based matrix construction approach outperforms the mode decomposition-based methods in terms of capacity and adaptability for feature extraction. PMID:28346385

Call sign intelligibility improvement using a spatial auditory display

NASA Technical Reports Server (NTRS)

Begault, Durand R.

1993-01-01

A spatial auditory display was used to convolve speech stimuli, consisting of 130 different call signs used in the communications protocol of NASA's John F. Kennedy Space Center, to different virtual auditory positions. An adaptive staircase method was used to determine intelligibility levels of the signal against diotic speech babble, with spatial positions at 30 deg azimuth increments. Non-individualized, minimum-phase approximations of head-related transfer functions were used. The results showed a maximal intelligibility improvement of about 6 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Computing Nash equilibria through computational intelligence methods

NASA Astrophysics Data System (ADS)

Pavlidis, N. G.; Parsopoulos, K. E.; Vrahatis, M. N.

2005-03-01

Nash equilibrium constitutes a central solution concept in game theory. The task of detecting the Nash equilibria of a finite strategic game remains a challenging problem up-to-date. This paper investigates the effectiveness of three computational intelligence techniques, namely, covariance matrix adaptation evolution strategies, particle swarm optimization, as well as, differential evolution, to compute Nash equilibria of finite strategic games, as global minima of a real-valued, nonnegative function. An issue of particular interest is to detect more than one Nash equilibria of a game. The performance of the considered computational intelligence methods on this problem is investigated using multistart and deflection.

Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

NASA Astrophysics Data System (ADS)

Sadek, Add; Basha, Nagi

Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Integrated intelligent systems in advanced reactor control rooms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beckmeyer, R.R.

1989-01-01

An intelligent, reactor control room, information system is designed to be an integral part of an advanced control room and will assist the reactor operator's decision making process by continuously monitoring the current plant state and providing recommended operator actions to improve that state. This intelligent system is an integral part of, as well as an extension to, the plant protection and control systems. This paper describes the interaction of several functional components (intelligent information data display, technical specifications monitoring, and dynamic procedures) of the overall system and the artificial intelligence laboratory environment assembled for testing the prototype. 10 refs.,more » 5 figs.« less

Sex differences in the development of neuroanatomical functional connectivity underlying intelligence found using Bayesian connectivity analysis.

PubMed

Schmithorst, Vincent J; Holland, Scott K

2007-03-01

A Bayesian method for functional connectivity analysis was adapted to investigate between-group differences. This method was applied in a large cohort of almost 300 children to investigate differences in boys and girls in the relationship between intelligence and functional connectivity for the task of narrative comprehension. For boys, a greater association was shown between intelligence and the functional connectivity linking Broca's area to auditory processing areas, including Wernicke's areas and the right posterior superior temporal gyrus. For girls, a greater association was shown between intelligence and the functional connectivity linking the left posterior superior temporal gyrus to Wernicke's areas bilaterally. A developmental effect was also seen, with girls displaying a positive correlation with age in the association between intelligence and the functional connectivity linking the right posterior superior temporal gyrus to Wernicke's areas bilaterally. Our results demonstrate a sexual dimorphism in the relationship of functional connectivity to intelligence in children and an increasing reliance on inter-hemispheric connectivity in girls with age.

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Analytical design of intelligent machines

NASA Technical Reports Server (NTRS)

Saridis, George N.; Valavanis, Kimon P.

1987-01-01

The problem of designing 'intelligent machines' to operate in uncertain environments with minimum supervision or interaction with a human operator is examined. The structure of an 'intelligent machine' is defined to be the structure of a Hierarchically Intelligent Control System, composed of three levels hierarchically ordered according to the principle of 'increasing precision with decreasing intelligence', namely: the organizational level, performing general information processing tasks in association with a long-term memory; the coordination level, dealing with specific information processing tasks with a short-term memory; and the control level, which performs the execution of various tasks through hardware using feedback control methods. The behavior of such a machine may be managed by controls with special considerations and its 'intelligence' is directly related to the derivation of a compatible measure that associates the intelligence of the higher levels with the concept of entropy, which is a sufficient analytic measure that unifies the treatment of all the levels of an 'intelligent machine' as the mathematical problem of finding the right sequence of internal decisions and controls for a system structured in the order of intelligence and inverse order of precision such that it minimizes its total entropy. A case study on the automatic maintenance of a nuclear plant illustrates the proposed approach.

Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

PubMed Central

Poonamallee, Latha; Harrington, Alex M.; Nagpal, Manisha; Musial, Alec

2018-01-01

Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies. PMID:29527182