Intelligent Life-Extending Controls for Aircraft Engines Studied
NASA Technical Reports Server (NTRS)
Guo, Ten-Huei
2005-01-01
Current aircraft engine controllers are designed and operated to provide desired performance and stability margins. Except for the hard limits for extreme conditions, engine controllers do not usually take engine component life into consideration during the controller design and operation. The end result is that aircraft pilots regularly operate engines under unnecessarily harsh conditions to strive for optimum performance. The NASA Glenn Research Center and its industrial and academic partners have been working together toward an intelligent control concept that will include engine life as part of the controller design criteria. This research includes the study of the relationship between control action and engine component life as well as the design of an intelligent control algorithm to provide proper tradeoffs between performance and engine life. This approach is expected to maintain operating safety while minimizing overall operating costs. In this study, the thermomechanical fatigue (TMF) of a critical component was selected to demonstrate how an intelligent engine control algorithm can significantly extend engine life with only a very small sacrifice in performance. An intelligent engine control scheme based on modifying the high-pressure spool speed (NH) was proposed to reduce TMF damage from ground idle to takeoff. The NH acceleration schedule was optimized to minimize the TMF damage for a given rise-time constraint, which represents the performance requirement. The intelligent engine control scheme was used to simulate a commercial short-haul aircraft engine.
NASA Astrophysics Data System (ADS)
Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi
2011-12-01
A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.
NASA Technical Reports Server (NTRS)
Litt, Jonathan; Kurtkaya, Mehmet; Duyar, Ahmet
1994-01-01
This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.
Intelligent control of PV system on the basis of the fuzzy recurrent neuronet*
NASA Astrophysics Data System (ADS)
Engel, E. A.; Kovalev, I. V.; Engel, N. E.
2016-04-01
This paper presents the fuzzy recurrent neuronet for PV system’s control. Based on the PV system’s state, the fuzzy recurrent neural net tracks the maximum power point under random perturbations. The validity and advantages of the proposed intelligent control of PV system are demonstrated by numerical simulations. The simulation results show that the proposed intelligent control of PV system achieves real-time control speed and competitive performance, as compared to a classical control scheme on the basis of the perturbation & observation algorithm.
NASA Astrophysics Data System (ADS)
Capo-Lugo, Pedro A.
Formation flying consists of multiple spacecraft orbiting in a required configuration about a planet or through Space. The National Aeronautics and Space Administration (NASA) Benchmark Tetrahedron Constellation is one of the proposed constellations to be launched in the year 2009 and provides the motivation for this investigation. The problem that will be researched here consists of three stages. The first stage contains the deployment of the satellites; the second stage is the reconfiguration process to transfer the satellites through different specific sizes of the NASA benchmark problem; and, the third stage is the station-keeping procedure for the tetrahedron constellation. Every stage contains different control schemes and transfer procedures to obtain/maintain the proposed tetrahedron constellation. In the first stage, the deployment procedure will depend on a combination of two techniques in which impulsive maneuvers and a digital controller are used to deploy the satellites and to maintain the tetrahedron constellation at the following apogee point. The second stage that corresponds to the reconfiguration procedure shows a different control scheme in which the intelligent control systems are implemented to perform this procedure. In this research work, intelligent systems will eliminate the use of complex mathematical models and will reduce the computational time to perform different maneuvers. Finally, the station-keeping process, which is the third stage of this research problem, will be implemented with a two-level hierarchical control scheme to maintain the separation distance constraints of the NASA Benchmark Tetrahedron Constellation. For this station-keeping procedure, the system of equations defining the dynamics of a pair of satellites is transformed to take in account the perturbation due to the oblateness of the Earth and the disturbances due to solar pressure. The control procedures used in this research will be transformed from a continuous control system to a digital control system which will simplify the implementation into the computer onboard the satellite. In addition, this research will show an introductory chapter on attitude dynamics that can be used to maintain the orientation of the satellites, and an adaptive intelligent control scheme will be proposed to maintain the desired orientation of the spacecraft. In conclusion, a solution for the dynamics of the NASA Benchmark Tetrahedron Constellation will be presented in this research work. The main contribution of this work is the use of discrete control schemes, impulsive maneuvers, and intelligent control schemes that can be used to reduce the computational time in which these control schemes can be easily implemented in the computer onboard the satellite. These contributions are explained through the deployment, reconfiguration, and station-keeping process of the proposed NASA Benchmark Tetrahedron Constellation.
Intelligent control of non-linear dynamical system based on the adaptive neurocontroller
NASA Astrophysics Data System (ADS)
Engel, E.; Kovalev, I. V.; Kobezhicov, V.
2015-10-01
This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.
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.
Effect of noise in intelligent cellular decision making.
Bates, Russell; Blyuss, Oleg; Alsaedi, Ahmed; Zaikin, Alexey
2015-01-01
Similar to intelligent multicellular neural networks controlling human brains, even single cells, surprisingly, are able to make intelligent decisions to classify several external stimuli or to associate them. This happens because of the fact that gene regulatory networks can perform as perceptrons, simple intelligent schemes known from studies on Artificial Intelligence. We study the role of genetic noise in intelligent decision making at the genetic level and show that noise can play a constructive role helping cells to make a proper decision. We show this using the example of a simple genetic classifier able to classify two external stimuli.
NASA Astrophysics Data System (ADS)
Park, Sangsoo; Miura, Yushi; Ise, Toshifumi
This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.
An Intelligent Actuator Fault Reconstruction Scheme for Robotic Manipulators.
Xiao, Bing; Yin, Shen
2018-02-01
This paper investigates a difficult problem of reconstructing actuator faults for robotic manipulators. An intelligent approach with fast reconstruction property is developed. This is achieved by using observer technique. This scheme is capable of precisely reconstructing the actual actuator fault. It is shown by Lyapunov stability analysis that the reconstruction error can converge to zero after finite time. A perfect reconstruction performance including precise and fast properties can be provided for actuator fault. The most important feature of the scheme is that, it does not depend on control law, dynamic model of actuator, faults' type, and also their time-profile. This super reconstruction performance and capability of the proposed approach are further validated by simulation and experimental results.
Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.
Xu, Bin; Sun, Fuchun
2018-02-01
This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.
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.
Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan; Li, Hai
2014-01-01
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme.
Dong, Zhekang; Duan, Shukai; Hu, Xiaofang; Wang, Lidan
2014-01-01
In this paper, we present an implementation scheme of memristor-based multilayer feedforward small-world neural network (MFSNN) inspirited by the lack of the hardware realization of the MFSNN on account of the need of a large number of electronic neurons and synapses. More specially, a mathematical closed-form charge-governed memristor model is presented with derivation procedures and the corresponding Simulink model is presented, which is an essential block for realizing the memristive synapse and the activation function in electronic neurons. Furthermore, we investigate a more intelligent memristive PID controller by incorporating the proposed MFSNN into intelligent PID control based on the advantages of the memristive MFSNN on computation speed and accuracy. Finally, numerical simulations have demonstrated the effectiveness of the proposed scheme. PMID:25202723
Chang, Yeong-Chan
2005-12-01
This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.
Advanced feedback control methods in EXTRAP T2R reversed field pinch
NASA Astrophysics Data System (ADS)
Yadikin, D.; Brunsell, P. R.; Paccagnella, R.
2006-07-01
Previous experiments in the EXTRAP T2R reversed field pinch device have shown the possibility of suppression of multiple resistive wall modes (RWM). A feedback system has been installed in EXTRAP T2R having 100% coverage of the toroidal surface by the active coil array. Predictions based on theory and the previous experimental results show that the number of active coils should be sufficient for independent stabilization of all unstable RWMs in the EXTRAP T2R. Experiments using different feedback schemes are performed, comparing the intelligent shell, the fake rotating shell, and the mode control with complex feedback gains. Stabilization of all unstable RWMs throughout the discharge duration of td≈10τw is seen using the intelligent shell feedback scheme. Mode rotation and the control of selected Fourier harmonics is obtained simultaneously using the mode control scheme with complex gains. Different sensor signals are studied. A feedback system with toroidal magnetic field sensors could have an advantage of lower feedback gain needed for the RWM suppression compared to the system with radial magnetic field sensors. In this study, RWM suppression is demonstrated, using also the toroidal field component as a sensor signal in the feedback system.
Intelligent call admission control for multi-class services in mobile cellular networks
NASA Astrophysics Data System (ADS)
Ma, Yufeng; Hu, Xiulin; Zhang, Yunyu
2005-11-01
Scarcity of the spectrum resource and mobility of users make quality of service (QoS) provision a critical issue in mobile cellular networks. This paper presents a fuzzy call admission control scheme to meet the requirement of the QoS. A performance measure is formed as a weighted linear function of new call and handoff call blocking probabilities of each service class. Simulation compares the proposed fuzzy scheme with complete sharing and guard channel policies. Simulation results show that fuzzy scheme has a better robust performance in terms of average blocking criterion.
Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.
Wang, Lukun; Zhao, Xiaoying; Su, Hao; Tang, Gongyou
2016-01-01
This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control. Firstly, the kinematic model and dynamics model of intelligent vehicle with non-holonomic constraint are established. Secondly, two constraints of lane changing on curved road in practice (LCCP) are proposed. Thirdly, two arcs with same curvature are constructed for the desired lane changing trajectory. According to the geometrical characteristics of arcs trajectory, equations of desired state can be calculated. Finally, the backstepping method is employed to design a kinematic trajectory tracking controller. Then the sliding-mode dynamics controller is designed to ensure that the motion of the intelligent vehicle can follow the desired velocity generated by kinematic controller. The stability of control system is proved by Lyapunov theory. Computer simulation demonstrates that the desired arcs trajectory and state curves with B-spline optimization can meet the requirements of LCCP constraints and the proposed control schemes can make tracking errors to converge uniformly.
Autonomous power expert system
NASA Technical Reports Server (NTRS)
Ringer, Mark J.; Quinn, Todd M.
1990-01-01
The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.
Autonomous power expert system
NASA Technical Reports Server (NTRS)
Ringer, Mark J.; Quinn, Todd M.
1990-01-01
The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.
Artificial intelligence in a mission operations and satellite test environment
NASA Technical Reports Server (NTRS)
Busse, Carl
1988-01-01
A Generic Mission Operations System using Expert System technology to demonstrate the potential of Artificial Intelligence (AI) automated monitor and control functions in a Mission Operations and Satellite Test environment will be developed at the National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL). Expert system techniques in a real time operation environment are being studied and applied to science and engineering data processing. Advanced decommutation schemes and intelligent display technology will be examined to develop imaginative improvements in rapid interpretation and distribution of information. The Generic Payload Operations Control Center (GPOCC) will demonstrate improved data handling accuracy, flexibility, and responsiveness in a complex mission environment. The ultimate goal is to automate repetitious mission operations, instrument, and satellite test functions by the applications of expert system technology and artificial intelligence resources and to enhance the level of man-machine sophistication.
Design of on-board parallel computer on nano-satellite
NASA Astrophysics Data System (ADS)
You, Zheng; Tian, Hexiang; Yu, Shijie; Meng, Li
2007-11-01
This paper provides one scheme of the on-board parallel computer system designed for the Nano-satellite. Based on the development request that the Nano-satellite should have a small volume, low weight, low power cost, and intelligence, this scheme gets rid of the traditional one-computer system and dual-computer system with endeavor to improve the dependability, capability and intelligence simultaneously. According to the method of integration design, it employs the parallel computer system with shared memory as the main structure, connects the telemetric system, attitude control system, and the payload system by the intelligent bus, designs the management which can deal with the static tasks and dynamic task-scheduling, protect and recover the on-site status and so forth in light of the parallel algorithms, and establishes the fault diagnosis, restoration and system restructure mechanism. It accomplishes an on-board parallel computer system with high dependability, capability and intelligence, a flexible management on hardware resources, an excellent software system, and a high ability in extension, which satisfies with the conception and the tendency of the integration electronic design sufficiently.
EXODUS: Integrating intelligent systems for launch operations support
NASA Technical Reports Server (NTRS)
Adler, Richard M.; Cottman, Bruce H.
1991-01-01
Kennedy Space Center (KSC) is developing knowledge-based systems to automate critical operations functions for the space shuttle fleet. Intelligent systems will monitor vehicle and ground support subsystems for anomalies, assist in isolating and managing faults, and plan and schedule shuttle operations activities. These applications are being developed independently of one another, using different representation schemes, reasoning and control models, and hardware platforms. KSC has recently initiated the EXODUS project to integrate these stand alone applications into a unified, coordinated intelligent operations support system. EXODUS will be constructed using SOCIAL, a tool for developing distributed intelligent systems. EXODUS, SOCIAL, and initial prototyping efforts using SOCIAL to integrate and coordinate selected EXODUS applications are described.
Intelligent on-line fault tolerant control for unanticipated catastrophic failures.
Yen, Gary G; Ho, Liang-Wei
2004-10-01
As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.
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.
Performance Analysis of Cluster Formation in Wireless Sensor Networks.
Montiel, Edgar Romo; Rivero-Angeles, Mario E; Rubino, Gerardo; Molina-Lozano, Heron; Menchaca-Mendez, Rolando; Menchaca-Mendez, Ricardo
2017-12-13
Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes.
Performance Analysis of Cluster Formation in Wireless Sensor Networks
Montiel, Edgar Romo; Rivero-Angeles, Mario E.; Rubino, Gerardo; Molina-Lozano, Heron; Menchaca-Mendez, Rolando; Menchaca-Mendez, Ricardo
2017-01-01
Clustered-based wireless sensor networks have been extensively used in the literature in order to achieve considerable energy consumption reductions. However, two aspects of such systems have been largely overlooked. Namely, the transmission probability used during the cluster formation phase and the way in which cluster heads are selected. Both of these issues have an important impact on the performance of the system. For the former, it is common to consider that sensor nodes in a clustered-based Wireless Sensor Network (WSN) use a fixed transmission probability to send control data in order to build the clusters. However, due to the highly variable conditions experienced by these networks, a fixed transmission probability may lead to extra energy consumption. In view of this, three different transmission probability strategies are studied: optimal, fixed and adaptive. In this context, we also investigate cluster head selection schemes, specifically, we consider two intelligent schemes based on the fuzzy C-means and k-medoids algorithms and a random selection with no intelligence. We show that the use of intelligent schemes greatly improves the performance of the system, but their use entails higher complexity and selection delay. The main performance metrics considered in this work are energy consumption, successful transmission probability and cluster formation latency. As an additional feature of this work, we study the effect of errors in the wireless channel and the impact on the performance of the system under the different transmission probability schemes. PMID:29236065
Towards using musculoskeletal models for intelligent control of physically assistive robots.
Carmichael, Marc G; Liu, Dikai
2011-01-01
With the increasing number of robots being developed to physically assist humans in tasks such as rehabilitation and assistive living, more intelligent and personalized control systems are desired. In this paper we propose the use of a musculoskeletal model to estimate the strength of the user, from which information can be utilized to improve control schemes in which robots physically assist humans. An optimization model is developed utilizing a musculoskeletal model to estimate human strength in a specified dynamic state. Results of this optimization as well as methods of using it to observe muscle-based weaknesses in task space are presented. Lastly potential methods and problems in incorporating this model into a robot control system are discussed.
Towards a Collaborative Intelligent Tutoring System Classification Scheme
ERIC Educational Resources Information Center
Harsley, Rachel
2014-01-01
This paper presents a novel classification scheme for Collaborative Intelligent Tutoring Systems (CITS), an emergent research field. The three emergent classifications of CITS are unstructured, semi-structured, and fully structured. While all three types of CITS offer opportunities to improve student learning gains, the full extent to which these…
Research on intelligent power consumption strategy based on time-of-use pricing
NASA Astrophysics Data System (ADS)
Fu, Wei; Gong, Li; Chen, Heli; He, Yu
2017-06-01
In this paper, through the analysis of shortcomings of the current domestic and foreign household power consumption strategy: Passive way of power consumption, ignoring the different priority of electric equipment, neglecting the actual load pressure of the grid, ignoring the interaction with the user, to decrease the peak-valley difference and improve load curve in residential area by demand response (DR technology), an intelligent power consumption scheme based on time-of-use(TOU) pricing for household appliances is proposed. The main contribution of this paper is: (1) Three types of household appliance loads are abstracted from different operating laws of various household appliances, and the control models and DR strategies corresponding to these types are established. (2) The fuzzified processing for the information of TOU price, which is based on the time intervals, is performed to get the price priority, in accordance with such DR events as the maximum restricted load of DR, the time of DR and the duration of interruptible load and so on, the DR control rule and pre-scheduling mechanism are led in. (3) The dispatching sequence of household appliances in the control and scheduling queue are switched and controlled to implement the equilibrium of peak and valley loads. The equilibrium effects and economic benefits of power system by pre-scheduling and DR dispatching are compared and analyzed by simulation example, and the results show that using the proposed household appliance control (HAC) scheme the overall cost of consumers can be reduced and the power system load can be alleviated, so the proposed household appliance control (HAC) scheme is feasible and reasonable.
Jena, Manas Kumar; Samantaray, Subhransu Ranjan
2016-01-01
This paper presents a data-mining-based intelligent differential relaying scheme for transmission lines, including flexible ac transmission system device, such as unified power flow controller (UPFC) and wind farms. Initially, the current and voltage signals are processed through extended Kalman filter phasor measurement unit for phasor estimation, and 21 potential features are computed at both ends of the line. Once the features are extracted at both ends, the corresponding differential features are derived. These differential features are fed to a data-mining model known as decision tree (DT) to provide the final relaying decision. The proposed technique has been extensively tested for single-circuit transmission line, including UPFC and wind farms with in-feed, double-circuit line with UPFC on one line and wind farm as one of the substations with wide variations in operating parameters. The test results obtained from simulation as well as in real-time digital simulator testing indicate that the DT-based intelligent differential relaying scheme is highly reliable and accurate with a response time of 2.25 cycles from the fault inception.
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.
ERIC Educational Resources Information Center
Claybrook, Billy G.
A new heuristic factorization scheme uses learning to improve the efficiency of determining the symbolic factorization of multivariable polynomials with interger coefficients and an arbitrary number of variables and terms. The factorization scheme makes extensive use of artificial intelligence techniques (e.g., model-building, learning, and…
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.
A high-resolution and intelligent dead pixel detection scheme for an electrowetting display screen
NASA Astrophysics Data System (ADS)
Luo, ZhiJie; Luo, JianKun; Zhao, WenWen; Cao, Yang; Lin, WeiJie; Zhou, GuoFu
2018-02-01
Electrowetting display technology is realized by tuning the surface energy of a hydrophobic surface by applying a voltage based on electrowetting mechanism. With the rapid development of the electrowetting industry, how to analyze efficiently the quality of an electrowetting display screen has a very important significance. There are two kinds of dead pixels on the electrowetting display screen. One is that the oil of pixel cannot completely cover the display area. The other is that indium tin oxide semiconductor wire connecting pixel and foil was burned. In this paper, we propose a high-resolution and intelligent dead pixel detection scheme for an electrowetting display screen. First, we built an aperture ratio-capacitance model based on the electrical characteristics of electrowetting display. A field-programmable gate array is used as the integrated logic hub of the system for a highly reliable and efficient control of the circuit. Dead pixels can be detected and displayed on a PC-based 2D graphical interface in real time. The proposed dead pixel detection scheme reported in this work has promise in automating electrowetting display experiments.
ERIC Educational Resources Information Center
Metz, Dale Evan; And Others
1992-01-01
A preliminary scheme for estimating the speech intelligibility of hearing-impaired speakers from acoustic parameters, using a computerized artificial neural network to process mathematically the acoustic input variables, is outlined. Tests with 60 hearing-impaired speakers found the scheme to be highly accurate in identifying speakers separated by…
NASA Astrophysics Data System (ADS)
Yadikin, D.; Brunsell, P. R.; Drake, J. R.
2006-01-01
An active feedback system is required for long pulse operation of the reversed field pinch (RFP) device to suppress resistive wall modes (RWMs). A general feature of a feedback system using a discrete active coil array is a coupling effect which arises when a set of side band modes determined by the number of active coils is produced. Recent results obtained on the EXTRAP T2R RFP demonstrated the suppression of independent m = 1 RWMs using an active feedback system with a two-dimensional array of discrete active coils in the poloidal and toroidal directions. One of the feedback algorithms used is the intelligent shell feedback scheme. Active feedback systems having different number of active coils in the poloidal (Mc) and toroidal (Nc) directions (Mc × Nc = 2 × 32 and Mc × Nc = 4 × 16) are studied. Different side band effects are seen for these configurations. A significant prolongation of the plasma discharge is achieved for the intelligent shell feedback scheme using the 2 × 32 active coil configuration. This is attributed to the side band sets including only one of the dominant unstable RWMs and avoiding coupling to resonant modes. Analog proportional-integral-derivative controllers are used in the feedback system. Regimes with different values of the proportional gain are studied. The requirement of the proportional-integral control for low proportional gain and proportional-derivative control for high proportional gain is seen in the experiments.
Scheduling policies of intelligent sensors and sensor/actuators in flexible structures
NASA Astrophysics Data System (ADS)
Demetriou, Michael A.; Potami, Raffaele
2006-03-01
In this note, we revisit the problem of actuator/sensor placement in large civil infrastructures and flexible space structures within the context of spatial robustness. The positioning of these devices becomes more important in systems employing wireless sensor and actuator networks (WSAN) for improved control performance and for rapid failure detection. The ability of the sensing and actuating devices to possess the property of spatial robustness results in reduced control energy and therefore the spatial distribution of disturbances is integrated into the location optimization measures. In our studies, the structure under consideration is a flexible plate clamped at all sides. First, we consider the case of sensor placement and the optimization scheme attempts to produce those locations that minimize the effects of the spatial distribution of disturbances on the state estimation error; thus the sensor locations produce state estimators with minimized disturbance-to-error transfer function norms. A two-stage optimization procedure is employed whereby one first considers the open loop system and the spatial distribution of disturbances is found that produces the maximal effects on the entire open loop state. Once this "worst" spatial distribution of disturbances is found, the optimization scheme subsequently finds the locations that produce state estimators with minimum transfer function norms. In the second part, we consider the collocated actuator/sensor pairs and the optimization scheme produces those locations that result in compensators with the smallest norms of the disturbance-to-state transfer functions. Going a step further, an intelligent control scheme is presented which, at each time interval, activates a subset of the actuator/sensor pairs in order provide robustness against spatiotemporally moving disturbances and minimize power consumption by keeping some sensor/actuators in sleep mode.
Automatic spin-chain learning to explore the quantum speed limit
NASA Astrophysics Data System (ADS)
Zhang, Xiao-Ming; Cui, Zi-Wei; Wang, Xin; Yung, Man-Hong
2018-05-01
One of the ambitious goals of artificial intelligence is to build a machine that outperforms human intelligence, even if limited knowledge and data are provided. Reinforcement learning (RL) provides one such possibility to reach this goal. In this work, we consider a specific task from quantum physics, i.e., quantum state transfer in a one-dimensional spin chain. The mission for the machine is to find transfer schemes with the fastest speeds while maintaining high transfer fidelities. The first scenario we consider is when the Hamiltonian is time independent. We update the coupling strength by minimizing a loss function dependent on both the fidelity and the speed. Compared with a scheme proven to be at the quantum speed limit for the perfect state transfer, the scheme provided by RL is faster while maintaining the infidelity below 5 ×10-4 . In the second scenario where a time-dependent external field is introduced, we convert the state transfer process into a Markov decision process that can be understood by the machine. We solve it with the deep Q-learning algorithm. After training, the machine successfully finds transfer schemes with high fidelities and speeds, which are faster than previously known ones. These results show that reinforcement learning can be a powerful tool for quantum control problems.
Enhancing the stabilization of aircraft pitch motion control via intelligent and classical method
NASA Astrophysics Data System (ADS)
Lukman, H.; Munawwarah, S.; Azizan, A.; Yakub, F.; Zaki, S. A.; Rasid, Z. A.
2017-12-01
The pitching movement of an aircraft is very important to ensure passengers are intrinsically safe and the aircraft achieve its maximum stability. The equations governing the motion of an aircraft are a complex set of six nonlinear coupled differential equations. Under certain assumptions, it can be decoupled and linearized into longitudinal and lateral equations. Pitch control is a longitudinal problem and thus, only the longitudinal dynamics equations are involved in this system. It is a third order nonlinear system, which is linearized about the operating point. The system is also inherently unstable due to the presence of a free integrator. Because of this, a feedback controller is added in order to solve this problem and enhance the system performance. This study uses two approaches in designing controller: a conventional controller and an intelligent controller. The pitch control scheme consists of proportional, integral and derivatives (PID) for conventional controller and fuzzy logic control (FLC) for intelligent controller. Throughout the paper, the performance of the presented controllers are investigated and compared based on the common criteria of step response. Simulation results have been obtained and analysed by using Matlab and Simulink software. The study shows that FLC controller has higher ability to control and stabilize the aircraft's pitch angle as compared to PID controller.
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.
Using new aggregation operators in rule-based intelligent control
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Chen, Yung-Yaw; Yager, Ronald R.
1990-01-01
A new aggregation operator is applied in the design of an approximate reasoning-based controller. The ordered weighted averaging (OWA) operator has the property of lying between the And function and the Or function used in previous fuzzy set reasoning systems. It is shown here that, by applying OWA operators, more generalized types of control rules, which may include linguistic quantifiers such as Many and Most, can be developed. The new aggregation operators, as tested in a cart-pole balancing control problem, illustrate improved performance when compared with existing fuzzy control aggregation schemes.
NASA Technical Reports Server (NTRS)
Defeo, P.; Chen, M.
1987-01-01
Means for evaluating data bus architectures and protocols for highly integrated flight control system applications are needed. Described are the criteria and plans to do this by using the NASA/Ames Intelligent Redundant Actuation System (IRAS) experimental set-up. Candidate bus architectures differ from one another in terms of: topology, access control, message transfer schemes, message characteristics, initialization. data flow control, transmission rates, fault tolerance, and time synchronization. The evaluation criteria are developed relative to these features. A preliminary, analytical evaluation of four candidate busses (MIL-STD-1553B, DATAC, Ethernet, and HSIS) is described. A bus must be exercised in a real-time environment to evaluate its dynamic characteristics. A plan for real-time evaluation of these four busses using a combination of hardware and simulation techniques is presented.
An intelligent control scheme for precise tip-motion control in atomic force microscopy.
Wang, Yanyan; Hu, Xiaodong; Xu, Linyan
2016-01-01
The paper proposes a new intelligent control method to precisely control the tip motion of the atomic force microscopy (AFM). The tip moves up and down at a high rate along the z direction during scanning, requiring the utilization of a rapid feedback controller. The standard proportional-integral (PI) feedback controller is commonly used in commercial AFMs to enable topography measurements. The controller's response performance is determined by the set of the proportional (P) parameter and the integral (I) parameter. However, the two parameters cannot be automatically altered simultaneously according to the scanning speed and the surface topography during continuors scanning, leading to an inaccurate measurement. Thus a new intelligent controller combining the fuzzy controller and the PI controller is put forward in the paper. The new controller automatically selects the most appropriate PI parameters to achieve a fast response rate on basis of the tracking errors. In the experimental setup, the new controller is realized with a digital signal process (DSP) system, implemented in a conventional AFM system. Experiments are carried out by comparing the new method with the standard PI controller. The results demonstrate that the new method is more robust and effective for the precise tip motion control, corresponding to the achievement of a highly qualified image by shortening the response time of the controller. © Wiley Periodicals, Inc.
De Momi, E; Ferrigno, G
2010-01-01
The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.
Design of housing file box of fire academy based on RFID
NASA Astrophysics Data System (ADS)
Li, Huaiyi
2018-04-01
This paper presents a design scheme of intelligent file box based on RFID. The advantages of RFID file box and traditional file box are compared and analyzed, and the feasibility of RFID file box design is analyzed based on the actual situation of our university. After introducing the shape and structure design of the intelligent file box, the paper discusses the working process of the file box, and explains in detail the internal communication principle of the RFID file box and the realization of the control system. The application of the RFID based file box will greatly improve the efficiency of our school's archives management.
The sixth generation robot in space
NASA Technical Reports Server (NTRS)
Butcher, A.; Das, A.; Reddy, Y. V.; Singh, H.
1990-01-01
The knowledge based simulator developed in the artificial intelligence laboratory has become a working test bed for experimenting with intelligent reasoning architectures. With this simulator, recently, small experiments have been done with an aim to simulate robot behavior to avoid colliding paths. An automatic extension of such experiments to intelligently planning robots in space demands advanced reasoning architectures. One such architecture for general purpose problem solving is explored. The robot, seen as a knowledge base machine, goes via predesigned abstraction mechanism for problem understanding and response generation. The three phases in one such abstraction scheme are: abstraction for representation, abstraction for evaluation, and abstraction for resolution. Such abstractions require multimodality. This multimodality requires the use of intensional variables to deal with beliefs in the system. Abstraction mechanisms help in synthesizing possible propagating lattices for such beliefs. The machine controller enters into a sixth generation paradigm.
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.
Intelligent Power Swing Detection Scheme to Prevent False Relay Tripping Using S-Transform
NASA Astrophysics Data System (ADS)
Mohamad, Nor Z.; Abidin, Ahmad F.; Musirin, Ismail
2014-06-01
Distance relay design is equipped with out-of-step tripping scheme to ensure correct distance relay operation during power swing. The out-of-step condition is a consequence result from unstable power swing. It requires proper detection of power swing to initiate a tripping signal followed by separation of unstable part from the entire power system. The distinguishing process of unstable swing from stable swing poses a challenging task. This paper presents an intelligent approach to detect power swing based on S-Transform signal processing tool. The proposed scheme is based on the use of S-Transform feature of active power at the distance relay measurement point. It is demonstrated that the proposed scheme is able to detect and discriminate the unstable swing from stable swing occurring in the system. To ascertain validity of the proposed scheme, simulations were carried out with the IEEE 39 bus system and its performance has been compared with the wavelet transform-based power swing detection scheme.
NASA Astrophysics Data System (ADS)
Wang, Jin; Xu, Fan; Lu, GuoDong
2017-09-01
More complex problems of simultaneous position and internal force control occur with cooperative manipulator systems than that of a single one. In the presence of unwanted parametric and modelling uncertainties as well as external disturbances, a decentralised position synchronised force control scheme is proposed. With a feedforward neural network estimating engine, a precise model of the system dynamics is not required. Unlike conventional cooperative or synchronised controllers, virtual position and virtual synchronisation errors are introduced for internal force tracking control and task space position synchronisation. Meanwhile joint space synchronisation and force measurement are unnecessary. Together with simulation studies and analysis, the position and the internal force errors are shown to asymptotically converge to zero. Moreover, the controller exhibits different characteristics with selected synchronisation factors. Under certain settings, it can deal with temporary cooperation by an intelligent retreat mechanism, where less internal force would occur and rigid collision can be avoided. Using a Lyapunov stability approach, the controller is proven to be robust in face of the aforementioned uncertainties.
NASA Technical Reports Server (NTRS)
Duyar, A.; Guo, T.-H.; Merrill, W.; Musgrave, J.
1992-01-01
In a previous study, Guo, Merrill and Duyar, 1990, reported a conceptual development of a fault detection and diagnosis system for actuation faults of the space shuttle main engine. This study, which is a continuation of the previous work, implements the developed fault detection and diagnosis scheme for the real time actuation fault diagnosis of the space shuttle main engine. The scheme will be used as an integral part of an intelligent control system demonstration experiment at NASA Lewis. The diagnosis system utilizes a model based method with real time identification and hypothesis testing for actuation, sensor, and performance degradation faults.
Effects of Instantaneous Multiband Dynamic Compression on Speech Intelligibility
NASA Astrophysics Data System (ADS)
Herzke, Tobias; Hohmann, Volker
2005-12-01
The recruitment phenomenon, that is, the reduced dynamic range between threshold and uncomfortable level, is attributed to the loss of instantaneous dynamic compression on the basilar membrane. Despite this, hearing aids commonly use slow-acting dynamic compression for its compensation, because this was found to be the most successful strategy in terms of speech quality and intelligibility rehabilitation. Former attempts to use fast-acting compression gave ambiguous results, raising the question as to whether auditory-based recruitment compensation by instantaneous compression is in principle applicable in hearing aids. This study thus investigates instantaneous multiband dynamic compression based on an auditory filterbank. Instantaneous envelope compression is performed in each frequency band of a gammatone filterbank, which provides a combination of time and frequency resolution comparable to the normal healthy cochlea. The gain characteristics used for dynamic compression are deduced from categorical loudness scaling. In speech intelligibility tests, the instantaneous dynamic compression scheme was compared against a linear amplification scheme, which used the same filterbank for frequency analysis, but employed constant gain factors that restored the sound level for medium perceived loudness in each frequency band. In subjective comparisons, five of nine subjects preferred the linear amplification scheme and would not accept the instantaneous dynamic compression in hearing aids. Four of nine subjects did not perceive any quality differences. A sentence intelligibility test in noise (Oldenburg sentence test) showed little to no negative effects of the instantaneous dynamic compression, compared to linear amplification. A word intelligibility test in quiet (one-syllable rhyme test) showed that the subjects benefit from the larger amplification at low levels provided by instantaneous dynamic compression. Further analysis showed that the increase in intelligibility resulting from a gain provided by instantaneous compression is as high as from a gain provided by linear amplification. No negative effects of the distortions introduced by the instantaneous compression scheme in terms of speech recognition are observed.
Rizvi, Sanam Shahla; Chung, Tae-Sun
2010-01-01
Flash memory has become a more widespread storage medium for modern wireless devices because of its effective characteristics like non-volatility, small size, light weight, fast access speed, shock resistance, high reliability and low power consumption. Sensor nodes are highly resource constrained in terms of limited processing speed, runtime memory, persistent storage, communication bandwidth and finite energy. Therefore, for wireless sensor networks supporting sense, store, merge and send schemes, an efficient and reliable file system is highly required with consideration of sensor node constraints. In this paper, we propose a novel log structured external NAND flash memory based file system, called Proceeding to Intelligent service oriented memorY Allocation for flash based data centric Sensor devices in wireless sensor networks (PIYAS). This is the extended version of our previously proposed PIYA [1]. The main goals of the PIYAS scheme are to achieve instant mounting and reduced SRAM space by keeping memory mapping information to a very low size of and to provide high query response throughput by allocation of memory to the sensor data by network business rules. The scheme intelligently samples and stores the raw data and provides high in-network data availability by keeping the aggregate data for a longer period of time than any other scheme has done before. We propose effective garbage collection and wear-leveling schemes as well. The experimental results show that PIYAS is an optimized memory management scheme allowing high performance for wireless sensor networks.
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
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.
Neuro-fuzzy control of structures using acceleration feedback
NASA Astrophysics Data System (ADS)
Schurter, Kyle C.; Roschke, Paul N.
2001-08-01
This paper described a new approach for the reduction of environmentally induced vibration in constructed facilities by way of a neuro-fuzzy technique. The new control technique is presented and tested in a numerical study that involves two types of building models. The energy of each building is dissipated through magnetorheological (MR) dampers whose damping properties are continuously updated by a fuzzy controller. This semi-active control scheme relies on the development of a correlation between the accelerations of the building (controller input) and the voltage applied to the MR damper (controller output). This correlation forms the basis for the development of an intelligent neuro-fuzzy control strategy. To establish a context for assessing the effectiveness of the semi-active control scheme, responses to earthquake excitation are compared with passive strategies that have similar authority for control. According to numerical simulation, MR dampers are less effective control mechanisms than passive dampers with respect to a single degree of freedom (DOF) building model. On the other hand, MR dampers are predicted to be superior when used with multiple DOF structures for reduction of lateral acceleration.
End-User Tools Towards AN Efficient Electricity Consumption: the Dynamic Smart Grid
NASA Astrophysics Data System (ADS)
Kamel, Fouad; Kist, Alexander A.
2010-06-01
Growing uncontrolled electrical demands have caused increased supply requirements. This causes volatile electrical markets and has detrimental unsustainable environmental impacts. The market is presently characterized by regular daily peak demand conditions associated with high electricity prices. A demand-side response system can limit peak demands to an acceptable level. The proposed scheme is based on energy demand and price information which is available online. An online server is used to communicate the information of electricity suppliers to users, who are able to use the information to manage and control their own demand. A configurable, intelligent switching system is used to control local loads during peak events and mange the loads at other times as necessary. The aim is to shift end user loads towards periods where energy demand and therefore also prices are at the lowest. As a result, this will flatten the load profile and avoiding load peeks which are costly for suppliers. The scheme is an endeavour towards achieving a dynamic smart grid demand-side-response environment using information-based communication and computer-controlled switching. Diffusing the scheme shall lead to improved electrical supply services and controlled energy consumption and prices.
Research on robot mobile obstacle avoidance control based on visual information
NASA Astrophysics Data System (ADS)
Jin, Jiang
2018-03-01
Robots to detect obstacles and control robots to avoid obstacles has been a key research topic of robot control. In this paper, a scheme of visual information acquisition is proposed. By judging visual information, the visual information is transformed into the information source of path processing. In accordance with the established route, in the process of encountering obstacles, the algorithm real-time adjustment trajectory to meet the purpose of intelligent control of mobile robots. Simulation results show that, through the integration of visual sensing information, the obstacle information is fully obtained, while the real-time and accuracy of the robot movement control is guaranteed.
A CLS-based survivable and energy-saving WDM-PON architecture
NASA Astrophysics Data System (ADS)
Zhu, Min; Zhong, Wen-De; Zhang, Zhenrong; Luan, Feng
2013-11-01
We propose and demonstrate an improved survivable and energy-saving WDM-PON with colorless ONUs. It incorporates both energy-saving and self-healing operations. A simple effective energy-saving scheme is proposed by including an energy-saving control unit in the OLT and a control unit at each ONU. The energy-saving scheme realizes both dozing and sleep (offline) modes, which greatly improves the energy-saving efficiency for WDM-PONs. An intelligent protection switching scheme is designed in the OLT, which can distinguish if an ONU is in dozing/sleep (offline) state or a fiber is faulty. Moreover, by monitoring the optical power of each channel on both working and protection paths, the OLT can know the connection status of every fiber path, thus facilitating an effective protection switching and a faster failure recovery. The improved WDM-PON architecture not only significantly reduces energy consumption, but also performs self-healing operation in practical operation scenarios. The scheme feasibility is experimentally verified with 10 Gbit/s downstream and 1.25 Gbit/s upstream transmissions. We also examine the energy-saving efficiency of our proposed energy-saving scheme by simulation, which reveals that energy saving mainly arises from the dozing mode, not from the sleep mode when the ONU is in the online state.
Intercluster Connection in Cognitive Wireless Mesh Networks Based on Intelligent Network Coding
NASA Astrophysics Data System (ADS)
Chen, Xianfu; Zhao, Zhifeng; Jiang, Tao; Grace, David; Zhang, Honggang
2009-12-01
Cognitive wireless mesh networks have great flexibility to improve spectrum resource utilization, within which secondary users (SUs) can opportunistically access the authorized frequency bands while being complying with the interference constraint as well as the QoS (Quality-of-Service) requirement of primary users (PUs). In this paper, we consider intercluster connection between the neighboring clusters under the framework of cognitive wireless mesh networks. Corresponding to the collocated clusters, data flow which includes the exchanging of control channel messages usually needs four time slots in traditional relaying schemes since all involved nodes operate in half-duplex mode, resulting in significant bandwidth efficiency loss. The situation is even worse at the gateway node connecting the two colocated clusters. A novel scheme based on network coding is proposed in this paper, which needs only two time slots to exchange the same amount of information mentioned above. Our simulation shows that the network coding-based intercluster connection has the advantage of higher bandwidth efficiency compared with the traditional strategy. Furthermore, how to choose an optimal relaying transmission power level at the gateway node in an environment of coexisting primary and secondary users is discussed. We present intelligent approaches based on reinforcement learning to solve the problem. Theoretical analysis and simulation results both show that the intelligent approaches can achieve optimal throughput for the intercluster relaying in the long run.
Intelligent demand side management of residential building energy systems
NASA Astrophysics Data System (ADS)
Sinha, Maruti N.
Advent of modern sensing technologies, data processing capabilities and rising cost of energy are driving the implementation of intelligent systems in buildings and houses which constitute 41% of total energy consumption. The primary motivation has been to provide a framework for demand-side management and to improve overall reliability. The entire formulation is to be implemented on NILM (Non-Intrusive Load Monitoring System), a smart meter. This is going to play a vital role in the future of demand side management. Utilities have started deploying smart meters throughout the world which will essentially help to establish communication between utility and consumers. This research is focused on investigation of a suitable thermal model of residential house, building up control system and developing diagnostic and energy usage forecast tool. The present work has considered measurement based approach to pursue. Identification of building thermal parameters is the very first step towards developing performance measurement and controls. The proposed identification technique is PEM (Prediction Error Method) based, discrete state-space model. The two different models have been devised. First model is focused toward energy usage forecast and diagnostics. Here one of the novel idea has been investigated which takes integral of thermal capacity to identify thermal model of house. The purpose of second identification is to build up a model for control strategy. The controller should be able to take into account the weather forecast information, deal with the operating point constraints and at the same time minimize the energy consumption. To design an optimal controller, MPC (Model Predictive Control) scheme has been implemented instead of present thermostatic/hysteretic control. This is a receding horizon approach. Capability of the proposed schemes has also been investigated.
Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.
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.
High-performance object tracking and fixation with an online neural estimator.
Kumarawadu, Sisil; Watanabe, Keigo; Lee, Tsu-Tian
2007-02-01
Vision-based target tracking and fixation to keep objects that move in three dimensions in view is important for many tasks in several fields including intelligent transportation systems and robotics. Much of the visual control literature has focused on the kinematics of visual control and ignored a number of significant dynamic control issues that limit performance. In line with this, this paper presents a neural network (NN)-based binocular tracking scheme for high-performance target tracking and fixation with minimum sensory information. The procedure allows the designer to take into account the physical (Lagrangian dynamics) properties of the vision system in the control law. The design objective is to synthesize a binocular tracking controller that explicitly takes the systems dynamics into account, yet needs no knowledge of dynamic nonlinearities and joint velocity sensory information. The combined neurocontroller-observer scheme can guarantee the uniform ultimate bounds of the tracking, observer, and NN weight estimation errors under fairly general conditions on the controller-observer gains. The controller is tested and verified via simulation tests in the presence of severe target motion changes.
Pressure intelligent control strategy of Waste heat recovery system of converter vapors
NASA Astrophysics Data System (ADS)
Feng, Xugang; Wu, Zhiwei; Zhang, Jiayan; Qian, Hong
2013-01-01
The converter gas evaporative cooling system is mainly used for absorbing heat in the high temperature exhaust gas which produced by the oxygen blowing reaction. Vaporization cooling steam pressure control system of converter is a nonlinear, time-varying, lagging behind, close coupling of multivariable control object. This article based on the analysis of converter operation characteristics of evaporation cooling system, of vaporization in a production run of pipe pressure variation and disturbance factors.For the dynamic characteristics of the controlled objects,we have improved the conventional PID control scheme.In Oxygen blowing process, we make intelligent control by using fuzzy-PID cascade control method and adjusting the Lance,that it can realize the optimization of the boiler steam pressure control.By design simulation, results show that the design has a good control not only ensures drum steam pressure in the context of security, enabling efficient conversion of waste heat.And the converter of 1800 flue gas through pipes and cool and dust removal also can be cooled to about 800. Therefore the converter haze evaporative cooling system has achieved to the converter haze temperature decrease effect and enhanced to the coal gas returns-ratio.
Automation of closed environments in space for human comfort and safety
NASA Technical Reports Server (NTRS)
1992-01-01
This report culminates the work accomplished during a three year design project on the automation of an Environmental Control and Life Support System (ECLSS) suitable for space travel and colonization. The system would provide a comfortable living environment in space that is fully functional with limited human supervision. A completely automated ECLSS would increase astronaut productivity while contributing to their safety and comfort. The first section of this report, section 1.0, briefly explains the project, its goals, and the scheduling used by the team in meeting these goals. Section 2.0 presents an in-depth look at each of the component subsystems. Each subsection describes the mathematical modeling and computer simulation used to represent that portion of the system. The individual models have been integrated into a complete computer simulation of the CO2 removal process. In section 3.0, the two simulation control schemes are described. The classical control approach uses traditional methods to control the mechanical equipment. The expert control system uses fuzzy logic and artificial intelligence to control the system. By integrating the two control systems with the mathematical computer simulation, the effectiveness of the two schemes can be compared. The results are then used as proof of concept in considering new control schemes for the entire ECLSS. Section 4.0 covers the results and trends observed when the model was subjected to different test situations. These results provide insight into the operating procedures of the model and the different control schemes. The appendix, section 5.0, contains summaries of lectures presented during the past year, homework assignments, and the completed source code used for the computer simulation and control system.
A hybrid intelligent controller for a twin rotor MIMO system and its hardware implementation.
Juang, Jih-Gau; Liu, Wen-Kai; Lin, Ren-Wei
2011-10-01
This paper presents a fuzzy PID control scheme with a real-valued genetic algorithm (RGA) to a setpoint control problem. The objective of this paper is to control a twin rotor MIMO system (TRMS) to move quickly and accurately to the desired attitudes, both the pitch angle and the azimuth angle in a cross-coupled condition. A fuzzy compensator is applied to the PID controller. The proposed control structure includes four PID controllers with independent inputs in 2-DOF. In order to reduce total error and control energy, all parameters of the controller are obtained by a RGA with the system performance index as a fitness function. The system performance index utilized the integral of time multiplied by the square error criterion (ITSE) to build a suitable fitness function in the RGA. A new method for RGA to solve more than 10 parameters in the control scheme is investigated. For real-time control, Xilinx Spartan II SP200 FPGA (Field Programmable Gate Array) is employed to construct a hardware-in-the-loop system through writing VHDL on this FPGA. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.
1983-11-03
capability. An intelligent library management system will be supported by knowledge-based techniques. In fact, until a formal specification of library...from artificial intelligence and information science 2 might also be useful, for example automatic indexing and cataloging schemes, methods for fast...Artificial Intelligence 5:1045-1058, 1977. [Burstall & Goguen 801 Burstall, R. M., and Goguen, J. A. The Semantics of Clear, a Specification Language. In
Drive Control System for Pipeline Crawl Robot Based on CAN Bus
NASA Astrophysics Data System (ADS)
Chen, H. J.; Gao, B. T.; Zhang, X. H.; Deng2, Z. Q.
2006-10-01
Drive control system plays important roles in pipeline robot. In order to inspect the flaw and corrosion of seabed crude oil pipeline, an original mobile pipeline robot with crawler drive unit, power and monitor unit, central control unit, and ultrasonic wave inspection device is developed. The CAN bus connects these different function units and presents a reliable information channel. Considering the limited space, a compact hardware system is designed based on an ARM processor with two CAN controllers. With made-to-order CAN protocol for the crawl robot, an intelligent drive control system is developed. The implementation of the crawl robot demonstrates that the presented drive control scheme can meet the motion control requirements of the underwater pipeline crawl robot.
Gomaa Haroun, A H; Li, Yin-Ya
2017-11-01
In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Biomechanical modeling and load-carrying simulation of lower limb exoskeleton.
Zhu, Yanhe; Zhang, Guoan; Zhang, Chao; Liu, Gangfeng; Zhao, Jie
2015-01-01
This paper introduces novel modern equipment-a lower extremity exoskeleton, which can implement the mutual complement and the interaction between human intelligence and the robot's mechanical strength. In order to provide a reference for the exoskeleton structure and the drive unit, the human biomechanics were modeled and analyzed by LifeModeler and Adams software to derive each joint kinematic parameter. The control was designed to implement the zero-force interaction between human and exoskeleton. Furthermore, simulations were performed to verify the control and assist effect. In conclusion, the system scheme of lower extremity exoskeleton is demonstrated to be feasible.
Chiang, Kai-Wei; Chang, Hsiu-Wen; Li, Chia-Yuan; Huang, Yun-Wen
2009-01-01
Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated. PMID:22574034
Brain limbic system-based intelligent controller application to lane change manoeuvre
NASA Astrophysics Data System (ADS)
Kim, Changwon; Langari, Reza
2011-12-01
This paper presents the application of a novel neuromorphic control strategy for lane change manoeuvres in the highway environment. The lateral dynamics of a vehicle with and without wind disturbance are derived and utilised to implement a control strategy based on the brain limbic system. To show the robustness of the proposed controller, several disturbance conditions including wind, uncertainty in the cornering stiffness, and changes in the vehicle mass are investigated. To demonstrate the performance of the suggested strategy, simulation results of the proposed method are compared with the human driver model-based control scheme, which has been discussed in the literature. The simulation results demonstrate the superiority of the proposed controller in energy efficiency, driving comfort, and robustness.
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…
2017-12-11
provides ultra-low energy search operations. To improve throughput, the in-array pipeline scheme has been developed, allowing the MeTCAM to operate at a...controlled magnetic tunnel junction (VC-MTJ), which not only reduces cell area (thus achieving higher density) but also eliminates standby energy . This...Variations of the cell design are presented and evaluated. The results indicated a potential 90x improvement in the energy efficiency and a 50x
A Roadmap for Aircraft Engine Life Extending Control
NASA Technical Reports Server (NTRS)
Guo, Ten-Huei
2001-01-01
The concept of Aircraft Engine Life Extending Control is introduced. A brief description of the tradeoffs between performance and engine life are first explained. The overall goal of the life extending controller is to reduce the engine operating cost by extending the on-wing engine life while improving operational safety. The research results for NASA's Rocket Engine life extending control program are also briefly described. Major building blocks of the Engine Life Extending Control architecture are examined. These blocks include: life prediction models, engine operation models, stress and thermal analysis tools, control schemes, and intelligent control systems. The technology areas that would likely impact the successful implementation of an aircraft engine life extending control are also briefly described. Near, intermediate, and long term goals of NASA's activities are also presented.
Kaburlasos, V G; Petridis, V; Brett, P N; Baker, D A
1999-12-01
Stapedotomy is a surgical procedure aimed at the treatment of hearing impairment due to otosclerosis. The treatment consists of drilling a hole through the stapes bone in the inner ear in order to insert a prosthesis. Safety precautions require knowledge of the nonmeasurable stapes thickness. The technical goal herein has been the design of high-level controls for an intelligent mechatronics drilling tool in order to enable the estimation of stapes thickness from measurable drilling data. The goal has been met by learning a map between drilling features, hence no model of the physical system has been necessary. Learning has been achieved as explained in this paper by a scheme, namely the d-sigma Fuzzy Lattice Neurocomputing (d sigma-FLN) scheme for classification, within the framework of fuzzy lattices. The successful application of the d sigma-FLN scheme is demonstrated in estimating the thickness of a stapes bone "on-line" using drilling data obtained experimentally in the laboratory.
Yu, Yu-Ning; Doctor, Faiyaz; Fan, Shou-Zen; Shieh, Jiann-Shing
2018-04-13
During surgical procedures, bispectral index (BIS) is a well-known measure used to determine the patient's depth of anesthesia (DOA). However, BIS readings can be subject to interference from many factors during surgery, and other parameters such as blood pressure (BP) and heart rate (HR) can provide more stable indicators. However, anesthesiologist still consider BIS as a primary measure to determine if the patient is correctly anaesthetized while relaying on the other physiological parameters to monitor and ensure the patient's status is maintained. The automatic control of administering anesthesia using intelligent control systems has been the subject of recent research in order to alleviate the burden on the anesthetist to manually adjust drug dosage in response physiological changes for sustaining DOA. A system proposed for the automatic control of anesthesia based on type-2 Self Organizing Fuzzy Logic Controllers (T2-SOFLCs) has been shown to be effective in the control of DOA under simulated scenarios while contending with uncertainties due to signal noise and dynamic changes in pharmacodynamics (PD) and pharmacokinetic (PK) effects of the drug on the body. This study considers both BIS and BP as part of an adaptive automatic control scheme, which can adjust to the monitoring of either parameter in response to changes in the availability and reliability of BIS signals during surgery. The simulation of different control schemes using BIS data obtained during real surgical procedures to emulate noise and interference factors have been conducted. The use of either or both combined parameters for controlling the delivery Propofol to maintain safe target set points for DOA are evaluated. The results show that combing BIS and BP based on the proposed adaptive control scheme can ensure the target set points and the correct amount of drug in the body is maintained even with the intermittent loss of BIS signal that could otherwise disrupt an automated control system.
Synthetic cognitive development. Where intelligence comes from
NASA Astrophysics Data System (ADS)
Weinbaum (Weaver), D.; Veitas, V.
2017-01-01
The human cognitive system is a remarkable exemplar of a general intelligent system whose competence is not confined to a specific problem domain. Evidently, general cognitive competences are a product of a prolonged and complex process of cognitive development. Therefore, the process of cognitive development is a primary key to understanding the emergence of intelligent behavior. This paper develops the theoretical foundations for a model that generalizes the process of cognitive development. The model aims to provide a realistic scheme for the synthesis of scalable cognitive systems with an open-ended range of capabilities. Major concepts and theories of human cognitive development are introduced and briefly explored, focusing on the enactive approach to cognition and the concept of sense-making. The initial scheme of human cognitive development is then generalized by introducing the philosophy of individuation and the abstract mechanism of transduction. The theory of individuation provides the ground for the necessary paradigmatic shift from cognitive systems as given products to cognitive development as a formative process of self-organization. Next, the conceptual model is specified as a scalable scheme of networks of agents. The mechanisms of individuation are formulated in context-independent information theoretical terms. Finally, the paper discusses two concrete aspects of the generative model - mechanisms of transduction and value modulating systems. These are topics of further research towards an implementable architecture.
GT-CATS: Tracking Operator Activities in Complex Systems
NASA Technical Reports Server (NTRS)
Callantine, Todd J.; Mitchell, Christine M.; Palmer, Everett A.
1999-01-01
Human operators of complex dynamic systems can experience difficulties supervising advanced control automation. One remedy is to develop intelligent aiding systems that can provide operators with context-sensitive advice and reminders. The research reported herein proposes, implements, and evaluates a methodology for activity tracking, a form of intent inferencing that can supply the knowledge required for an intelligent aid by constructing and maintaining a representation of operator activities in real time. The methodology was implemented in the Georgia Tech Crew Activity Tracking System (GT-CATS), which predicts and interprets the actions performed by Boeing 757/767 pilots navigating using autopilot flight modes. This report first describes research on intent inferencing and complex modes of automation. It then provides a detailed description of the GT-CATS methodology, knowledge structures, and processing scheme. The results of an experimental evaluation using airline pilots are given. The results show that GT-CATS was effective in predicting and interpreting pilot actions in real time.
An intelligent load shedding scheme using neural networks and neuro-fuzzy.
Haidar, Ahmed M A; Mohamed, Azah; Al-Dabbagh, Majid; Hussain, Aini; Masoum, Mohammad
2009-12-01
Load shedding is some of the essential requirement for maintaining security of modern power systems, particularly in competitive energy markets. This paper proposes an intelligent scheme for fast and accurate load shedding using neural networks for predicting the possible loss of load at the early stage and neuro-fuzzy for determining the amount of load shed in order to avoid a cascading outage. A large scale electrical power system has been considered to validate the performance of the proposed technique in determining the amount of load shed. The proposed techniques can provide tools for improving the reliability and continuity of power supply. This was confirmed by the results obtained in this research of which sample results are given in this paper.
Liu, Changxin; Gao, Jian; Li, Huiping; Xu, Demin
2018-05-01
The event-triggered control is a promising solution to cyber-physical systems, such as networked control systems, multiagent systems, and large-scale intelligent systems. In this paper, we propose an event-triggered model predictive control (MPC) scheme for constrained continuous-time nonlinear systems with bounded disturbances. First, a time-varying tightened state constraint is computed to achieve robust constraint satisfaction, and an event-triggered scheduling strategy is designed in the framework of dual-mode MPC. Second, the sufficient conditions for ensuring feasibility and closed-loop robust stability are developed, respectively. We show that robust stability can be ensured and communication load can be reduced with the proposed MPC algorithm. Finally, numerical simulations and comparison studies are performed to verify the theoretical results.
NASA Astrophysics Data System (ADS)
Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza
2016-06-01
This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.
Master-slave control scheme in electric vehicle smart charging infrastructure.
Chung, Ching-Yen; Chynoweth, Joshua; Chu, Chi-Cheng; Gadh, Rajit
2014-01-01
WINSmartEV is a software based plug-in electric vehicle (PEV) monitoring, control, and management system. It not only incorporates intelligence at every level so that charge scheduling can avoid grid bottlenecks, but it also multiplies the number of PEVs that can be plugged into a single circuit. This paper proposes, designs, and executes many upgrades to WINSmartEV. These upgrades include new hardware that makes the level 1 and level 2 chargers faster, more robust, and more scalable. It includes algorithms that provide a more optimal charge scheduling for the level 2 (EVSE) and an enhanced vehicle monitoring/identification module (VMM) system that can automatically identify PEVs and authorize charging.
Master-Slave Control Scheme in Electric Vehicle Smart Charging Infrastructure
Chung, Ching-Yen; Chynoweth, Joshua; Chu, Chi-Cheng; Gadh, Rajit
2014-01-01
WINSmartEV is a software based plug-in electric vehicle (PEV) monitoring, control, and management system. It not only incorporates intelligence at every level so that charge scheduling can avoid grid bottlenecks, but it also multiplies the number of PEVs that can be plugged into a single circuit. This paper proposes, designs, and executes many upgrades to WINSmartEV. These upgrades include new hardware that makes the level 1 and level 2 chargers faster, more robust, and more scalable. It includes algorithms that provide a more optimal charge scheduling for the level 2 (EVSE) and an enhanced vehicle monitoring/identification module (VMM) system that can automatically identify PEVs and authorize charging. PMID:24982956
Harlander, Niklas; Rosenkranz, Tobias; Hohmann, Volker
2012-08-01
Single channel noise reduction has been well investigated and seems to have reached its limits in terms of speech intelligibility improvement, however, the quality of such schemes can still be advanced. This study tests to what extent novel model-based processing schemes might improve performance in particular for non-stationary noise conditions. Two prototype model-based algorithms, a speech-model-based, and a auditory-model-based algorithm were compared to a state-of-the-art non-parametric minimum statistics algorithm. A speech intelligibility test, preference rating, and listening effort scaling were performed. Additionally, three objective quality measures for the signal, background, and overall distortions were applied. For a better comparison of all algorithms, particular attention was given to the usage of the similar Wiener-based gain rule. The perceptual investigation was performed with fourteen hearing-impaired subjects. The results revealed that the non-parametric algorithm and the auditory model-based algorithm did not affect speech intelligibility, whereas the speech-model-based algorithm slightly decreased intelligibility. In terms of subjective quality, both model-based algorithms perform better than the unprocessed condition and the reference in particular for highly non-stationary noise environments. Data support the hypothesis that model-based algorithms are promising for improving performance in non-stationary noise conditions.
Learning and tuning fuzzy logic controllers through reinforcements.
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.
2016-07-14
applicability of the sensor model in the context under consideration. A similar information flow can be considered for obtaining direct reliability of an... Modeling , Bex Concepts Human Intelligence Simulation USE CASES Army: Opns in Megacities, Syrian Civil War Navy: Piracy (NATO, Book), Autonomous ISR...2007) 6 [25] Bex, F. and Verheij, B ., Story Schemes for Argumentation about the Facts of a Crime, Computational Models of Narrative: Papers from the
Improving multivariate Horner schemes with Monte Carlo tree search
NASA Astrophysics Data System (ADS)
Kuipers, J.; Plaat, A.; Vermaseren, J. A. M.; van den Herik, H. J.
2013-11-01
Optimizing the cost of evaluating a polynomial is a classic problem in computer science. For polynomials in one variable, Horner's method provides a scheme for producing a computationally efficient form. For multivariate polynomials it is possible to generalize Horner's method, but this leaves freedom in the order of the variables. Traditionally, greedy schemes like most-occurring variable first are used. This simple textbook algorithm has given remarkably efficient results. Finding better algorithms has proved difficult. In trying to improve upon the greedy scheme we have implemented Monte Carlo tree search, a recent search method from the field of artificial intelligence. This results in better Horner schemes and reduces the cost of evaluating polynomials, sometimes by factors up to two.
Applications of artificial intelligence in safe human-robot interactions.
Najmaei, Nima; Kermani, Mehrdad R
2011-04-01
The integration of industrial robots into the human workspace presents a set of unique challenges. This paper introduces a new sensory system for modeling, tracking, and predicting human motions within a robot workspace. A reactive control scheme to modify a robot's operations for accommodating the presence of the human within the robot workspace is also presented. To this end, a special class of artificial neural networks, namely, self-organizing maps (SOMs), is employed for obtaining a superquadric-based model of the human. The SOM network receives information of the human's footprints from the sensory system and infers necessary data for rendering the human model. The model is then used in order to assess the danger of the robot operations based on the measured as well as predicted human motions. This is followed by the introduction of a new reactive control scheme that results in the least interferences between the human and robot operations. The approach enables the robot to foresee an upcoming danger and take preventive actions before the danger becomes imminent. Simulation and experimental results are presented in order to validate the effectiveness of the proposed method.
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.
Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei
2016-01-01
We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.
Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei
2016-01-01
We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot’s performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks. PMID:27806074
Agent Based Fault Tolerance for the Mobile Environment
NASA Astrophysics Data System (ADS)
Park, Taesoon
This paper presents a fault-tolerance scheme based on mobile agents for the reliable mobile computing systems. Mobility of the agent is suitable to trace the mobile hosts and the intelligence of the agent makes it efficient to support the fault tolerance services. This paper presents two approaches to implement the mobile agent based fault tolerant service and their performances are evaluated and compared with other fault-tolerant schemes.
NASA Astrophysics Data System (ADS)
Nishikawa, Robert M.; Giger, Maryellen L.; Doi, Kunio; Vyborny, Carl J.; Schmidt, Robert A.; Metz, Charles E.; Wu, Chris Y.; Yin, Fang-Fang; Jiang, Yulei; Huo, Zhimin; Lu, Ping; Zhang, Wei; Ema, Takahiro; Bick, Ulrich; Papaioannou, John; Nagel, Rufus H.
1993-07-01
We are developing an 'intelligent' workstation to assist radiologists in diagnosing breast cancer from mammograms. The hardware for the workstation will consist of a film digitizer, a high speed computer, a large volume storage device, a film printer, and 4 high resolution CRT monitors. The software for the workstation is a comprehensive package of automated detection and classification schemes. Two rule-based detection schemes have been developed, one for breast masses and the other for clustered microcalcifications. The sensitivity of both schemes is 85% with a false-positive rate of approximately 3.0 and 1.5 false detections per image, for the mass and cluster detection schemes, respectively. Computerized classification is performed by an artificial neural network (ANN). The ANN has a sensitivity of 100% with a specificity of 60%. Currently, the ANN, which is a three-layer, feed-forward network, requires as input ratings of 14 different radiographic features of the mammogram that were determined subjectively by a radiologist. We are in the process of developing automated techniques to objectively determine these 14 features. The workstation will be placed in the clinical reading area of the radiology department in the near future, where controlled clinical tests will be performed to measure its efficacy.
Discrete shaped strain sensors for intelligent structures
NASA Technical Reports Server (NTRS)
Andersson, Mark S.; Crawley, Edward F.
1992-01-01
Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.
Information Processing in Cognition Process and New Artificial Intelligent Systems
NASA Astrophysics Data System (ADS)
Zheng, Nanning; Xue, Jianru
In this chapter, we discuss, in depth, visual information processing and a new artificial intelligent (AI) system that is based upon cognitive mechanisms. The relationship between a general model of intelligent systems and cognitive mechanisms is described, and in particular we explore visual information processing with selective attention. We also discuss a methodology for studying the new AI system and propose some important basic research issues that have emerged in the intersecting fields of cognitive science and information science. To this end, a new scheme for associative memory and a new architecture for an AI system with attractors of chaos are addressed.
NASA Astrophysics Data System (ADS)
Ismail, Firas B.; Thiruchelvam, Vinesh
2013-06-01
Steam condenser is one of the most important equipment in steam power plants. If the steam condenser trips it may lead to whole unit shutdown, which is economically burdensome. Early condenser trips monitoring is crucial to maintain normal and safe operational conditions. In the present work, artificial intelligent monitoring systems specialized in condenser outages has been proposed and coded within the MATLAB environment. The training and validation of the system has been performed using real operational measurements captured from the control system of selected steam power plant. An integrated plant data preparation scheme for condenser outages with related operational variables has been proposed. Condenser outages under consideration have been detected by developed system before the plant control system"
An overview on real-time control schemes for wheeled mobile robot
NASA Astrophysics Data System (ADS)
Radzak, M. S. A.; Ali, M. A. H.; Sha’amri, S.; Azwan, A. R.
2018-04-01
The purpose of this paper is to review real-time control motion algorithms for wheeled mobile robot (WMR) when navigating in environment such as road. Its need a good controller to avoid collision with any disturbance and maintain a track error at zero level. The controllers are used with other aiding sensors to measure the WMR’s velocities, posture, and interference to estimate the required torque to be applied on the wheels of mobile robot. Four main categories for wheeled mobile robot control systems have been found in literature which are namely: Kinematic based controller, Dynamic based controllers, artificial intelligence based control system, and Active Force control. A MATLAB/Simulink software is the main software to simulate and implement the control system. The real-time toolbox in MATLAB/SIMULINK are used to receive/send data from sensors/to actuator with presence of disturbances, however others software such C, C++ and visual basic are rare to be used.
Performance-cost evaluation methodology for ITS equipment deployment
DOT National Transportation Integrated Search
2000-09-01
Although extensive Intelligent Transportation Systems (ITS) technology is being deployed in the field, little analysis is being performed to evaluate the benefits of implementation schemes. Benefit analysis is particularly in need for one popular ITS...
Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng
2018-01-11
Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes.
A systematic review of current and emergent manipulator control approaches
NASA Astrophysics Data System (ADS)
Ajwad, Syed Ali; Iqbal, Jamshed; Ullah, Muhammad Imran; Mehmood, Adeel
2015-06-01
Pressing demands of productivity and accuracy in today's robotic applications have highlighted an urge to replace classical control strategies with their modern control counterparts. This recent trend is further justified by the fact that the robotic manipulators have complex nonlinear dynamic structure with uncertain parameters. Highlighting the authors' research achievements in the domain of manipulator design and control, this paper presents a systematic and comprehensive review of the state-of-the-art control techniques that find enormous potential in controlling manipulators to execute cuttingedge applications. In particular, three kinds of strategies, i.e., intelligent proportional-integral-derivative (PID) scheme, robust control and adaptation based approaches, are reviewed. Future trend in the subject area is commented. Open-source simulators to facilitate controller design are also tabulated. With a comprehensive list of references, it is anticipated that the review will act as a firsthand reference for researchers, engineers and industrialinterns to realize the control laws for multi-degree of freedom (DOF) manipulators.
Approaches to the study of intelligence
NASA Technical Reports Server (NTRS)
Norman, Donald A.
1991-01-01
A survey and an evaluation are conducted for the Rosenbloom et al. (1991) 'SOAR' model of intelligence, both as found in humans and in prospective AI systems, which views it as a representational system for goal-oriented symbolic activity based on a physical symbol system. Attention is given to SOAR's implications for semantic and episodic memory, symbol processing, and search within a uniform problem space; also noted are the relationships of SOAR to competing AI schemes, and its potential usefulness as a theoretical tool for cognitive psychology.
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.
Learning and tuning fuzzy logic controllers through reinforcements
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Khedkar, Pratap
1992-01-01
A new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. In particular, our Generalized Approximate Reasoning-based Intelligent Control (GARIC) architecture: (1) learns and tunes a fuzzy logic controller even when only weak reinforcements, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) 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. We extend the AHC algorithm of Barto, Sutton, and Anderson to include the prior control knowledge of human operators. The GARIC architecture is applied to a cart-pole balancing system and has demonstrated 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.
Visual privacy by context: proposal and evaluation of a level-based visualisation scheme.
Padilla-López, José Ramón; Chaaraoui, Alexandros Andre; Gu, Feng; Flórez-Revuelta, Francisco
2015-06-04
Privacy in image and video data has become an important subject since cameras are being installed in an increasing number of public and private spaces. Specifically, in assisted living, intelligent monitoring based on computer vision can allow one to provide risk detection and support services that increase people's autonomy at home. In the present work, a level-based visualisation scheme is proposed to provide visual privacy when human intervention is necessary, such as at telerehabilitation and safety assessment applications. Visualisation levels are dynamically selected based on the previously modelled context. In this way, different levels of protection can be provided, maintaining the necessary intelligibility required for the applications. Furthermore, a case study of a living room, where a top-view camera is installed, is presented. Finally, the performed survey-based evaluation indicates the degree of protection provided by the different visualisation models, as well as the personal privacy preferences and valuations of the users.
Improved biliary detection and diagnosis through intelligent machine analysis.
Logeswaran, Rajasvaran
2012-09-01
This paper reports on work undertaken to improve automated detection of bile ducts in magnetic resonance cholangiopancreatography (MRCP) images, with the objective of conducting preliminary classification of the images for diagnosis. The proposed I-BDeDIMA (Improved Biliary Detection and Diagnosis through Intelligent Machine Analysis) scheme is a multi-stage framework consisting of successive phases of image normalization, denoising, structure identification, object labeling, feature selection and disease classification. A combination of multiresolution wavelet, dynamic intensity thresholding, segment-based region growing, region elimination, statistical analysis and neural networks, is used in this framework to achieve good structure detection and preliminary diagnosis. Tests conducted on over 200 clinical images with known diagnosis have shown promising results of over 90% accuracy. The scheme outperforms related work in the literature, making it a viable framework for computer-aided diagnosis of biliary diseases. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Intelligent Engine Systems: Thermal Management and Advanced Cooling
NASA Technical Reports Server (NTRS)
Bergholz, Robert
2008-01-01
The objective is to provide turbine-cooling technologies to meet Propulsion 21 goals related to engine fuel burn, emissions, safety, and reliability. Specifically, the GE Aviation (GEA) Advanced Turbine Cooling and Thermal Management program seeks to develop advanced cooling and flow distribution methods for HP turbines, while achieving a substantial reduction in total cooling flow and assuring acceptable turbine component safety and reliability. Enhanced cooling techniques, such as fluidic devices, controlled-vortex cooling, and directed impingement jets, offer the opportunity to incorporate both active and passive schemes. Coolant heat transfer enhancement also can be achieved from advanced designs that incorporate multi-disciplinary optimization of external film and internal cooling passage geometry.
A robust trust establishment scheme for wireless sensor networks.
Ishmanov, Farruh; Kim, Sung Won; Nam, Seung Yeob
2015-03-23
Security techniques like cryptography and authentication can fail to protect a network once a node is compromised. Hence, trust establishment continuously monitors and evaluates node behavior to detect malicious and compromised nodes. However, just like other security schemes, trust establishment is also vulnerable to attack. Moreover, malicious nodes might misbehave intelligently to trick trust establishment schemes. Unfortunately, attack-resistance and robustness issues with trust establishment schemes have not received much attention from the research community. Considering the vulnerability of trust establishment to different attacks and the unique features of sensor nodes in wireless sensor networks, we propose a lightweight and robust trust establishment scheme. The proposed trust scheme is lightweight thanks to a simple trust estimation method. The comprehensiveness and flexibility of the proposed trust estimation scheme make it robust against different types of attack and misbehavior. Performance evaluation under different types of misbehavior and on-off attacks shows that the detection rate of the proposed trust mechanism is higher and more stable compared to other trust mechanisms.
NASA Technical Reports Server (NTRS)
Colombano, Silvano; Norvig, Peter (Technical Monitor)
2000-01-01
Few human endeavors can be viewed both as extremely successful and unsuccessful at the same time. This is typically the case when goals have not been well defined or have been shifting in time. This has certainly been true of Artificial Intelligence (AI). The nature of intelligence has been the object of much thought and speculation throughout the history of philosophy. It is in the nature of philosophy that real headway is sometimes made only when appropriate tools become available. Similarly the computer, coupled with the ability to program (at least in principle) any function, appeared to be the tool that could tackle the notion of intelligence. To suit the tool, the problem of the nature of intelligence was soon sidestepped in favor of this notion: If a probing conversation with a computer could not be distinguished from a conversation with a human, then AI had been achieved. This notion became known as the Turing test, after the mathematician Alan Turing who proposed it in 1950. Conceptually rich and interesting, these early efforts gave rise to a large portion of the field's framework. Key to AI, rather than the 'number crunching' typical of computers until then, was viewed as the ability to manipulate symbols and make logical inferences. To facilitate these tasks, AI languages such as LISP and Prolog were invented and used widely in the field. One idea that emerged and enabled some success with real world problems was the notion that 'most intelligence' really resided in knowledge. A phrase attributed to Feigenbaum, one of the pioneers, was 'knowledge is the power.' With this premise, the problem is shifted from 'how do we solve problems' to 'how do we represent knowledge.' A good knowledge representation scheme could allow one to draw conclusions from given premises. Such schemes took forms such as rules,frames and scripts. It allowed the building of what became known as expert systems or knowledge based systems (KBS).
Variable cycle control model for intersection based on multi-source information
NASA Astrophysics Data System (ADS)
Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan
2018-05-01
In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.
Li, Congcong; Zhang, Xi; Wang, Haiping; Li, Dongfeng
2018-01-01
Vehicular sensor networks have been widely applied in intelligent traffic systems in recent years. Because of the specificity of vehicular sensor networks, they require an enhanced, secure and efficient authentication scheme. Existing authentication protocols are vulnerable to some problems, such as a high computational overhead with certificate distribution and revocation, strong reliance on tamper-proof devices, limited scalability when building many secure channels, and an inability to detect hardware tampering attacks. In this paper, an improved authentication scheme using certificateless public key cryptography is proposed to address these problems. A security analysis of our scheme shows that our protocol provides an enhanced secure anonymous authentication, which is resilient against major security threats. Furthermore, the proposed scheme reduces the incidence of node compromise and replication attacks. The scheme also provides a malicious-node detection and warning mechanism, which can quickly identify compromised static nodes and immediately alert the administrative department. With performance evaluations, the scheme can obtain better trade-offs between security and efficiency than the well-known available schemes. PMID:29324719
Game Theory for Wireless Sensor Networks: A Survey
Shi, Hai-Yan; Wang, Wan-Liang; Kwok, Ngai-Ming; Chen, Sheng-Yong
2012-01-01
Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field. PMID:23012533
ERPs evidence for the relationship between fluid intelligence and cognitive control.
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.
NASA Astrophysics Data System (ADS)
Rababaah, Haroun; Shirkhodaie, Amir
2009-04-01
The rapidly advancing hardware technology, smart sensors and sensor networks are advancing environment sensing. One major potential of this technology is Large-Scale Surveillance Systems (LS3) especially for, homeland security, battlefield intelligence, facility guarding and other civilian applications. The efficient and effective deployment of LS3 requires addressing number of aspects impacting the scalability of such systems. The scalability factors are related to: computation and memory utilization efficiency, communication bandwidth utilization, network topology (e.g., centralized, ad-hoc, hierarchical or hybrid), network communication protocol and data routing schemes; and local and global data/information fusion scheme for situational awareness. Although, many models have been proposed to address one aspect or another of these issues but, few have addressed the need for a multi-modality multi-agent data/information fusion that has characteristics satisfying the requirements of current and future intelligent sensors and sensor networks. In this paper, we have presented a novel scalable fusion engine for multi-modality multi-agent information fusion for LS3. The new fusion engine is based on a concept we call: Energy Logic. Experimental results of this work as compared to a Fuzzy logic model strongly supported the validity of the new model and inspired future directions for different levels of fusion and different applications.
Intellectual Production Supervision Perform based on RFID Smart Electricity Meter
NASA Astrophysics Data System (ADS)
Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng
2018-03-01
This topic develops the RFID intelligent electricity meter production supervision project management system. The system is designed for energy meter production supervision in the management of the project schedule, quality and cost information management requirements in RFID intelligent power, and provide quantitative information more comprehensive, timely and accurate for supervision engineer and project manager management decisions, and to provide technical information for the product manufacturing stage file. From the angle of scheme analysis, design, implementation and test, the system development of production supervision project management system for RFID smart meter project is discussed. Focus on the development of the system, combined with the main business application and management mode at this stage, focuses on the energy meter to monitor progress information, quality information and cost based information on RFID intelligent power management function. The paper introduces the design scheme of the system, the overall client / server architecture, client oriented graphical user interface universal, complete the supervision of project management and interactive transaction information display, the server system of realizing the main program. The system is programmed with C# language and.NET operating environment, and the client and server platforms use Windows operating system, and the database server software uses Oracle. The overall platform supports mainstream information and standards and has good scalability.
A Multi-dimensional Model for Vehicle Impact on Traffic Safety, Congestion, and Environment
DOT National Transportation Integrated Search
2012-01-01
The Intelligent Transportation System (ITS) has recently received great attention in the research : community. It offers a revolutionary vision of transportation, in which a full-scale : communication scheme between vehicles (V2V) and vehicles and in...
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.
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.
Cognitive Play and Mathematical Learning in Computer Microworlds.
ERIC Educational Resources Information Center
Steffe, Leslie P.; Wiegel, Heide G.
1994-01-01
Uses the constructivist principle of active learning to explore the possibly essential elements in transforming a cognitive play activity into mathematical activity. Suggests that for such transformation to occur, cognitive play activity must involve operations of intelligence that, yield situations of mathematical schemes. Illustrates the…
A Novel Certificateless Signature Scheme for Smart Objects in the Internet-of-Things.
Yeh, Kuo-Hui; Su, Chunhua; Choo, Kim-Kwang Raymond; Chiu, Wayne
2017-05-01
Rapid advances in wireless communications and pervasive computing technologies have resulted in increasing interest and popularity of Internet-of-Things (IoT) architecture, ubiquitously providing intelligence and convenience to our daily life. In IoT-based network environments, smart objects are embedded everywhere as ubiquitous things connected in a pervasive manner. Ensuring security for interactions between these smart things is significantly more important, and a topic of ongoing interest. In this paper, we present a certificateless signature scheme for smart objects in IoT-based pervasive computing environments. We evaluate the utility of the proposed scheme in IoT-oriented testbeds, i.e., Arduino Uno and Raspberry PI 2. Experiment results present the practicability of the proposed scheme. Moreover, we revisit the scheme of Wang et al. (2015) and revealed that a malicious super type I adversary can easily forge a legitimate signature to cheat any receiver as he/she wishes in the scheme. The superiority of the proposed certificateless signature scheme over relevant studies is demonstrated in terms of the summarized security and performance comparisons.
A Novel Certificateless Signature Scheme for Smart Objects in the Internet-of-Things
Yeh, Kuo-Hui; Su, Chunhua; Choo, Kim-Kwang Raymond; Chiu, Wayne
2017-01-01
Rapid advances in wireless communications and pervasive computing technologies have resulted in increasing interest and popularity of Internet-of-Things (IoT) architecture, ubiquitously providing intelligence and convenience to our daily life. In IoT-based network environments, smart objects are embedded everywhere as ubiquitous things connected in a pervasive manner. Ensuring security for interactions between these smart things is significantly more important, and a topic of ongoing interest. In this paper, we present a certificateless signature scheme for smart objects in IoT-based pervasive computing environments. We evaluate the utility of the proposed scheme in IoT-oriented testbeds, i.e., Arduino Uno and Raspberry PI 2. Experiment results present the practicability of the proposed scheme. Moreover, we revisit the scheme of Wang et al. (2015) and revealed that a malicious super type I adversary can easily forge a legitimate signature to cheat any receiver as he/she wishes in the scheme. The superiority of the proposed certificateless signature scheme over relevant studies is demonstrated in terms of the summarized security and performance comparisons. PMID:28468313
Visual Privacy by Context: Proposal and Evaluation of a Level-Based Visualisation Scheme
Padilla-López, José Ramón; Chaaraoui, Alexandros Andre; Gu, Feng; Flórez-Revuelta, Francisco
2015-01-01
Privacy in image and video data has become an important subject since cameras are being installed in an increasing number of public and private spaces. Specifically, in assisted living, intelligent monitoring based on computer vision can allow one to provide risk detection and support services that increase people's autonomy at home. In the present work, a level-based visualisation scheme is proposed to provide visual privacy when human intervention is necessary, such as at telerehabilitation and safety assessment applications. Visualisation levels are dynamically selected based on the previously modelled context. In this way, different levels of protection can be provided, maintaining the necessary intelligibility required for the applications. Furthermore, a case study of a living room, where a top-view camera is installed, is presented. Finally, the performed survey-based evaluation indicates the degree of protection provided by the different visualisation models, as well as the personal privacy preferences and valuations of the users. PMID:26053746
An intelligent robotic aid system for human services
NASA Technical Reports Server (NTRS)
Kawamura, K.; Bagchi, S.; Iskarous, M.; Pack, R. T.; Saad, A.
1994-01-01
The long term goal of our research at the Intelligent Robotic Laboratory at Vanderbilt University is to develop advanced intelligent robotic aid systems for human services. As a first step toward our goal, the current thrusts of our R&D are centered on the development of an intelligent robotic aid called the ISAC (Intelligent Soft Arm Control). In this paper, we describe the overall system architecture and current activities in intelligent control, adaptive/interactive control and task learning.
Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence
NASA Astrophysics Data System (ADS)
Muraleedharan, Rajani; Ye, Xiang; Osadciw, Lisa Ann
2008-04-01
Security in wireless sensor networks is typically sacrificed or kept minimal due to limited resources such as memory and battery power. Hence, the sensor nodes are prone to Denial-of-service attacks and detecting the threats is crucial in any application. In this paper, the Sybil attack is analyzed and a novel prediction method, combining Bayesian algorithm and Swarm Intelligence (SI) is proposed. Bayesian Networks (BN) is used in representing and reasoning problems, by modeling the elements of uncertainty. The decision from the BN is applied to SI forming an Hybrid Intelligence Scheme (HIS) to re-route the information and disconnecting the malicious nodes in future routes. A performance comparison based on the prediction using HIS vs. Ant System (AS) helps in prioritizing applications where decisions are time-critical.
DREAM: Classification scheme for dialog acts in clinical research query mediation.
Hoxha, Julia; Chandar, Praveen; He, Zhe; Cimino, James; Hanauer, David; Weng, Chunhua
2016-02-01
Clinical data access involves complex but opaque communication between medical researchers and query analysts. Understanding such communication is indispensable for designing intelligent human-machine dialog systems that automate query formulation. This study investigates email communication and proposes a novel scheme for classifying dialog acts in clinical research query mediation. We analyzed 315 email messages exchanged in the communication for 20 data requests obtained from three institutions. The messages were segmented into 1333 utterance units. Through a rigorous process, we developed a classification scheme and applied it for dialog act annotation of the extracted utterances. Evaluation results with high inter-annotator agreement demonstrate the reliability of this scheme. This dataset is used to contribute preliminary understanding of dialog acts distribution and conversation flow in this dialog space. Copyright © 2015 Elsevier Inc. All rights reserved.
Neural robust stabilization via event-triggering mechanism and adaptive learning technique.
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.
Learning and tuning fuzzy logic controllers through reinforcements
NASA Technical Reports Server (NTRS)
Berenji, Hamid R.; Khedkar, Pratap
1992-01-01
This paper presents a new method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system. In particular, our generalized approximate reasoning-based intelligent control (GARIC) architecture (1) learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; (2) introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; (3) introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and (4) learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward neural network, which can then adaptively improve performance by using gradient descent methods. We extend the AHC algorithm of Barto et al. (1983) to include the prior control knowledge of human operators. 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.
Control of fixed-wing UAV at levelling phase using artificial intelligence
NASA Astrophysics Data System (ADS)
Sayfeddine, Daher
2018-03-01
The increase in the share of fly-by-wire and software controlled UAV is explained by the need to release the human-operator and the desire to reduce the degree of influence of the human factor errors that account for 26% of aircraft accidents. An important reason for the introduction of new control algorithms is also the high level of UAV failures due loss of communication channels and possible hacking. This accounts for 17% of the total number of accidents. The comparison with manned flights shows that the frequency of accidents of unmanned flights is 27,000 times higher. This means that the UAV has 1611 failures per million flight hours and only 0.06 failures at the same time for the manned flight. In view of that, this paper studies the flight autonomy of fixed-wing UAV at the levelling phase. Landing parameters of the UAV are described. They will be used to setup a control scheme for an autopilot based on fuzzy logic algorithm.
NASA Astrophysics Data System (ADS)
Viswanath, Satish; Bloch, B. Nicholas; Chappelow, Jonathan; Patel, Pratik; Rofsky, Neil; Lenkinski, Robert; Genega, Elizabeth; Madabhushi, Anant
2011-03-01
Currently, there is significant interest in developing methods for quantitative integration of multi-parametric (structural, functional) imaging data with the objective of building automated meta-classifiers to improve disease detection, diagnosis, and prognosis. Such techniques are required to address the differences in dimensionalities and scales of individual protocols, while deriving an integrated multi-parametric data representation which best captures all disease-pertinent information available. In this paper, we present a scheme called Enhanced Multi-Protocol Analysis via Intelligent Supervised Embedding (EMPrAvISE); a powerful, generalizable framework applicable to a variety of domains for multi-parametric data representation and fusion. Our scheme utilizes an ensemble of embeddings (via dimensionality reduction, DR); thereby exploiting the variance amongst multiple uncorrelated embeddings in a manner similar to ensemble classifier schemes (e.g. Bagging, Boosting). We apply this framework to the problem of prostate cancer (CaP) detection on 12 3 Tesla pre-operative in vivo multi-parametric (T2-weighted, Dynamic Contrast Enhanced, and Diffusion-weighted) magnetic resonance imaging (MRI) studies, in turn comprising a total of 39 2D planar MR images. We first align the different imaging protocols via automated image registration, followed by quantification of image attributes from individual protocols. Multiple embeddings are generated from the resultant high-dimensional feature space which are then combined intelligently to yield a single stable solution. Our scheme is employed in conjunction with graph embedding (for DR) and probabilistic boosting trees (PBTs) to detect CaP on multi-parametric MRI. Finally, a probabilistic pairwise Markov Random Field algorithm is used to apply spatial constraints to the result of the PBT classifier, yielding a per-voxel classification of CaP presence. Per-voxel evaluation of detection results against ground truth for CaP extent on MRI (obtained by spatially registering pre-operative MRI with available whole-mount histological specimens) reveals that EMPrAvISE yields a statistically significant improvement (AUC=0.77) over classifiers constructed from individual protocols (AUC=0.62, 0.62, 0.65, for T2w, DCE, DWI respectively) as well as one trained using multi-parametric feature concatenation (AUC=0.67).
The Effectiveness of Clear Speech as a Masker
ERIC Educational Resources Information Center
Calandruccio, Lauren; Van Engen, Kristin; Dhar, Sumitrajit; Bradlow, Ann R.
2010-01-01
Purpose: It is established that speaking clearly is an effective means of enhancing intelligibility. Because any signal-processing scheme modeled after known acoustic-phonetic features of clear speech will likely affect both target and competing speech, it is important to understand how speech recognition is affected when a competing speech signal…
A flexible routing scheme for patients with topographical disorientation.
Torres-Solis, Jorge; Chau, Tom
2007-11-28
Individuals with topographical disorientation have difficulty navigating through indoor environments. Recent literature has suggested that ambient intelligence technologies may provide patients with navigational assistance through auditory or graphical instructions delivered via embedded devices. We describe an automatic routing engine for such an ambient intelligence system. The method routes patients with topographical disorientation through indoor environments by repeatedly computing the route of minimal cost from the current location of the patient to a specified destination. The cost of a given path not only reflects the physical distance between end points, but also incorporates individual patient abilities, the presence of mobility-impeding physical barriers within a building and the dynamic nature of the indoor environment. We demonstrate the method by routing simulated patients with either topographical disorientation or physical disabilities. Additionally, we exemplify the ability to route a patient from source to destination while taking into account changes to the building interior. When compared to a random walk, the proposed routing scheme offers potential cost-savings even when the patient follows only a subset of instructions. The routing method presented reduces the navigational effort for patients with topographical disorientation in indoor environments, accounting for physical abilities of the patient, environmental barriers and dynamic building changes. The routing algorithm and database proposed could be integrated into wearable and mobile platforms within the context of an ambient intelligence solution.
Smart Prosthetic Hand Technology - Phase 2
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
Adaptive power allocation schemes based on IAFS algorithm for OFDM-based cognitive radio systems
NASA Astrophysics Data System (ADS)
Zhang, Shuying; Zhao, Xiaohui; Liang, Cong; Ding, Xu
2017-01-01
In cognitive radio (CR) systems, reasonable power allocation can increase transmission rate of CR users or secondary users (SUs) as much as possible and at the same time insure normal communication among primary users (PUs). This study proposes an optimal power allocation scheme for the OFDM-based CR system with one SU influenced by multiple PU interference constraints. This scheme is based on an improved artificial fish swarm (IAFS) algorithm in combination with the advantage of conventional artificial fish swarm (ASF) algorithm and particle swarm optimisation (PSO) algorithm. In performance comparison of IAFS algorithm with other intelligent algorithms by simulations, the superiority of the IAFS algorithm is illustrated; this superiority results in better performance of our proposed scheme than that of the power allocation algorithms proposed by the previous studies in the same scenario. Furthermore, our proposed scheme can obtain higher transmission data rate under the multiple PU interference constraints and the total power constraint of SU than that of the other mentioned works.
Protection of autonomous microgrids using agent-based distributed communication
Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.
2016-04-06
This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less
An Enhanced Privacy-Preserving Authentication Scheme for Vehicle Sensor Networks.
Zhou, Yousheng; Zhao, Xiaofeng; Jiang, Yi; Shang, Fengjun; Deng, Shaojiang; Wang, Xiaojun
2017-12-08
Vehicle sensor networks (VSNs) are ushering in a promising future by enabling more intelligent transportation systems and providing a more efficient driving experience. However, because of their inherent openness, VSNs are subject to a large number of potential security threats. Although various authentication schemes have been proposed for addressing security problems, they are not suitable for VSN applications because of their high computation and communication costs. Chuang and Lee have developed a trust-extended authentication mechanism (TEAM) for vehicle-to-vehicle communication using a transitive trust relationship, which they claim can resist various attacks. However, it fails to counter internal attacks because of the utilization of a shared secret key. In this paper, to eliminate the vulnerability of TEAM, an enhanced privacy-preserving authentication scheme for VSNs is constructed. The security of our proposed scheme is proven under the random oracle model based on the assumption of the computational Diffie-Hellman problem.
Heuristic pattern correction scheme using adaptively trained generalized regression neural networks.
Hoya, T; Chambers, J A
2001-01-01
In many pattern classification problems, an intelligent neural system is required which can learn the newly encountered but misclassified patterns incrementally, while keeping a good classification performance over the past patterns stored in the network. In the paper, an heuristic pattern correction scheme is proposed using adaptively trained generalized regression neural networks (GRNNs). The scheme is based upon both network growing and dual-stage shrinking mechanisms. In the network growing phase, a subset of the misclassified patterns in each incoming data set is iteratively added into the network until all the patterns in the incoming data set are classified correctly. Then, the redundancy in the growing phase is removed in the dual-stage network shrinking. Both long- and short-term memory models are considered in the network shrinking, which are motivated from biological study of the brain. The learning capability of the proposed scheme is investigated through extensive simulation studies.
Efficient Secure and Privacy-Preserving Route Reporting Scheme for VANETs
NASA Astrophysics Data System (ADS)
Zhang, Yuanfei; Pei, Qianwen; Dai, Feifei; Zhang, Lei
2017-10-01
Vehicular ad-hoc network (VANET) is a core component of intelligent traffic management system which could provide various of applications such as accident prediction, route reporting, etc. Due to the problems caused by traffic congestion, route reporting becomes a prospective application which can help a driver to get optimal route to save her travel time. Before enjoying the convenience of route reporting, security and privacy-preserving issues need to be concerned. In this paper, we propose a new secure and privacy-preserving route reporting scheme for VANETs. In our scheme, only an authenticated vehicle can use the route reporting service provided by the traffic management center. Further, a vehicle may receive the response from the traffic management center with low latency and without violating the privacy of the vehicle. Experiment results show that our scheme is much more efficiency than the existing one.
An Enhanced Privacy-Preserving Authentication Scheme for Vehicle Sensor Networks
Zhou, Yousheng; Zhao, Xiaofeng; Jiang, Yi; Shang, Fengjun; Deng, Shaojiang; Wang, Xiaojun
2017-01-01
Vehicle sensor networks (VSNs) are ushering in a promising future by enabling more intelligent transportation systems and providing a more efficient driving experience. However, because of their inherent openness, VSNs are subject to a large number of potential security threats. Although various authentication schemes have been proposed for addressing security problems, they are not suitable for VSN applications because of their high computation and communication costs. Chuang and Lee have developed a trust-extended authentication mechanism (TEAM) for vehicle-to-vehicle communication using a transitive trust relationship, which they claim can resist various attacks. However, it fails to counter internal attacks because of the utilization of a shared secret key. In this paper, to eliminate the vulnerability of TEAM, an enhanced privacy-preserving authentication scheme for VSNs is constructed. The security of our proposed scheme is proven under the random oracle model based on the assumption of the computational Diffie–Hellman problem. PMID:29292792
Protection of autonomous microgrids using agent-based distributed communication
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.
This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less
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.
Intelligent systems for the autonomous exploration of Titan and Enceladus
NASA Astrophysics Data System (ADS)
Furfaro, Roberto; Lunine, Jonathan I.; Kargel, Jeffrey S.; Fink, Wolfgang
2008-04-01
Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.
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.
Intelligent Signal Processing for Active Control
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.
Treml, Benjamin; Gillman, Andrew; Buskohl, Philip; Vaia, Richard
2018-06-18
Robots autonomously interact with their environment through a continual sense-decide-respond control loop. Most commonly, the decide step occurs in a central processing unit; however, the stiffness mismatch between rigid electronics and the compliant bodies of soft robots can impede integration of these systems. We develop a framework for programmable mechanical computation embedded into the structure of soft robots that can augment conventional digital electronic control schemes. Using an origami waterbomb as an experimental platform, we demonstrate a 1-bit mechanical storage device that writes, erases, and rewrites itself in response to a time-varying environmental signal. Further, we show that mechanical coupling between connected origami units can be used to program the behavior of a mechanical bit, produce logic gates such as AND, OR, and three input majority gates, and transmit signals between mechanologic gates. Embedded mechanologic provides a route to add autonomy and intelligence in soft robots and machines. Copyright © 2018 the Author(s). Published by PNAS.
Biosensors with Built-In Biomolecular Logic Gates for Practical Applications
Lai, Yu-Hsuan; Sun, Sin-Cih; Chuang, Min-Chieh
2014-01-01
Molecular logic gates, designs constructed with biological and chemical molecules, have emerged as an alternative computing approach to silicon-based logic operations. These molecular computers are capable of receiving and integrating multiple stimuli of biochemical significance to generate a definitive output, opening a new research avenue to advanced diagnostics and therapeutics which demand handling of complex factors and precise control. In molecularly gated devices, Boolean logic computations can be activated by specific inputs and accurately processed via bio-recognition, bio-catalysis, and selective chemical reactions. In this review, we survey recent advances of the molecular logic approaches to practical applications of biosensors, including designs constructed with proteins, enzymes, nucleic acids, nanomaterials, and organic compounds, as well as the research avenues for future development of digitally operating “sense and act” schemes that logically process biochemical signals through networked circuits to implement intelligent control systems. PMID:25587423
Lateral polarity control of III-nitride thin film and application in GaN Schottky barrier diode
NASA Astrophysics Data System (ADS)
Li, Junmei; Guo, Wei; Sheikhi, Moheb; Li, Hongwei; Bo, Baoxue; Ye, Jichun
2018-05-01
N-polar and III-polar GaN and AlN epitaxial thin films grown side by side on single sapphire substrate was reported. Surface morphology, wet etching susceptibility and bi-axial strain conditions were investigated and the polarity control scheme was utilized in the fabrication of Schottky barrier diode where ohmic contact and Schottky contact were deposited on N-polar domains and Ga-polar domains, respectively. The influence of N-polarity on on-state resistivity and I–V characteristic was discussed, demonstrating that lateral polarity structure of GaN and AlN can be widely used in new designs of optoelectronic and electronic devices. Project partially supported by the National Key Research and Development Program of China (No. 2016YFB0400802), the National Natural Science Foundation of China (No. 61704176), and the Open project of Zhejiang Key Laboratory for Advanced Microelectronic Intelligent Systems and Applications (No. ZJUAMIS1704).
Ensemble learning in fixed expansion layer networks for mitigating catastrophic forgetting.
Coop, Robert; Mishtal, Aaron; Arel, Itamar
2013-10-01
Catastrophic forgetting is a well-studied attribute of most parameterized supervised learning systems. A variation of this phenomenon, in the context of feedforward neural networks, arises when nonstationary inputs lead to loss of previously learned mappings. The majority of the schemes proposed in the literature for mitigating catastrophic forgetting were not data driven and did not scale well. We introduce the fixed expansion layer (FEL) feedforward neural network, which embeds a sparsely encoding hidden layer to help mitigate forgetting of prior learned representations. In addition, we investigate a novel framework for training ensembles of FEL networks, based on exploiting an information-theoretic measure of diversity between FEL learners, to further control undesired plasticity. The proposed methodology is demonstrated on a basic classification task, clearly emphasizing its advantages over existing techniques. The architecture proposed can be enhanced to address a range of computational intelligence tasks, such as regression problems and system control.
NASA Astrophysics Data System (ADS)
Costoiu, M.; Ioana, A.; Semenescu, A.; Marcu, D.
2016-11-01
The article presents the main advantages of electric arc furnace (EAF): it has a great contribution to reintroduce significant quantities of reusable metallic materials in the economic circuit, it constitutes itself as an important part in the Primary Materials and Energy Recovery (PMER), good productivity, good quality / price ratio, the possibility of developing a wide variety of classes and types of steels, including special steels and high alloy. In this paper it is presented some important developments of electric arc furnace: vacuum electric arc furnace, artificial intelligence expert systems for pollution control Steelworks. Another important aspect presented in the article is an original block diagram for optimization the EAF management system. This scheme is based on the original objective function (criterion function) represented by the price / quality ratio. The article presents an original block diagram for optimization the control system of the EAF. For designing this concept of EAF management system, many principles were used.
NASA Astrophysics Data System (ADS)
Meier, E.; Biedron, S. G.; LeBlanc, G.; Morgan, M. J.
2011-03-01
This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI@Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.
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...
Abdelkarim, Noha; Mohamed, Amr E; El-Garhy, Ahmed M; Dorrah, Hassen T
2016-01-01
The two-coupled distillation column process is a physically complicated system in many aspects. Specifically, the nested interrelationship between system inputs and outputs constitutes one of the significant challenges in system control design. Mostly, such a process is to be decoupled into several input/output pairings (loops), so that a single controller can be assigned for each loop. In the frame of this research, the Brain Emotional Learning Based Intelligent Controller (BELBIC) forms the control structure for each decoupled loop. The paper's main objective is to develop a parameterization technique for decoupling and control schemes, which ensures robust control behavior. In this regard, the novel optimization technique Bacterial Swarm Optimization (BSO) is utilized for the minimization of summation of the integral time-weighted squared errors (ITSEs) for all control loops. This optimization technique constitutes a hybrid between two techniques, which are the Particle Swarm and Bacterial Foraging algorithms. According to the simulation results, this hybridized technique ensures low mathematical burdens and high decoupling and control accuracy. Moreover, the behavior analysis of the proposed BELBIC shows a remarkable improvement in the time domain behavior and robustness over the conventional PID controller.
Mohamed, Amr E.; Dorrah, Hassen T.
2016-01-01
The two-coupled distillation column process is a physically complicated system in many aspects. Specifically, the nested interrelationship between system inputs and outputs constitutes one of the significant challenges in system control design. Mostly, such a process is to be decoupled into several input/output pairings (loops), so that a single controller can be assigned for each loop. In the frame of this research, the Brain Emotional Learning Based Intelligent Controller (BELBIC) forms the control structure for each decoupled loop. The paper's main objective is to develop a parameterization technique for decoupling and control schemes, which ensures robust control behavior. In this regard, the novel optimization technique Bacterial Swarm Optimization (BSO) is utilized for the minimization of summation of the integral time-weighted squared errors (ITSEs) for all control loops. This optimization technique constitutes a hybrid between two techniques, which are the Particle Swarm and Bacterial Foraging algorithms. According to the simulation results, this hybridized technique ensures low mathematical burdens and high decoupling and control accuracy. Moreover, the behavior analysis of the proposed BELBIC shows a remarkable improvement in the time domain behavior and robustness over the conventional PID controller. PMID:27807444
Automatic background updating for video-based vehicle detection
NASA Astrophysics Data System (ADS)
Hu, Chunhai; Li, Dongmei; Liu, Jichuan
2008-03-01
Video-based vehicle detection is one of the most valuable techniques for the Intelligent Transportation System (ITS). The widely used video-based vehicle detection technique is the background subtraction method. The key problem of this method is how to subtract and update the background effectively. In this paper an efficient background updating scheme based on Zone-Distribution for vehicle detection is proposed to resolve the problems caused by sudden camera perturbation, sudden or gradual illumination change and the sleeping person problem. The proposed scheme is robust and fast enough to satisfy the real-time constraints of vehicle detection.
Application of the GA-BP Neural Network in Earthwork Calculation
NASA Astrophysics Data System (ADS)
Fang, Peng; Cai, Zhixiong; Zhang, Ping
2018-01-01
The calculation of earthwork quantity is the key factor to determine the project cost estimate and the optimization of the scheme. It is of great significance and function in the excavation of earth and rock works. We use optimization principle of GA-BP intelligent algorithm running process, and on the basis of earthwork quantity and cost information database, the design of the GA-BP neural network intelligent computing model, through the network training and learning, the accuracy of the results meet the actual engineering construction of gauge fan requirements, it provides a new approach for other projects the calculation, and has good popularization value.
NASA Astrophysics Data System (ADS)
Low, Kerwin; Elhadidi, Basman; Glauser, Mark
2009-11-01
Understanding the different noise production mechanisms caused by the free shear flows in a turbulent jet flow provides insight to improve ``intelligent'' feedback mechanisms to control the noise. Towards this effort, a control scheme is based on feedback of azimuthal pressure measurements in the near field of the jet at two streamwise locations. Previous studies suggested that noise reduction can be achieved by azimuthal actuators perturbing the shear layer at the jet lip. The closed-loop actuation will be based on a low-dimensional Fourier representation of the hydrodynamic pressure measurements. Preliminary results show that control authority and reduction in the overall sound pressure level was possible. These results provide motivation to move forward with the overall vision of developing innovative multi-mode sensing methods to improve state estimation and derive dynamical systems. It is envisioned that estimating velocity-field and dynamic pressure information from various locations both local and in the far-field regions, sensor fusion techniques can be utilized to ascertain greater overall control authority.
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.
Matrix Completion Optimization for Localization in Wireless Sensor Networks for Intelligent IoT
Nguyen, Thu L. N.; Shin, Yoan
2016-01-01
Localization in wireless sensor networks (WSNs) is one of the primary functions of the intelligent Internet of Things (IoT) that offers automatically discoverable services, while the localization accuracy is a key issue to evaluate the quality of those services. In this paper, we develop a framework to solve the Euclidean distance matrix completion problem, which is an important technical problem for distance-based localization in WSNs. The sensor network localization problem is described as a low-rank dimensional Euclidean distance completion problem with known nodes. The task is to find the sensor locations through recovery of missing entries of a squared distance matrix when the dimension of the data is small compared to the number of data points. We solve a relaxation optimization problem using a modification of Newton’s method, where the cost function depends on the squared distance matrix. The solution obtained in our scheme achieves a lower complexity and can perform better if we use it as an initial guess for an interactive local search of other higher precision localization scheme. Simulation results show the effectiveness of our approach. PMID:27213378
Intelligent voltage control strategy for three-phase UPS inverters with output LC filter
NASA Astrophysics Data System (ADS)
Jung, J. W.; Leu, V. Q.; Dang, D. Q.; Do, T. D.; Mwasilu, F.; Choi, H. H.
2015-08-01
This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.
Classification of extraterrestrial civilizations
NASA Astrophysics Data System (ADS)
Tang, Tong B.; Chang, Grace
1991-06-01
A scheme of classification of extraterrestrial intelligence (ETI) communities based on the scope of energy accessible to the civilization in question is proposed as an alternative to the Kardeshev (1964) scheme that includes three types of civilization, as determined by their levels of energy expenditure. The proposed scheme includes six classes: (1) a civilization that runs essentially on energy exerted by individual beings or by domesticated lower life forms, (2) harnessing of natural sources on planetary surface with artificial constructions, like water wheels and wind sails, (3) energy from fossils and fissionable isotopes, mined beneath the planet surface, (4) exploitation of nuclear fusion on a large scale, whether on the planet, in space, or from primary solar energy, (5) extensive use of antimatter for energy storage, and (6) energy from spacetime, perhaps via the action of naked singularities.
NASA Astrophysics Data System (ADS)
Gao, Tao; Wulan, Wulan; Yu, Xiao; Yang, Zelong; Gao, Jing; Hua, Weiqi; Yang, Peng; Si, Yaobing
2018-05-01
Spring precipitation is the predominant factor that controls meteorological drought in Inner Mongolia (IM), China. This study used the anomaly percentage of spring precipitation (PAP) as a drought index to measure spring drought. A scheme for forecasting seasonal drought was designed based on evidence of spring drought occurrence and speculative reasoning methods introduced in computer artificial intelligence theory. Forecast signals with sufficient lead-time for predictions of spring drought were extracted from eight crucial areas of oceans and 500-hPa geopotential height. Using standardized values, these signals were synthesized into three examples of spring drought evidence (SDE) depending on their primary effects on three major atmospheric circulation components of spring precipitation in IM: the western Pacific subtropical high, North Polar vortex, and East Asian trough. Thresholds for the SDE were determined following numerical analyses of the influential factors. Furthermore, five logical reasoning rules for distinguishing the occurrence of SDE were designed after examining all possible combined cases. The degree of confidence in the rules was determined based on estimations of their prior probabilities. Then, an optimized logical reasoning scheme was identified for judging the possibility of spring drought. The scheme was successful in hindcast predictions of 11 of the 16 (accuracy: 68.8%) spring droughts that have occurred during 1960-2009. Moreover, the accuracy ratio for the same period was 82.0% for drought (PAP ≤ -20%) or not (PAP > -20%). Predictions for the recent 6-year period (2010-2015) demonstrated successful outcomes.
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
Synthetic biology routes to bio-artificial intelligence
Zaikin, Alexey; Saka, Yasushi; Romano, M. Carmen; Giuraniuc, Claudiu V.; Kanakov, Oleg; Laptyeva, Tetyana
2016-01-01
The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular ‘teachers’ and ‘students’ is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). PMID:27903825
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.
Intelligent flight control systems
NASA Technical Reports Server (NTRS)
Stengel, Robert F.
1993-01-01
The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.
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.
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
Janke, Katrin; Driessen, Martin; Behnia, Behnoush; Wingenfeld, Katja; Roepke, Stefan
2018-06-01
Emotional intelligence as a part of social cognition has, to our knowledge, never been investigated in patients with Posttraumatic Stress Disorder (PTSD), though the disorder is characterized by aspects of emotional dysfunctioning. PTSD often occurs with Borderline Personality Disorder (BPD) as a common comorbidity. Studies about social cognition and emotional intelligence in patients with BPD propose aberrant social cognition, but produced inconsistent results regarding emotional intelligence. The present study aims to assess emotional intelligence in patients with PTSD without comorbid BPD, PTSD with comorbid BPD, and BPD patients without comorbid PTSD, as well as in healthy controls. 71 patients with PTSD (41 patients with PTSD without comorbid BPD, 30 patients with PTSD with comorbid BPD), 56 patients with BPD without PTSD, and 63 healthy controls filled in the Test of Emotional Intelligence (TEMINT). Patients with PTSD without comorbid BPD showed impairments in emotional intelligence compared to patients with BPD without PTSD, and compared to healthy controls. These impairments were not restricted to specific emotions. Patients with BPD did not differ significantly from healthy controls. This study provides evidence for an impaired emotional intelligence in PTSD without comorbid BPD compared to BPD and healthy controls, affecting a wide range of emotions. Copyright © 2018 Elsevier B.V. All rights reserved.
Hey, Matthias; Hocke, Thomas; Mauger, Stefan; Müller-Deile, Joachim
2016-11-01
Individual speech intelligibility was measured in quiet and noise for cochlear Implant recipients upgrading from the Freedom to the CP900 series sound processor. The postlingually deafened participants (n = 23) used either Nucleus CI24RE or CI512 cochlear implant, and currently wore a Freedom sound processor. A significant group mean improvement in speech intelligibility was found in quiet (Freiburg monosyllabic words at 50 dB SPL ) and in noise (adaptive Oldenburger sentences in noise) for the two CP900 series SmartSound programs compared to the Freedom program. Further analysis was carried out on individual's speech intelligibility outcomes in quiet and in noise. Results showed a significant improvement or decrement for some recipients when upgrading to the new programs. To further increase speech intelligibility outcomes when upgrading, an enhanced upgrade procedure is proposed that includes additional testing with different signal-processing schemes. Implications of this research are that future automated scene analysis and switching technologies could provide additional performance improvements by introducing individualized scene-dependent settings.
Yu, Chunshui; Li, Jun; Liu, Yong; Qin, Wen; Li, Yonghui; Shu, Ni; Jiang, Tianzi; Li, Kuncheng
2008-05-01
It is well known that brain structures correlate with intelligence but the association between the integrity of brain white matter tracts and intelligence in patients with mental retardation (MR) and healthy adults remains unknown. The aims of this study are to investigate whether the integrity of corpus callosum (CC), cingulum, uncinate fasciculus (UF), optic radiation (OR) and corticospinal tract (CST) are damaged in patients with MR, and to determine the correlations between the integrity of these tracts and full scale intelligence quotient (FSIQ) in both patients and controls. Fifteen MR patients and 79 healthy controls underwent intelligence tests and diffusion tensor imaging examinations. According to the FSIQ, all healthy controls were divided into general intelligence (GI: FSIQ<120; n=42) and high intelligence (HI: FSIQ> or =120; n=37) groups. Intelligence was assessed by Chinese Revised Wechsler Adult Intelligence Scale, and white matter tract integrity was assessed by fractional anisotropy (FA). MR patients showed significantly lower FA than healthy controls in the CC, UF, OR and CST. However, GI subjects only demonstrated lower FA than HI subjects in the right UF. Partial correlation analysis controlling for age and sex showed that FSIQ scores were significantly correlated with the FA of the bilateral UF, genu and truncus of CC, bilateral OR and left CST. While FSIQ scores were only significantly correlated with the FA of the right UF when further controlling for group. This study indicate that MR patients show extensive damage in the integrity of the brain white matter tracts, and the right UF is an important neural basis of human intelligence.
Intelligent Traffic Light Based on PLC Control
NASA Astrophysics Data System (ADS)
Mei, Lin; Zhang, Lijian; Wang, Lingling
2017-11-01
The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.
Cheng, George Shu-Xing; Mulkey, Steven L; Wang, Qiang; Chow, Andrew J
2013-11-26
A method and apparatus for intelligently controlling continuous process variables. A Dream Controller comprises an Intelligent Engine mechanism and a number of Model-Free Adaptive (MFA) controllers, each of which is suitable to control a process with specific behaviors. The Intelligent Engine can automatically select the appropriate MFA controller and its parameters so that the Dream Controller can be easily used by people with limited control experience and those who do not have the time to commission, tune, and maintain automatic controllers.
Advanced Protection & Service Restoration for FREEDM Systems
NASA Astrophysics Data System (ADS)
Singh, Urvir
A smart electric power distribution system (FREEDM system) that incorporates DERs (Distributed Energy Resources), SSTs (Solid State Transformers - that can limit the fault current to two times of the rated current) & RSC (Reliable & Secure Communication) capabilities has been studied in this work in order to develop its appropriate protection & service restoration techniques. First, a solution is proposed that can make conventional protective devices be able to provide effective protection for FREEDM systems. Results show that although this scheme can provide required protection but it can be quite slow. Using the FREEDM system's communication capabilities, a communication assisted Overcurrent (O/C) protection scheme is proposed & results show that by using communication (blocking signals) very fast operating times are achieved thereby, mitigating the problem of conventional O/C scheme. Using the FREEDM System's DGI (Distributed Grid Intelligence) capability, an automated FLISR (Fault Location, Isolation & Service Restoration) scheme is proposed that is based on the concept of 'software agents' & uses lesser data (than conventional centralized approaches). Test results illustrated that this scheme is able to provide a global optimal system reconfiguration for service restoration.
From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks
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.
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.
Parallel Logic Programming Architecture
1990-04-01
Section 3.1. 3.1. A STATIC ALLOCATION SCHEME (SAS) Methods that have been used for decomposing distributed problems in artificial intelligence...multiple agents, knowledge organization and allocation, and cooperative parallel execution. These difficulties are common to distributed artificial ...for the following reasons. First, intellegent backtracking requires much more bookkeeping and is therefore more costly during consult-time and during
TOWARDS MEASURES OF INTELLIGENCE BASED ON SEMIOTIC CONTROL
DOE Office of Scientific and Technical Information (OSTI.GOV)
C. JOSLYN
2000-08-01
We address the question of how to identify and measure the degree of intelligence in systems. We define the presence of intelligence as equivalent to the presence of a control relation. We contrast the distinct atomic semioic definitions of models and controls, and discuss hierarchical and anticipatory control. We conclude with a suggestion about moving towards quantitative measures of the degree of such control in systems.
The application of intelligent process control to space based systems
NASA Technical Reports Server (NTRS)
Wakefield, G. Steve
1990-01-01
The application of Artificial Intelligence to electronic and process control can help attain the autonomy and safety requirements of manned space systems. An overview of documented applications within various industries is presented. The development process is discussed along with associated issues for implementing an intelligence process control system.
Numerical simulation of intelligent compaction technology for construction quality control.
DOT National Transportation Integrated Search
2014-12-01
Intelligent compaction (IC) technique is a fast-developing technology for compaction quality control and acceptance. Proof rolling using the intelligent compaction rollers after completing compaction can eectively identify : the weak spots and sig...
Artificial intelligence in robot control systems
NASA Astrophysics Data System (ADS)
Korikov, A.
2018-05-01
This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.
NASA Astrophysics Data System (ADS)
Alkan, Hilal; Balkaya, Çağlayan
2018-02-01
We present an efficient inversion tool for parameter estimation from horizontal loop electromagnetic (HLEM) data using Differential Search Algorithm (DSA) which is a swarm-intelligence-based metaheuristic proposed recently. The depth, dip, and origin of a thin subsurface conductor causing the anomaly are the parameters estimated by the HLEM method commonly known as Slingram. The applicability of the developed scheme was firstly tested on two synthetically generated anomalies with and without noise content. Two control parameters affecting the convergence characteristic to the solution of the algorithm were tuned for the so-called anomalies including one and two conductive bodies, respectively. Tuned control parameters yielded more successful statistical results compared to widely used parameter couples in DSA applications. Two field anomalies measured over a dipping graphitic shale from Northern Australia were then considered, and the algorithm provided the depth estimations being in good agreement with those of previous studies and drilling information. Furthermore, the efficiency and reliability of the results obtained were investigated via probability density function. Considering the results obtained, we can conclude that DSA characterized by the simple algorithmic structure is an efficient and promising metaheuristic for the other relatively low-dimensional geophysical inverse problems. Finally, the researchers after being familiar with the content of developed scheme displaying an easy to use and flexible characteristic can easily modify and expand it for their scientific optimization problems.
Entanglement-Gradient Routing for Quantum Networks.
Gyongyosi, Laszlo; Imre, Sandor
2017-10-27
We define the entanglement-gradient routing scheme for quantum repeater networks. The routing framework fuses the fundamentals of swarm intelligence and quantum Shannon theory. Swarm intelligence provides nature-inspired solutions for problem solving. Motivated by models of social insect behavior, the routing is performed using parallel threads to determine the shortest path via the entanglement gradient coefficient, which describes the feasibility of the entangled links and paths of the network. The routing metrics are derived from the characteristics of entanglement transmission and relevant measures of entanglement distribution in quantum networks. The method allows a moderate complexity decentralized routing in quantum repeater networks. The results can be applied in experimental quantum networking, future quantum Internet, and long-distance quantum communications.
An Intelligent Fingerprint-Biometric Image Scrambling Scheme
NASA Astrophysics Data System (ADS)
Khan, Muhammad Khurram; Zhang, Jiashu
To obstruct the attacks, and to hamper with the liveness and retransmission issues of biometrics images, we have researched on the challenge/response-based biometrics scrambled image transmission. We proposed an intelligent biometrics sensor, which has computational power to receive challenges from the authentication server and generate response against the challenge with the encrypted biometric image. We utilized the FRT for biometric image encryption and used its scaling factors and random phase mask as the additional secret keys. In addition, we chaotically generated the random phase masks by a chaotic map to further improve the encryption security. Experimental and simulation results have shown that the presented system is secure, robust, and deters the risks of attacks of biometrics image transmission.
The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.
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
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
Namasivayam, Aravind Kumar; Pukonen, Margit; Goshulak, Debra; Yu, Vickie Y; Kadis, Darren S; Kroll, Robert; Pang, Elizabeth W; De Nil, Luc F
2013-01-01
The current study was undertaken to investigate the impact of speech motor issues on the speech intelligibility of children with moderate to severe speech sound disorders (SSD) within the context of the PROMPT intervention approach. The word-level Children's Speech Intelligibility Measure (CSIM), the sentence-level Beginner's Intelligibility Test (BIT) and tests of speech motor control and articulation proficiency were administered to 12 children (3:11 to 6:7 years) before and after PROMPT therapy. PROMPT treatment was provided for 45 min twice a week for 8 weeks. Twenty-four naïve adult listeners aged 22-46 years judged the intelligibility of the words and sentences. For CSIM, each time a recorded word was played to the listeners they were asked to look at a list of 12 words (multiple-choice format) and circle the word while for BIT sentences, the listeners were asked to write down everything they heard. Words correctly circled (CSIM) or transcribed (BIT) were averaged across three naïve judges to calculate percentage speech intelligibility. Speech intelligibility at both the word and sentence level was significantly correlated with speech motor control, but not articulatory proficiency. Further, the severity of speech motor planning and sequencing issues may potentially be a limiting factor in connected speech intelligibility and highlights the need to target these issues early and directly in treatment. The reader will be able to: (1) outline the advantages and disadvantages of using word- and sentence-level speech intelligibility tests; (2) describe the impact of speech motor control and articulatory proficiency on speech intelligibility; and (3) describe how speech motor control and speech intelligibility data may provide critical information to aid treatment planning. Copyright © 2013 Elsevier Inc. All rights reserved.
Artificial intelligent techniques for optimizing water allocation in a reservoir watershed
NASA Astrophysics Data System (ADS)
Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung
2014-05-01
This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.
[Intelligence level and intelligence structure of children with primary nocturnal enuresis].
Dai, Xiao-Mei; Ma, Hong-Wei; Pan, Xue-Xia
2007-10-01
Some research has shown that there may be memory/caution (M/C) defects in children with primary nocturnal enuresis (PNE). This study aimed to investigate whether the defects affect the intelligence level and the intelligence structure in PNE children. Intelligence tests were performed by means of Wechsler Young Children Scales of Intelligence (C-WISC) in 40 children with PNE and 40 age-matched normal children. The full intelligence quotient (FIQ), verbal IQ (VIQ) and performances IQ (PIQ) in the PNE group were in a normal range and did not different from the control group. There were significant differences in the scores for digit extent, decipher, knowledge and arithmetics between the PNE and the control groups (P < 0.05). M/C factor in the PNE group was statistically lower than in the control group (93.44 +/-11.27 vs 100.03 +/-11.79; P < 0.05). The total intelligence level of children with PNE was normal, but the M/C factor in the intelligence structure had some defects, suggesting that PNE may be related to the abnormity of executive function in the frontal lobe.
Intelligent open-architecture controller using knowledge server
NASA Astrophysics Data System (ADS)
Nacsa, Janos; Kovacs, George L.; Haidegger, Geza
2001-12-01
In an ideal scenario of intelligent machine tools [22] the human mechanist was almost replaced by the controller. During the last decade many efforts have been made to get closer to this ideal scenario, but the way of information processing within the CNC did not change too much. The paper summarizes the requirements of an intelligent CNC evaluating the different research efforts done in this field using different artificial intelligence (AI) methods. The need for open CNC architecture was emerging at many places around the world. The second part of the paper introduces and shortly compares these efforts. In the third part a low cost concept for intelligent and open systems named Knowledge Server for Controllers (KSC) is introduced. It allows more devices to solve their intelligent processing needs using the same server that is capable to process intelligent data. In the final part the KSC concept is used in an open CNC environment to build up some elements of an intelligent CNC. The preliminary results of the implementation are also introduced.
Implementation of Integrated System Fault Management Capability
NASA Technical Reports Server (NTRS)
Figueroa, Fernando; Schmalzel, John; Morris, Jon; Smith, Harvey; Turowski, Mark
2008-01-01
Fault Management to support rocket engine test mission with highly reliable and accurate measurements; while improving availability and lifecycle costs. CORE ELEMENTS: Architecture, taxonomy, and ontology (ATO) for DIaK management. Intelligent Sensor Processes; Intelligent Element Processes; Intelligent Controllers; Intelligent Subsystem Processes; Intelligent System Processes; Intelligent Component Processes.
SDN-Enabled Dynamic Feedback Control and Sensing in Agile Optical Networks
NASA Astrophysics Data System (ADS)
Lin, Likun
Fiber optic networks are no longer just pipelines for transporting data in the long haul backbone. Exponential growth in traffic in metro-regional areas has pushed higher capacity fiber toward the edge of the network, and highly dynamic patterns of heterogeneous traffic have emerged that are often bursty, severely stressing the historical "fat and dumb pipe" static optical network, which would need to be massively over-provisioned to deal with these loads. What is required is a more intelligent network with a span of control over the optical as well as electrical transport mechanisms which enables handling of service requests in a fast and efficient way that guarantees quality of service (QoS) while optimizing capacity efficiency. An "agile" optical network is a reconfigurable optical network comprised of high speed intelligent control system fed by real-time in situ network sensing. It provides fast response in the control and switching of optical signals in response to changing traffic demands and network conditions. This agile control of optical signals is enabled by pushing switching decisions downward in the network stack to the physical layer. Implementing such agility is challenging due to the response dynamics and interactions of signals in the physical layer. Control schemes must deal with issues such as dynamic power equalization, EDFA transients and cascaded noise effects, impairments due to self-phase modulation and dispersion, and channel-to-channel cross talk. If these issues are not properly predicted and mitigated, attempts at dynamic control can drive the optical network into an unstable state. In order to enable high speed actuation of signal modulators and switches, the network controller must be able to make decisions based on predictive models. In this thesis, we consider how to take advantage of Software Defined Networking (SDN) capabilities for network reconfiguration, combined with embedded models that access updates from deployed network monitoring sensors. In order to maintain signal quality while optimizing network resources, we find that it is essential to model and update estimates of the physical link impairments in real-time. In this thesis, we consider the key elements required to enable an agile optical network, with contributions as follows: • Control Framework: extended the SDN concept to include the optical transport network through extensions to the OpenFlow (OF) protocol. A unified SDN control plane is built to facilitate control and management capability across the electrical/packet-switched and optical/circuit-switched portions of the network seamlessly. The SDN control plane serves as a platform to abstract the resources of multilayer/multivendor networks. Through this platform, applications can dynamically request the network resources to meet their service requirements. • Use of In-situ Monitors: enabled real-time physical impairment sensing in the control plane using in-situ Optical Performance Monitoring (OPM) and bit error rate (BER) analyzers. OPM and BER values are used as quantitative indicators of the link status and are fed to the control plane through a high-speed data collection interface to form a closed-loop feedback system to enable adaptive resource allocation. • Predictive Network Model: used a network model embedded in the control layer to study the link status. The estimated results of network status is fed into the control decisions to precompute the network resources. The performance of the network model can be enhanced by the sensing results. • Real-Time Control Algorithms: investigated various dynamic resource allocation mechanisms supporting an agile optical network. Intelligent routing and wavelength switching for recovering from traffic impairments is achieved experimentally in the agile optical network within one second. A distance-adaptive spectrum allocation scheme to address transmission impairments caused by cascaded Wavelength Selective Switches (WSS) is proposed and evaluated for improving network spectral efficiency.
A novel control algorithm for interaction between surface waves and a permeable floating structure
NASA Astrophysics Data System (ADS)
Tsai, Pei-Wei; Alsaedi, A.; Hayat, T.; Chen, Cheng-Wu
2016-04-01
An analytical solution is undertaken to describe the wave-induced flow field and the surge motion of a permeable platform structure with fuzzy controllers in an oceanic environment. In the design procedure of the controller, a parallel distributed compensation (PDC) scheme is utilized to construct a global fuzzy logic controller by blending all local state feedback controllers. A stability analysis is carried out for a real structure system by using Lyapunov method. The corresponding boundary value problems are then incorporated into scattering and radiation problems. They are analytically solved, based on separation of variables, to obtain series solutions in terms of the harmonic incident wave motion and surge motion. The dependence of the wave-induced flow field and its resonant frequency on wave characteristics and structure properties including platform width, thickness and mass has been thus drawn with a parametric approach. From which mathematical models are applied for the wave-induced displacement of the surge motion. A nonlinearly inverted pendulum system is employed to demonstrate that the controller tuned by swarm intelligence method can not only stabilize the nonlinear system, but has the robustness against external disturbance.
Intelligent Control Approaches for Aircraft Applications
NASA Technical Reports Server (NTRS)
Gundy-Burlet, Karen; KrishnaKumar, K.; Soloway, Don; Kaneshige, John; Clancy, Daniel (Technical Monitor)
2001-01-01
This paper presents an overview of various intelligent control technologies currently being developed and studied under the Intelligent Flight Control (IFC) program at the NASA Ames Research Center. The main objective of the intelligent flight control program is to develop the next generation of flight controllers for the purpose of automatically compensating for a broad spectrum of damaged or malfunctioning aircraft components and to reduce control law development cost and time. The approaches being examined include: (a) direct adaptive dynamic inverse controller and (b) an adaptive critic-based dynamic inverse controller. These approaches can utilize, but do not require, fault detection and isolation information. Piloted simulation studies are performed to examine if the intelligent flight control techniques adequately: 1) Match flying qualities of modern fly-by-wire flight controllers under nominal conditions; 2) Improve performance under failure conditions when sufficient control authority is available; and 3) Achieve consistent handling qualities across the flight envelope and for different aircraft configurations. Results obtained so far demonstrate the potential for improving handling qualities and significantly increasing survivability rates under various simulated failure conditions.
An Emergency Packet Forwarding Scheme for V2V Communication Networks
2014-01-01
This paper proposes an effective warning message forwarding scheme for cooperative collision avoidance. In an emergency situation, an emergency-detecting vehicle warns the neighbor vehicles via an emergency warning message. Since the transmission range is limited, the warning message is broadcast in a multihop manner. Broadcast packets lead two challenges to forward the warning message in the vehicular network: redundancy of warning messages and competition with nonemergency transmissions. In this paper, we study and address the two major challenges to achieve low latency in delivery of the warning message. To reduce the intervehicle latency and end-to-end latency, which cause chain collisions, we propose a two-way intelligent broadcasting method with an adaptable distance-dependent backoff algorithm. Considering locations of vehicles, the proposed algorithm controls the broadcast of a warning message to reduce redundant EWM messages and adaptively chooses the contention window to compete with nonemergency transmission. Via simulations, we show that our proposed algorithm reduces the probability of rear-end crashes by 70% compared to previous algorithms by reducing the intervehicle delay. We also show that the end-to-end propagation delay of the warning message is reduced by 55%. PMID:25054181
Intelligent editor/printer enhancements
NASA Technical Reports Server (NTRS)
Woodfill, M. C.; Pheanis, D. C.
1983-01-01
Microprocessor support hardware, software, and cross assemblers relating to the Motorola 6800 and 6809 process systems were developed. Pinter controller and intelligent CRT development are discussed. The user's manual, design specifications for the MC6809 version of the intelligent printer controller card, and a 132-character by 64-line intelligent CRT display system using a Motorola 6809 MPU, and a one-line assembler and disassembler are provided.
Facts and fiction of learning systems. [decision making intelligent control
NASA Technical Reports Server (NTRS)
Saridis, G. N.
1975-01-01
The methodology that will provide the updated precision for the hardware control and the advanced decision making and planning in the software control is called learning systems and intelligent control. It was developed theoretically as an alternative for the nonsystematic heuristic approaches of artificial intelligence experiments and the inflexible formulation of modern optimal control methods. Its basic concepts are discussed and some feasibility studies of some practical applications are presented.
An intelligent traffic controller
DOT National Transportation Integrated Search
1995-11-01
Advances in computing sciences have not been applied to traffic control. This paper describes the development of an intelligent controller. A controller with advanced control logic can significantly improve traffic flows at intersections. In this vei...
Autonomous Distributed Congestion Control Scheme in WCDMA Network
NASA Astrophysics Data System (ADS)
Ahmad, Hafiz Farooq; Suguri, Hiroki; Choudhary, Muhammad Qaisar; Hassan, Ammar; Liaqat, Ali; Khan, Muhammad Umer
Wireless technology has become widely popular and an important means of communication. A key issue in delivering wireless services is the problem of congestion which has an adverse impact on the Quality of Service (QoS), especially timeliness. Although a lot of work has been done in the context of RRM (Radio Resource Management), the deliverance of quality service to the end user still remains a challenge. Therefore there is need for a system that provides real-time services to the users through high assurance. We propose an intelligent agent-based approach to guarantee a predefined Service Level Agreement (SLA) with heterogeneous user requirements for appropriate bandwidth allocation in QoS sensitive cellular networks. The proposed system architecture exploits Case Based Reasoning (CBR) technique to handle RRM process of congestion management. The system accomplishes predefined SLA through the use of Retrieval and Adaptation Algorithm based on CBR case library. The proposed intelligent agent architecture gives autonomy to Radio Network Controller (RNC) or Base Station (BS) in accepting, rejecting or buffering a connection request to manage system bandwidth. Instead of simply blocking the connection request as congestion hits the system, different buffering durations are allocated to diverse classes of users based on their SLA. This increases the opportunity of connection establishment and reduces the call blocking rate extensively in changing environment. We carry out simulation of the proposed system that verifies efficient performance for congestion handling. The results also show built-in dynamism of our system to cater for variety of SLA requirements.
DOE Office of Scientific and Technical Information (OSTI.GOV)
AlperEker; Mark Giammattia; Paul Houpt
''Intelligent Extruder'' described in this report is a software system and associated support services for monitoring and control of compounding extruders to improve material quality, reduce waste and energy use, with minimal addition of new sensors or changes to the factory floor system components. Emphasis is on process improvements to the mixing, melting and de-volatilization of base resins, fillers, pigments, fire retardants and other additives in the :finishing'' stage of high value added engineering polymer materials. While GE Plastics materials were used for experimental studies throughout the program, the concepts and principles are broadly applicable to other manufacturers materials. Themore » project involved a joint collaboration among GE Global Research, GE Industrial Systems and Coperion Werner & Pleiderer, USA, a major manufacturer of compounding equipment. Scope of the program included development of a algorithms for monitoring process material viscosity without rheological sensors or generating waste streams, a novel detection scheme for rapid detection of process upsets and an adaptive feedback control system to compensate for process upsets where at line adjustments are feasible. Software algorithms were implemented and tested on a laboratory scale extruder (50 lb/hr) at GE Global Research and data from a production scale system (2000 lb/hr) at GE Plastics was used to validate the monitoring and detection software. Although not evaluated experimentally, a new concept for extruder process monitoring through estimation of high frequency drive torque without strain gauges is developed and demonstrated in simulation. A plan to commercialize the software system is outlined, but commercialization has not been completed.« less
Control of parallel manipulators using force feedback
NASA Technical Reports Server (NTRS)
Nanua, Prabjot
1994-01-01
Two control schemes are compared for parallel robotic mechanisms actuated by hydraulic cylinders. One scheme, the 'rate based scheme', uses the position and rate information only for feedback. The second scheme, the 'force based scheme' feeds back the force information also. The force control scheme is shown to improve the response over the rate control one. It is a simple constant gain control scheme better suited to parallel mechanisms. The force control scheme can be easily modified for the dynamic forces on the end effector. This paper presents the results of a computer simulation of both the rate and force control schemes. The gains in the force based scheme can be individually adjusted in all three directions, whereas the adjustment in just one direction of the rate based scheme directly affects the other two directions.
Intelligent Integrated Health Management for a System of Systems
NASA Technical Reports Server (NTRS)
Smith, Harvey; Schmalzel, John; Figueroa, Fernando
2008-01-01
An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.
The relationship between executive functions and fluid intelligence in Parkinson's disease
Roca, M.; Manes, F.; Chade, A.; Gleichgerrcht, E.; Gershanik, O.; Arévalo, G. G.; Torralva, T.; Duncan, J.
2012-01-01
Background We recently demonstrated that decline in fluid intelligence is a substantial contributor to frontal deficits. For some classical ‘executive’ tasks, such as the Wisconsin Card Sorting Test (WCST) and Verbal Fluency, frontal deficits were entirely explained by fluid intelligence. However, on a second set of frontal tasks, deficits remained even after statistically controlling for this factor. These tasks included tests of theory of mind and multitasking. As frontal dysfunction is the most frequent cognitive deficit observed in early Parkinson's disease (PD), the present study aimed to determine the role of fluid intelligence in such deficits. Method We assessed patients with PD (n=32) and control subjects (n=22) with the aforementioned frontal tests and with a test of fluid intelligence. Group performance was compared and fluid intelligence was introduced as a covariate to determine its role in frontal deficits shown by PD patients. Results In line with our previous results, scores on the WCST and Verbal Fluency were closely linked to fluid intelligence. Significant patient–control differences were eliminated or at least substantially reduced once fluid intelligence was introduced as a covariate. However, for tasks of theory of mind and multitasking, deficits remained even after fluid intelligence was statistically controlled. Conclusions The present results suggest that clinical assessment of neuropsychological deficits in PD should include tests of fluid intelligence, together with one or more specific tasks that allow for the assessment of residual frontal deficits associated with theory of mind and multitasking. PMID:22440401
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 Weld Manufacturing: Role of Integrated Computational Welding Engineering
David, Stan A.; Chen, Jian; Feng, Zhili; ...
2017-12-02
A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less
Intelligent Weld Manufacturing: Role of Integrated Computational Welding Engineering
DOE Office of Scientific and Technical Information (OSTI.GOV)
David, Stan A.; Chen, Jian; Feng, Zhili
A master welder uses his sensory perceptions to evaluate the process and connect them with his/her knowledge base to take the necessary corrective measures with his/her acquired skills to make a good weld. All these actions must take place in real time. Success depends on intuition and skills, and the procedure is labor-intensive and frequently unreliable. The solution is intelligent weld manufacturing. The ultimate goal of intelligent weld manufacturing would involve sensing and control of heat source position, weld temperature, weld penetration, defect formation and ultimately control of microstructure and properties. This involves a solution to a problem (welding) withmore » many highly coupled and nonlinear variables. The trend is to use an emerging tool known as intelligent control. This approach enables the user to choose a desirable end factor such as properties, defect control, or productivity to derive the selection of process parameters such as current, voltage, or speed to provide for appropriate control of the process. Important elements of intelligent manufacturing are sensing and control theory and design, process modeling, and artificial intelligence. Significant progress has been made in all these areas. Integrated computational welding engineering (ICWE) is an emerging field that will aid in the realization of intelligent weld manufacturing. The paper will discuss the progress in process modeling, microstructure, properties, and process control and automation and the importance of ICWE. Also, control and automation strategies for friction stir welding will be discussed.« less
Fixed Point Learning Based Intelligent Traffic Control System
NASA Astrophysics Data System (ADS)
Zongyao, Wang; Cong, Sui; Cheng, Shao
2017-10-01
Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.
NASA Astrophysics Data System (ADS)
Zhou, Yanlai; Guo, Shenglian; Hong, Xingjun; Chang, Fi-John
2017-10-01
China's inter-basin water transfer projects have gained increasing attention in recent years. This study proposes an intelligent water allocation methodology for establishing optimal inter-basin water allocation schemes and assessing the impacts of water transfer projects on water-demanding sectors in the Hanjiang River Basin of China. We first analyze water demands for water allocation purpose, and then search optimal water allocation strategies for maximizing the water supply to water-demanding sectors and mitigating the negative impacts by using the Standard Genetic Algorithm (SGA) and Adaptive Genetic Algorithm (AGA), respectively. Lastly, the performance indexes of the water supply system are evaluated under different scenarios of inter-basin water transfer projects. The results indicate that: the AGA with adaptive crossover and mutation operators could increase the average annual water transfer from the Hanjiang River by 0.79 billion m3 (8.8%), the average annual water transfer from the Changjiang River by 0.18 billion m3 (6.5%), and the average annual hydropower generation by 0.49 billion kW h (5.4%) as well as reduce the average annual unmet water demand by 0.40 billion m3 (9.7%), as compared with the those of the SGA. We demonstrate that the proposed intelligent water allocation schemes can significantly mitigate the negative impacts of inter-basin water transfer projects on the reliability, vulnerability and resilience of water supply to the demanding sectors in water-supplying basins. This study has a direct bearing on more intelligent and effectual water allocation management under various scenarios of inter-basin water transfer projects.
Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.
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.
NASA Astrophysics Data System (ADS)
Xuejiao, M.; Chang, J.; Wang, Y.
2017-12-01
Flood risk reduction with non-engineering measures has become the main idea for flood management. It is more effective for flood risk management to take various non-engineering measures. In this paper, a flood control operation model for cascade reservoirs in the Upper Yellow River was proposed to lower the flood risk of the water system with multi-reservoir by combining the reservoir flood control operation (RFCO) and flood early warning together. Specifically, a discharge control chart was employed to build the joint RFCO simulation model for cascade reservoirs in the Upper Yellow River. And entropy-weighted fuzzy comprehensive evaluation method was adopted to establish a multi-factorial risk assessment model for flood warning grade. Furthermore, after determining the implementing mode of countermeasures with future inflow, an intelligent optimization algorithm was used to solve the optimization model for applicable water release scheme. In addition, another model without any countermeasure was set to be a comparative experiment. The results show that the model developed in this paper can further decrease the flood risk of water system with cascade reservoirs. It provides a new approach to flood risk management by coupling flood control operation and flood early warning of cascade reservoirs.
Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.
Zhang, Bin; Wang, Yuechao; Li, Hongyi
2015-01-01
Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579
Research on crude oil storage and transportation based on optimization algorithm
NASA Astrophysics Data System (ADS)
Yuan, Xuhua
2018-04-01
At present, the optimization theory and method have been widely used in the optimization scheduling and optimal operation scheme of complex production systems. Based on C++Builder 6 program development platform, the theoretical research results are implemented by computer. The simulation and intelligent decision system of crude oil storage and transportation inventory scheduling are designed. The system includes modules of project management, data management, graphics processing, simulation of oil depot operation scheme. It can realize the optimization of the scheduling scheme of crude oil storage and transportation system. A multi-point temperature measuring system for monitoring the temperature field of floating roof oil storage tank is developed. The results show that by optimizing operating parameters such as tank operating mode and temperature, the total transportation scheduling costs of the storage and transportation system can be reduced by 9.1%. Therefore, this method can realize safe and stable operation of crude oil storage and transportation system.
Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,
1981-05-08
STATEMENT ........................ 8 Artificial Intellegence Versus Supervisory Control ....... 8 Computer Generation of Operator Feedback...operator. Artificial Intelligence Versus Supervisory Control The use of computers to aid human operators can be divided into two catagories: artificial ...operator. Artificial intelligence ( A. I. ) attempts to give the computer maximum intelligence and to replace all operator functions by the computer
Artificial intelligence-assisted occupational lung disease diagnosis.
Harber, P; McCoy, J M; Howard, K; Greer, D; Luo, J
1991-08-01
An artificial intelligence expert-based system for facilitating the clinical recognition of occupational and environmental factors in lung disease has been developed in a pilot fashion. It utilizes a knowledge representation scheme to capture relevant clinical knowledge into structures about specific objects (jobs, diseases, etc) and pairwise relations between objects. Quantifiers describe both the closeness of association and risk, as well as the degree of belief in the validity of a fact. An independent inference engine utilizes the knowledge, combining likelihoods and uncertainties to achieve estimates of likelihood factors for specific paths from work to illness. The system creates a series of "paths," linking work activities to disease outcomes. One path links a single period of work to a single possible disease outcome. In a preliminary trial, the number of "paths" from job to possible disease averaged 18 per subject in a general population and averaged 25 per subject in an asthmatic population. Artificial intelligence methods hold promise in the future to facilitate diagnosis in pulmonary and occupational medicine.
Artificial intelligence based models for stream-flow forecasting: 2000-2015
NASA Astrophysics Data System (ADS)
Yaseen, Zaher Mundher; El-shafie, Ahmed; Jaafar, Othman; Afan, Haitham Abdulmohsin; Sayl, Khamis Naba
2015-11-01
The use of Artificial Intelligence (AI) has increased since the middle of the 20th century as seen in its application in a wide range of engineering and science problems. The last two decades, for example, has seen a dramatic increase in the development and application of various types of AI approaches for stream-flow forecasting. Generally speaking, AI has exhibited significant progress in forecasting and modeling non-linear hydrological applications and in capturing the noise complexity in the dataset. This paper explores the state-of-the-art application of AI in stream-flow forecasting, focusing on defining the data-driven of AI, the advantages of complementary models, as well as the literature and their possible future application in modeling and forecasting stream-flow. The review also identifies the major challenges and opportunities for prospective research, including, a new scheme for modeling the inflow, a novel method for preprocessing time series frequency based on Fast Orthogonal Search (FOS) techniques, and Swarm Intelligence (SI) as an optimization approach.
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.
A generalized form of the Bernoulli Trial collision scheme in DSMC: Derivation and evaluation
NASA Astrophysics Data System (ADS)
Roohi, Ehsan; Stefanov, Stefan; Shoja-Sani, Ahmad; Ejraei, Hossein
2018-02-01
The impetus of this research is to present a generalized Bernoulli Trial collision scheme in the context of the direct simulation Monte Carlo (DSMC) method. Previously, a subsequent of several collision schemes have been put forward, which were mathematically based on the Kac stochastic model. These include Bernoulli Trial (BT), Ballot Box (BB), Simplified Bernoulli Trial (SBT) and Intelligent Simplified Bernoulli Trial (ISBT) schemes. The number of considered pairs for a possible collision in the above-mentioned schemes varies between N (l) (N (l) - 1) / 2 in BT, 1 in BB, and (N (l) - 1) in SBT or ISBT, where N (l) is the instantaneous number of particles in the lth cell. Here, we derive a generalized form of the Bernoulli Trial collision scheme (GBT) where the number of selected pairs is any desired value smaller than (N (l) - 1), i.e., Nsel < (N (l) - 1), keeping the same the collision frequency and accuracy of the solution as the original SBT and BT models. We derive two distinct formulas for the GBT scheme, where both formula recover BB and SBT limits if Nsel is set as 1 and N (l) - 1, respectively, and provide accurate solutions for a wide set of test cases. The present generalization further improves the computational efficiency of the BT-based collision models compared to the standard no time counter (NTC) and nearest neighbor (NN) collision models.
Optimization and Control of Cyber-Physical Vehicle Systems
Bradley, Justin M.; Atkins, Ella M.
2015-01-01
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined. PMID:26378541
Optimization and Control of Cyber-Physical Vehicle Systems.
Bradley, Justin M; Atkins, Ella M
2015-09-11
A cyber-physical system (CPS) is composed of tightly-integrated computation, communication and physical elements. Medical devices, buildings, mobile devices, robots, transportation and energy systems can benefit from CPS co-design and optimization techniques. Cyber-physical vehicle systems (CPVSs) are rapidly advancing due to progress in real-time computing, control and artificial intelligence. Multidisciplinary or multi-objective design optimization maximizes CPS efficiency, capability and safety, while online regulation enables the vehicle to be responsive to disturbances, modeling errors and uncertainties. CPVS optimization occurs at design-time and at run-time. This paper surveys the run-time cooperative optimization or co-optimization of cyber and physical systems, which have historically been considered separately. A run-time CPVS is also cooperatively regulated or co-regulated when cyber and physical resources are utilized in a manner that is responsive to both cyber and physical system requirements. This paper surveys research that considers both cyber and physical resources in co-optimization and co-regulation schemes with applications to mobile robotic and vehicle systems. Time-varying sampling patterns, sensor scheduling, anytime control, feedback scheduling, task and motion planning and resource sharing are examined.
Constructive thinking, rational intelligence and irritable bowel syndrome.
Rey, Enrique; Moreno Ortega, Marta; Garcia Alonso, Monica-Olga; Diaz-Rubio, Manuel
2009-07-07
To evaluate rational and experiential intelligence in irritable bowel syndrome (IBS) sufferers. We recruited 100 subjects with IBS as per Rome II criteria (50 consulters and 50 non-consulters) and 100 healthy controls, matched by age, sex and educational level. Cases and controls completed a clinical questionnaire (including symptom characteristics and medical consultation) and the following tests: rational-intelligence (Wechsler Adult Intelligence Scale, 3rd edition); experiential-intelligence (Constructive Thinking Inventory); personality (NEO personality inventory); psychopathology (MMPI-2), anxiety (state-trait anxiety inventory) and life events (social readjustment rating scale). Analysis of variance was used to compare the test results of IBS-sufferers and controls, and a logistic regression model was then constructed and adjusted for age, sex and educational level to evaluate any possible association with IBS. No differences were found between IBS cases and controls in terms of IQ (102.0 +/- 10.8 vs 102.8 +/- 12.6), but IBS sufferers scored significantly lower in global constructive thinking (43.7 +/- 9.4 vs 49.6 +/- 9.7). In the logistic regression model, global constructive thinking score was independently linked to suffering from IBS [OR 0.92 (0.87-0.97)], without significant OR for total IQ. IBS subjects do not show lower rational intelligence than controls, but lower experiential intelligence is nevertheless associated with IBS.
Intelligent Home Control System Based on ARM10
NASA Astrophysics Data System (ADS)
Chen, G. X.; Jiang, J.; Zhong, L. H.
2017-10-01
Intelligent home is becoming the hot spot of social attention in the 21st century. When it is in China, it is a really new industry. However, there is no doubt that Intelligent home will become a new economic growth point of social development; it will change the life-style of human being. To develop the intelligent home, we should keep up with the development trend of technology. This is the reason why I talk about the intelligent home control system here. In this paper, intelligent home control system is designed for alarm and remote control on gas- leaking, fire disaster, earthquake prediction, etc., by examining environmental changes around house. When the Intelligent home control system has detected an accident occurs, the processor will communicate with the GSM module, informing the house keeper the occurrence of accident. User can receive and send the message to the system to cut the power by mobile phone. The system can get access to DCCthrough ARM10 JTAG interface, using DCC to send and receive messages. At the same time, the debugger on the host is mainly used to receive the user’s command and send it to the debug component in the target system. The data that returned from the target system is received and displayed to the user in a certain format.
Antecedents of Emotional Intelligence: An Empirical Study
ERIC Educational Resources Information Center
Barbuto, John E., Jr.; Story, Joana S.
2010-01-01
This study examined the relationships between emotional intelligence, locus of control, and mental boundaries. Three hundred and eighty-two county employees were sampled using a cross-sectional survey design. The results indicated internal locus of control and thin mental boundaries are positively related to emotional intelligence. A hierarchical…
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.
Global connectivity of prefrontal cortex predicts cognitive control and intelligence
Cole, Michael W.; Yarkoni, Tal; Repovs, Grega; Anticevic, Alan; Braver, Todd S.
2012-01-01
Control of thought and behavior is fundamental to human intelligence. Evidence suggests a fronto-parietal brain network implements such cognitive control across diverse contexts. We identify a mechanism – global connectivity – by which components of this network might coordinate control of other networks. A lateral prefrontal cortex (LPFC) region’s activity was found to predict performance in a high control demand working memory task, and also to exhibit high global connectivity. Critically, global connectivity in this LPFC region, involving connections both within and outside the fronto-parietal network, showed a highly selective relationship with individual differences in fluid intelligence. These findings suggest LPFC is a global hub with a brain-wide influence that facilitates the ability to implement control processes central to human intelligence. PMID:22745498
Emotional Intelligence Components in Alcohol Dependent and Mentally Healthy Individuals
Mohagheghi, Arash; Amiri, Shahrokh; Mousavi Rizi, Seyedreza; Safikhanlou, Salman
2015-01-01
Objective. Emotional intelligence might play an important role in the onset and persistence of different psychopathologies. This study investigated the relationship between emotional intelligence and alcohol dependence. Methods. In this case-control study, participants included alcohol dependent individuals and mentally healthy inpatients. Each group consisted of 40 individuals (male/female: 1). The diagnosis was based on the criteria of the DSM-IV-TR using the Structured Clinical Interview for DSM-IV (SCID-IV). All the participants completed Bar-On emotional intelligence test. Results. 20 males and 20 females were included in each group. Mean age of alcohol dependent participants and controls was 31.28 ± 7.82 and 34.93 ± 9.83 years in that order. The analyses showed that the alcohol dependent individuals had a significant difference compared with the control group and received lower scores in empathy, responsibility, impulse control, self-esteem, optimism, emotional consciousness, stress tolerance, autonomy, problem-solving, and total score of emotional intelligence components. Conclusion. Patients with alcohol dependence have deficits in components of emotional intelligence. Identifying and targeted training of the individuals with lower scores in components of emotional intelligence may be effective in prevention of alcohol dependence. PMID:25893214
Emotional intelligence components in alcohol dependent and mentally healthy individuals.
Mohagheghi, Arash; Amiri, Shahrokh; Mousavi Rizi, Seyedreza; Safikhanlou, Salman
2015-01-01
Emotional intelligence might play an important role in the onset and persistence of different psychopathologies. This study investigated the relationship between emotional intelligence and alcohol dependence. In this case-control study, participants included alcohol dependent individuals and mentally healthy inpatients. Each group consisted of 40 individuals (male/female: 1). The diagnosis was based on the criteria of the DSM-IV-TR using the Structured Clinical Interview for DSM-IV (SCID-IV). All the participants completed Bar-On emotional intelligence test. 20 males and 20 females were included in each group. Mean age of alcohol dependent participants and controls was 31.28±7.82 and 34.93±9.83 years in that order. The analyses showed that the alcohol dependent individuals had a significant difference compared with the control group and received lower scores in empathy, responsibility, impulse control, self-esteem, optimism, emotional consciousness, stress tolerance, autonomy, problem-solving, and total score of emotional intelligence components. Patients with alcohol dependence have deficits in components of emotional intelligence. Identifying and targeted training of the individuals with lower scores in components of emotional intelligence may be effective in prevention of alcohol dependence.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mohamed Abdelrahman; roger Haggard; Wagdy Mahmoud
The final goal of this project was the development of a system that is capable of controlling an industrial process effectively through the integration of information obtained through intelligent sensor fusion and intelligent control technologies. The industry of interest in this project was the metal casting industry as represented by cupola iron-melting furnaces. However, the developed technology is of generic type and hence applicable to several other industries. The system was divided into the following four major interacting components: 1. An object oriented generic architecture to integrate the developed software and hardware components @. Generic algorithms for intelligent signal analysismore » and sensor and model fusion 3. Development of supervisory structure for integration of intelligent sensor fusion data into the controller 4. Hardware implementation of intelligent signal analysis and fusion algorithms« less
NASA Astrophysics Data System (ADS)
Xie, Chang; Wen, Jing; Liu, Wenying; Wang, Jiaming
With the development of intelligent dispatching, the intelligence level of network control center full-service urgent need to raise. As an important daily work of network control center, the application of maintenance scheduling intelligent arrangement to achieve high-quality and safety operation of power grid is very important. By analyzing the shortages of the traditional maintenance scheduling software, this paper designs a power grid maintenance scheduling intelligence arrangement supporting system based on power flow forecasting, which uses the advanced technologies in maintenance scheduling, such as artificial intelligence, online security checking, intelligent visualization techniques. It implements the online security checking of maintenance scheduling based on power flow forecasting and power flow adjusting based on visualization, in order to make the maintenance scheduling arrangement moreintelligent and visual.
The Role of Intelligence Quotient and Emotional Intelligence in Cognitive Control Processes
Checa, Purificación; Fernández-Berrocal, Pablo
2015-01-01
The relationship between intelligence quotient (IQ) and cognitive control processes has been extensively established. Several studies have shown that IQ correlates with cognitive control abilities, such as interference suppression, as measured with experimental tasks like the Stroop and Flanker tasks. By contrast, there is a debate about the role of Emotional Intelligence (EI) in individuals' cognitive control abilities. The aim of this study is to examine the relation between IQ and EI, and cognitive control abilities evaluated by a typical laboratory control cognitive task, the Stroop task. Results show a negative correlation between IQ and the interference suppression index, the ability to inhibit processing of irrelevant information. However, the Managing Emotions dimension of EI measured by the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), but not self-reported of EI, negatively correlates with the impulsivity index, the premature execution of the response. These results suggest that not only is IQ crucial, but also competences related to EI are essential to human cognitive control processes. Limitations and implications of these results are also discussed. PMID:26648901
Kruschwitz, J D; Waller, L; Daedelow, L S; Walter, H; Veer, I M
2018-05-01
One hallmark example of a link between global topological network properties of complex functional brain connectivity and cognitive performance is the finding that general intelligence may depend on the efficiency of the brain's intrinsic functional network architecture. However, although this association has been featured prominently over the course of the last decade, the empirical basis for this broad association of general intelligence and global functional network efficiency is quite limited. In the current study, we set out to replicate the previously reported association between general intelligence and global functional network efficiency using the large sample size and high quality data of the Human Connectome Project, and extended the original study by testing for separate association of crystallized and fluid intelligence with global efficiency, characteristic path length, and global clustering coefficient. We were unable to provide evidence for the proposed association between general intelligence and functional brain network efficiency, as was demonstrated by van den Heuvel et al. (2009), or for any other association with the global network measures employed. More specifically, across multiple network definition schemes, ranging from voxel-level networks to networks of only 100 nodes, no robust associations and only very weak non-significant effects with a maximal R 2 of 0.01 could be observed. Notably, the strongest (non-significant) effects were observed in voxel-level networks. We discuss the possibility that the low power of previous studies and publication bias may have led to false positive results fostering the widely accepted notion of general intelligence being associated to functional global network efficiency. Copyright © 2018 Elsevier Inc. All rights reserved.
Galactic exploration by directed self-replicating probes, and its implications for the Fermi paradox
NASA Astrophysics Data System (ADS)
Barlow, Martin T.
2013-01-01
This paper proposes a long-term scheme for robotic exploration of the galaxy, and then considers the implications in terms of the `Fermi paradox' and our search for extraterrestrial intelligence (ETI). We discuss the `Galactic ecology' of civilizations in terms of the parameters T (time between ET civilizations arising) and L, the lifetime of these civilizations. Six different regions are described.
An intelligent automated command and control system for spacecraft mission operations
NASA Technical Reports Server (NTRS)
Stoffel, A. William
1994-01-01
The Intelligent Command and Control (ICC) System research project is intended to provide the technology base necessary for producing an intelligent automated command and control (C&C) system capable of performing all the ground control C&C functions currently performed by Mission Operations Center (MOC) project Flight Operations Team (FOT). The ICC research accomplishments to date, details of the ICC, and the planned outcome of the ICC research, mentioned above, are discussed in detail.
Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight
NASA Technical Reports Server (NTRS)
Dufrene, Warren R., Jr.
2004-01-01
This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.
Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight
NASA Technical Reports Server (NTRS)
Dufrene, Warren R., Jr.
2003-01-01
This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.
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.
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
This study assessed the enhanced energy production which is possible when variable-speed wind turbines are electronically controlled by an intelligent controller for efficiency optimization and performance improvement. The control system consists of three fuzzy- logic controllers...
Time estimation predicts mathematical intelligence.
Kramer, Peter; Bressan, Paola; Grassi, Massimo
2011-01-01
Performing mental subtractions affects time (duration) estimates, and making time estimates disrupts mental subtractions. This interaction has been attributed to the concurrent involvement of time estimation and arithmetic with general intelligence and working memory. Given the extant evidence of a relationship between time and number, here we test the stronger hypothesis that time estimation correlates specifically with mathematical intelligence, and not with general intelligence or working-memory capacity. Participants performed a (prospective) time estimation experiment, completed several subtests of the WAIS intelligence test, and self-rated their mathematical skill. For five different durations, we found that time estimation correlated with both arithmetic ability and self-rated mathematical skill. Controlling for non-mathematical intelligence (including working memory capacity) did not change the results. Conversely, correlations between time estimation and non-mathematical intelligence either were nonsignificant, or disappeared after controlling for mathematical intelligence. We conclude that time estimation specifically predicts mathematical intelligence. On the basis of the relevant literature, we furthermore conclude that the relationship between time estimation and mathematical intelligence is likely due to a common reliance on spatial ability.
NASA Technical Reports Server (NTRS)
Conway, Lynn; Volz, Richard; Walker, Michael W.
1989-01-01
There is a growing need for humans to perform complex remote operations and to extend the intelligence and experience of experts to distant applications. It is asserted that a blending of human intelligence, modern information technology, remote control, and intelligent autonomous systems is required, and have coined the term tele-autonomous technology, or tele-automation, for methods producing intelligent action at a distance. Tele-automation goes beyond autonomous control by blending in human intelligence. It goes beyond tele-operation by incorporating as much autonomy as possible and/or reasonable. A new approach is discussed for solving one of the fundamental problems facing tele-autonomous systems: The need to overcome time delays due to telemetry and signal propagation. New concepts are introduced called time and position clutches, that allow the time and position frames between the local user control and the remote device being controlled, to be desynchronized respectively. The design and implementation of these mechanisms are described in detail. It is demonstrated that these mechanisms lead to substantial telemanipulation performance improvements, including the result of improvements even in the absence of time delays. The new controls also yield a simple protocol for control handoffs of manipulation tasks between local operators and remote systems.
Li, Shanzhi; Wang, Haoping; Tian, Yang; Aitouch, Abdel; Klein, John
2016-09-01
This paper presents an intelligent proportional-integral sliding mode control (iPISMC) for direct power control of variable speed-constant frequency wind turbine system. This approach deals with optimal power production (in the maximum power point tracking sense) under several disturbance factors such as turbulent wind. This controller is made of two sub-components: (i) an intelligent proportional-integral module for online disturbance compensation and (ii) a sliding mode module for circumventing disturbance estimation errors. This iPISMC method has been tested on FAST/Simulink platform of a 5MW wind turbine system. The obtained results demonstrate that the proposed iPISMC method outperforms the classical PI and intelligent proportional-integral control (iPI) in terms of both active power and response time. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Sriram, Rishi
2014-01-01
This study utilized an experimental pretest-posttest control group design to determine if changing the way academically high-risk college students view intelligence affected their academic effort and achievement when compared to students in a control intervention. Results indicated that students taught to view intelligence as malleable reported…
ERIC Educational Resources Information Center
Stipancic, Kaila L.; Tjaden, Kris; Wilding, Gregory
2016-01-01
Purpose: This study obtained judgments of sentence intelligibility using orthographic transcription for comparison with previously reported intelligibility judgments obtained using a visual analog scale (VAS) for individuals with Parkinson's disease and multiple sclerosis and healthy controls (K. Tjaden, J. E. Sussman, & G. E. Wilding, 2014).…
Constructive thinking, rational intelligence and irritable bowel syndrome
Rey, Enrique; Ortega, Marta Moreno; Alonso, Monica Olga Garcia; Diaz-Rubio, Manuel
2009-01-01
AIM: To evaluate rational and experiential intelligence in irritable bowel syndrome (IBS) sufferers. METHODS: We recruited 100 subjects with IBS as per Rome II criteria (50 consulters and 50 non-consulters) and 100 healthy controls, matched by age, sex and educational level. Cases and controls completed a clinical questionnaire (including symptom characteristics and medical consultation) and the following tests: rational-intelligence (Wechsler Adult Intelligence Scale, 3rd edition); experiential-intelligence (Constructive Thinking Inventory); personality (NEO personality inventory); psychopathology (MMPI-2), anxiety (state-trait anxiety inventory) and life events (social readjustment rating scale). Analysis of variance was used to compare the test results of IBS-sufferers and controls, and a logistic regression model was then constructed and adjusted for age, sex and educational level to evaluate any possible association with IBS. RESULTS: No differences were found between IBS cases and controls in terms of IQ (102.0 ± 10.8 vs 102.8 ± 12.6), but IBS sufferers scored significantly lower in global constructive thinking (43.7 ± 9.4 vs 49.6 ± 9.7). In the logistic regression model, global constructive thinking score was independently linked to suffering from IBS [OR 0.92 (0.87-0.97)], without significant OR for total IQ. CONCLUSION: IBS subjects do not show lower rational intelligence than controls, but lower experiential intelligence is nevertheless associated with IBS. PMID:19575489
Architectures for intelligent machines
NASA Technical Reports Server (NTRS)
Saridis, George N.
1991-01-01
The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.
Distributed intelligence for supervisory control
NASA Technical Reports Server (NTRS)
Wolfe, W. J.; Raney, S. D.
1987-01-01
Supervisory control systems must deal with various types of intelligence distributed throughout the layers of control. Typical layers are real-time servo control, off-line planning and reasoning subsystems and finally, the human operator. Design methodologies must account for the fact that the majority of the intelligence will reside with the human operator. Hierarchical decompositions and feedback loops as conceptual building blocks that provide a common ground for man-machine interaction are discussed. Examples of types of parallelism and parallel implementation on several classes of computer architecture are also discussed.
The Intelligent Control System and Experiments for an Unmanned Wave Glider.
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
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
Overview of Intelligent Systems and Operations Development
NASA Technical Reports Server (NTRS)
Pallix, Joan; Dorais, Greg; Penix, John
2004-01-01
To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.
1984-12-01
system. The reconstruction process is Simply data fusion after allA data are in. After reconstruction, artifcial intelligence (Al) techniques may be...14. CATE OF fhPM~TVW MWtvt Ogv It PAWE COMN Interim __100 -_ TO December 1984 24 MILD ON" s-o Artificial intelligence Command control Data fusion...RD-Ai5O 867 RESEARCH NEEDS FOR ARTIFICIAL INTELLIGENCE APPLICATIONS i/i IN SUPPORT OF C3 (..(U) NAVAL OCEAN SVSTEIIS CENTER SAN DIEGO CA R R DILLARD
Control of a Robotic Hand Using a Tongue Control System-A Prosthesis Application.
Johansen, Daniel; Cipriani, Christian; Popovic, Dejan B; Struijk, Lotte N S A
2016-07-01
The aim of this study was to investigate the feasibility of using an inductive tongue control system (ITCS) for controlling robotic/prosthetic hands and arms. This study presents a novel dual modal control scheme for multigrasp robotic hands combining standard electromyogram (EMG) with the ITCS. The performance of the ITCS control scheme was evaluated in a comparative study. Ten healthy subjects used both the ITCS control scheme and a conventional EMG control scheme to complete grasping exercises with the IH1 Azzurra robotic hand implementing five grasps. Time to activate a desired function or grasp was used as the performance metric. Statistically significant differences were found when comparing the performance of the two control schemes. On average, the ITCS control scheme was 1.15 s faster than the EMG control scheme, corresponding to a 35.4% reduction in the activation time. The largest difference was for grasp 5 with a mean AT reduction of 45.3% (2.38 s). The findings indicate that using the ITCS control scheme could allow for faster activation of specific grasps or functions compared with a conventional EMG control scheme. For transhumeral and especially bilateral amputees, the ITCS control scheme could have a significant impact on the prosthesis control. In addition, the ITCS would provide bilateral amputees with the additional advantage of environmental and computer control for which the ITCS was originally developed.
Adaptive method with intercessory feedback control for an intelligent agent
Goldsmith, Steven Y.
2004-06-22
An adaptive architecture method with feedback control for an intelligent agent provides for adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. An adaptive architecture method with feedback control for multiple intelligent agents provides for coordinating and adaptively integrating reflexive and deliberative responses to a stimulus according to a goal. Re-programming of the adaptive architecture is through a nexus which coordinates reflexive and deliberator components.
Intelligent Propulsion System Foundation Technology: Summary of Research
NASA Technical Reports Server (NTRS)
Williams, James C.
2004-01-01
The purpose of this cooperative agreement was to develop a foundation of intelligent propulsion technologies for NASA and industry that will have an impact on safety, noise, emissions and cost. These intelligent engine technologies included sensors, electronics, communications, control logic, actuators, and smart materials and structures. Furthermore this cooperative agreement helped prepare future graduates to develop the revolutionary intelligent propulsion technologies that will be needed to ensure pre-eminence of the U.S. aerospace industry. The program consisted of three primary research areas (and associated work elements at Ohio universities): 1.0 Turbine Engine Prognostics, 2.0 Active Controls for Emissions and Noise Reduction, and 3.0 Active Structural Controls.
Research and development of intelligent controller for high-grade sanitary ware
NASA Astrophysics Data System (ADS)
Bao, Kongjun; Shen, Qingping
2013-03-01
With the social and economic development and people's living standards improve, more and more emphasis on modern society, people improve the quality of family life, the use of intelligent controller applications in high-grade sanitary ware physiotherapy students. Analysis of high-grade sanitary ware physiotherapy common functions pointed out in the production and use of the possible risks, proposed implementation of the system hardware and matching, given the system software implementation process. High-grade sanitary ware physiotherapy intelligent controller not only to achieve elegant and beautiful, simple, physical therapy, water power, deodorant, multi-function, intelligent control, to meet the consumers, the high-end sanitary ware market, strong demand, Accelerate the enterprise product Upgrade and improve the competitiveness of enterprises.
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.
ERIC Educational Resources Information Center
Ferrando, Mercedes; Prieto, Maria Dolores; Almeida, Leandro S.; Ferrandiz, Carmen; Bermejo, Rosario; Lopez-Pina, Jose Antonio; Hernandez, Daniel; Sainz, Marta; Fernandez, Mari-Carmen
2011-01-01
This article analyses the relationship between trait emotional intelligence and academic performance, controlling for the effects of IQ, personality, and self-concept dimensions. A sample of 290 preadolescents (11-12 years old) took part in the study. The instruments used were (a) Trait Emotional Intelligence Questionnaire-Adolescents Short Form…
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.
32 CFR 154.76 - Responsibilities.
Code of Federal Regulations, 2010 CFR
2010-07-01
... Defense for Command, Control, Communications, and Intelligence (ASD(C31)) shall have primary... Secretary of Defense for Command, Control, Communications, and Intelligence (ASD(C31)) and the General...
32 CFR 154.76 - Responsibilities.
Code of Federal Regulations, 2011 CFR
2011-07-01
... Defense for Command, Control, Communications, and Intelligence (ASD(C31)) shall have primary... Secretary of Defense for Command, Control, Communications, and Intelligence (ASD(C31)) and the General...
Research on computer-aided design of modern marine power systems
NASA Astrophysics Data System (ADS)
Ding, Dongdong; Zeng, Fanming; Chen, Guojun
2004-03-01
To make the MPS (Marine Power System) design process more economical and easier, a new CAD scheme is brought forward which takes much advantage of VR (Virtual Reality) and AI (Artificial Intelligence) technologies. This CAD system can shorten the period of design and reduce the requirements on designers' experience in large scale. And some key issues like the selection of hardware and software of such a system are discussed.
Evaluating the Effectiveness of IP Hopping via an Address Routing Gateway
2013-03-01
37 DARPA Defense Advanced Research Projects Agency . . . . . . . . . . . . . . . . . . . . . . . . . . 20 DHCP Dynamic Host...Protocol ( DHCP ) to force the changes. Through the use of a slightly intelligent DHCP server that leases IPs for a only a short time frame (on the order of...tens of minutes) and only offers IPs that have not been used recently, most networks already using DHCP can quickly change to a randomized scheme. This
Intelligent cognitive radio jamming - a game-theoretical approach
NASA Astrophysics Data System (ADS)
Dabcevic, Kresimir; Betancourt, Alejandro; Marcenaro, Lucio; Regazzoni, Carlo S.
2014-12-01
Cognitive radio (CR) promises to be a solution for the spectrum underutilization problems. However, security issues pertaining to cognitive radio technology are still an understudied topic. One of the prevailing such issues are intelligent radio frequency (RF) jamming attacks, where adversaries are able to exploit on-the-fly reconfigurability potentials and learning mechanisms of cognitive radios in order to devise and deploy advanced jamming tactics. In this paper, we use a game-theoretical approach to analyze jamming/anti-jamming behavior between cognitive radio systems. A non-zero-sum game with incomplete information on an opponent's strategy and payoff is modelled as an extension of Markov decision process (MDP). Learning algorithms based on adaptive payoff play and fictitious play are considered. A combination of frequency hopping and power alteration is deployed as an anti-jamming scheme. A real-life software-defined radio (SDR) platform is used in order to perform measurements useful for quantifying the jamming impacts, as well as to infer relevant hardware-related properties. Results of these measurements are then used as parameters for the modelled jamming/anti-jamming game and are compared to the Nash equilibrium of the game. Simulation results indicate, among other, the benefit provided to the jammer when it is employed with the spectrum sensing algorithm in proactive frequency hopping and power alteration schemes.
Novel approach for dam break flow modeling using computational intelligence
NASA Astrophysics Data System (ADS)
Seyedashraf, Omid; Mehrabi, Mohammad; Akhtari, Ali Akbar
2018-04-01
A new methodology based on the computational intelligence (CI) system is proposed and tested for modeling the classic 1D dam-break flow problem. The reason to seek for a new solution lies in the shortcomings of the existing analytical and numerical models. This includes the difficulty of using the exact solutions and the unwanted fluctuations, which arise in the numerical results. In this research, the application of the radial-basis-function (RBF) and multi-layer-perceptron (MLP) systems is detailed for the solution of twenty-nine dam-break scenarios. The models are developed using seven variables, i.e. the length of the channel, the depths of the up-and downstream sections, time, and distance as the inputs. Moreover, the depths and velocities of each computational node in the flow domain are considered as the model outputs. The models are validated against the analytical, and Lax-Wendroff and MacCormack FDM schemes. The findings indicate that the employed CI models are able to replicate the overall shape of the shock- and rarefaction-waves. Furthermore, the MLP system outperforms RBF and the tested numerical schemes. A new monolithic equation is proposed based on the best fitting model, which can be used as an efficient alternative to the existing piecewise analytic equations.
Exploration and design of smart home circuit based on ZigBee
NASA Astrophysics Data System (ADS)
Luo, Huirong
2018-05-01
To apply ZigBee technique in smart home circuit design, in the hardware design link of ZigBee node, TI Company's ZigBee wireless communication chip CC2530 was used to complete the design of ZigBee RF module circuit and peripheral circuit. In addition, the function demand and the overall scheme of the intelligent system based on smart home furnishing were proposed. Finally, the smart home system was built by combining ZigBee network and intelligent gateway. The function realization, reliability and power consumption of ZigBee network were tested. The results showed that ZigBee technology was applied to smart home system, making it have some advantages in terms of flexibility, scalability, power consumption and indoor aesthetics. To sum up, the system has high application value.
FPGA implementation of advanced FEC schemes for intelligent aggregation networks
NASA Astrophysics Data System (ADS)
Zou, Ding; Djordjevic, Ivan B.
2016-02-01
In state-of-the-art fiber-optics communication systems the fixed forward error correction (FEC) and constellation size are employed. While it is important to closely approach the Shannon limit by using turbo product codes (TPC) and low-density parity-check (LDPC) codes with soft-decision decoding (SDD) algorithm; rate-adaptive techniques, which enable increased information rates over short links and reliable transmission over long links, are likely to become more important with ever-increasing network traffic demands. In this invited paper, we describe a rate adaptive non-binary LDPC coding technique, and demonstrate its flexibility and good performance exhibiting no error floor at BER down to 10-15 in entire code rate range, by FPGA-based emulation, making it a viable solution in the next-generation high-speed intelligent aggregation networks.
NASA Astrophysics Data System (ADS)
Tipler, F. J.
1982-10-01
An assessment is presented of the probability of the existence of intelligent extraterrestrial life in view of biological evolutionary constraints, in order to furnish some perspective for the hopes and claims of search of extraterrestrial intelligence (SETI) enthusiasts. Attention is given to a hypothetical extraterrestrial civilization's exploration/colonization of interstellar space by means of von Neumann machine-like, endlessly self-replicating space probes which would eventually reach the planetary systems of all stars in the Galaxy. These probes would be able to replicate the biology of their creator species, upon reaching a hospitable planet. It is suggested that the fundamental technological feasibility of such schemes, and their geometrically progressive comprehension of the Galaxy, would make actual colonization of the earth by extraterrestrials so probable as to destroy the hopes of SETI backers for occasional contact.
An intelligent factory-wide optimal operation system for continuous production process
NASA Astrophysics Data System (ADS)
Ding, Jinliang; Chai, Tianyou; Wang, Hongfeng; Wang, Junwei; Zheng, Xiuping
2016-03-01
In this study, a novel intelligent factory-wide operation system for a continuous production process is designed to optimise the entire production process, which consists of multiple units; furthermore, this system is developed using process operational data to avoid the complexity of mathematical modelling of the continuous production process. The data-driven approach aims to specify the structure of the optimal operation system; in particular, the operational data of the process are used to formulate each part of the system. In this context, the domain knowledge of process engineers is utilised, and a closed-loop dynamic optimisation strategy, which combines feedback, performance prediction, feed-forward, and dynamic tuning schemes into a framework, is employed. The effectiveness of the proposed system has been verified using industrial experimental results.
NASA Astrophysics Data System (ADS)
Alaraj, Muhannad; Radenkovic, Miloje; Park, Jae-Do
2017-02-01
Microbial fuel cells (MFCs) are renewable and sustainable energy sources that can be used for various applications. The MFC output power depends on its biochemical conditions as well as the terminal operating points in terms of output voltage and current. There exists one operating point that gives the maximum possible power from the MFC, maximum power point (MPP), for a given operating condition. However, this MPP may vary and needs to be tracked in order to maintain the maximum power extraction from the MFC. Furthermore, MFC reactors often develop voltage overshoots that cause drastic drops in the terminal voltage, current, and the output power. When the voltage overshoot happens, an additional control measure is necessary as conventional MPPT algorithms will fail because of the change in the voltage-current relationship. In this paper, the extremum seeking (ES) algorithm was used to track the varying MPP and a voltage overshoot avoidance (VOA) algorithm is developed to manage the voltage overshoot conditions. The proposed ES-MPPT with VOA algorithm was able to extract 197.2 mJ during 10-min operation avoiding voltage overshoot, while the ES MPPT-only scheme stopped harvesting after only 18.75 mJ because of the voltage overshoot happened at 0.4 min.
The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...
The role of height in the sex difference in intelligence.
Kanazawa, Satoshi; Reyniers, Diane J
2009-01-01
Recent studies conclude that men on average have higher intelligence than women by 3-5 IQ points. However, the ultimate evolutionary question of why men should have evolved to have higher intelligence than women remains. We suggest that men may have slightly higher intelligence than women through 4 mechanisms: (1) assortative mating of intelligent men and beautiful women, (2) assortative mating of tall men and beautiful women, (3) an extrinsic correlation between height and intelligence produced by Mechanisms 1 and 2, and (4) a higher-than-expected offspring sex ratio (more sons) among tall (and hence intelligent) parents. Consistent with our suggestion, we show that men may have higher IQs than women because they are taller, and once we control for height women have slightly higher IQs than men.The correlation between height and IQ and the female advantage in intelligence persist even after we control for health as a measure of genetic quality, as well as physical attractiveness, age, race, education, and earnings. Height is also strongly associated with intelligence within each sex.
Serial network simplifies the design of multiple microcomputer systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Folkes, D.
1981-01-01
Recently there has been a lot of interest in developing network communication schemes for carrying digital data between locally distributed computing stations. Many of these schemes have focused on distributed networking techniques for data processing applications. These applications suggest the use of a serial, multipoint bus, where a number of remote intelligent units act as slaves to a central or host computer. Each slave would be serially addressable from the host and would perform required operations upon being addressed by the host. Based on an MK3873 single-chip microcomputer, the SCU 20 is designed to be such a remote slave device.more » The capabilities of the SCU 20 and its use in systems applications are examined.« less
Expertise and reasoning with possibility: An explanation of modal logic and expert systems
NASA Technical Reports Server (NTRS)
Rochowiak, Daniel
1988-01-01
Recently systems of modal reasoning have been brought to the foreground of artificial intelligence studies. The intuitive idea of research efforts in this area is that in addition to the actual world in which sentences have certain truth values there are other worlds in which those sentences have different truth values. Such alternative worlds can be considered as possible worlds, and an agent may or may not have access to some or all of them. This approach to reasoning can be valuable in extending the expert system paradigm. Using the scheme of reasoning proposed by Toulmin, Reike and Janick and the modal system T, a scheme is proposed for expert reasoning that mitigates some of the criticisms raised by Schank and Nickerson.
Intelligence and arms control - a marriage of convenience
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hirschfeld, T.J.
1987-01-01
This book offers the first comprehensive look at how the vast US intelligence network enables negotiators to forge viable arms control agreements. The intelligence role in all three phases of the arms control process is discussed - from the design phase when reliable information is needed, to the execution phase when proposals are modified, to the maintenance phase when agreed-upon obligations begin to constrain adversary behavior and compliance becomes the key political issue. Contributors include: former CIA Director William E. Colby; Douglas George, Chief of the CIA's Control Intelligence Staff, Admiral Bobby R. Inman, former NSA Director; Hans Mark, formermore » Air Force Secretary and NSA administrator; Walt W. Rostow, National Security Adviser to President Johnson; and Paul Warnke, former Director of the Arms Control and Disarmament Agency and Chief Negotiator for SALT II.« less
An Artificial Intelligence Approach for Gears Diagnostics in AUVs
Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano
2016-01-01
In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved. PMID:27077868
An Artificial Intelligence Approach for Gears Diagnostics in AUVs.
Marichal, Graciliano Nicolás; Del Castillo, María Lourdes; López, Jesús; Padrón, Isidro; Artés, Mariano
2016-04-12
In this paper, an intelligent scheme for detecting incipient defects in spur gears is presented. In fact, the study has been undertaken to determine these defects in a single propeller system of a small-sized unmanned helicopter. It is important to remark that although the study focused on this particular system, the obtained results could be extended to other systems known as AUVs (Autonomous Unmanned Vehicles), where the usage of polymer gears in the vehicle transmission is frequent. Few studies have been carried out on these kinds of gears. In this paper, an experimental platform has been adapted for the study and several samples have been prepared. Moreover, several vibration signals have been measured and their time-frequency characteristics have been taken as inputs to the diagnostic system. In fact, a diagnostic system based on an artificial intelligence strategy has been devised. Furthermore, techniques based on several paradigms of the Artificial Intelligence (Neural Networks, Fuzzy systems and Genetic Algorithms) have been applied altogether in order to design an efficient fault diagnostic system. A hybrid Genetic Neuro-Fuzzy system has been developed, where it is possible, at the final stage of the learning process, to express the fault diagnostic system as a set of fuzzy rules. Several trials have been carried out and satisfactory results have been achieved.
Knowledge-based processing for aircraft flight control
NASA Technical Reports Server (NTRS)
Painter, John H.; Glass, Emily; Economides, Gregory; Russell, Paul
1994-01-01
This Contractor Report documents research in Intelligent Control using knowledge-based processing in a manner dual to methods found in the classic stochastic decision, estimation, and control discipline. Such knowledge-based control has also been called Declarative, and Hybid. Software architectures were sought, employing the parallelism inherent in modern object-oriented modeling and programming. The viewpoint adopted was that Intelligent Control employs a class of domain-specific software architectures having features common over a broad variety of implementations, such as management of aircraft flight, power distribution, etc. As much attention was paid to software engineering issues as to artificial intelligence and control issues. This research considered that particular processing methods from the stochastic and knowledge-based worlds are duals, that is, similar in a broad context. They provide architectural design concepts which serve as bridges between the disparate disciplines of decision, estimation, control, and artificial intelligence. This research was applied to the control of a subsonic transport aircraft in the airport terminal area.
Scope of Attention, Control of Attention, and Intelligence in Children and Adults
Cowan, Nelson; Fristoe, Nathanael M.; Elliott, Emily M.; Brunner, Ryan P.; Saults, J. Scott
2006-01-01
Recent experimentation has shown that cognitive aptitude measures are predicted by tests of the scope of an individual’s attention or capacity in simple working-memory tasks, and also by the ability to control attention. However, these experiments do not indicate how separate or related the scope and control of attention are. An experiment with 52 children 10 to 11 years old and 52 college students included measures of the scope and control of attention as well as verbal and nonverbal aptitude measures. The children showed little evidence of using sophisticated attentional control, but the scope of attention predicted intelligence in that group. In adults, the scope and control of attention both varied among individuals, and they accounted for considerable individual variance in intelligence. About 1/3 that variance was shared between scope and control, the rest being unique to one or the other. Scope and control of attention appear to be related but distinct contributors to intelligence. PMID:17489300
Dorsolateral Prefrontal Contributions to Human Intelligence
Barbey, Aron K.; Colom, Roberto; Grafman, Jordan
2012-01-01
Although cognitive neuroscience has made remarkable progress in understanding the involvement of the prefrontal cortex in executive control functions for human intelligence, the necessity of the dorsolateral prefrontal cortex (dlPFC) for key competencies of general intelligence and executive function remains to be well established. Here we studied human brain lesion patients with dlPFC lesions to investigate whether this region is computationally necessary for performance on neuropsychological tests of general intelligence and executive function, administering the Wechsler Adult Intelligence Scale (WAIS) and subtests of the Delis Kaplan Executive Function System (D-KEFS) to three groups: dlPFC lesions (n = 19), non-dlPFC lesions (n = 152), and no brain lesions (n = 55). The key results indicate that: (1) patients with focal dlPFC damage exhibit lower scores, at the latent variable level, than controls in general intelligence (g) and executive function; (2) dlPFC patients demonstrate lower scores than controls in several executive measures; and (3) these latter differences are no longer significant when the pervasive influence of the general factor of intelligence (g) is statistically removed. The observed findings support a central role for the dlPFC in general intelligence and make specific recommendations for the interpretation and application of the WAIS and D-KEFS to the study of high-level cognition in health and disease. PMID:22634247
Cognitive Profile of Children and Adolescents with Anorexia Nervosa
Kjaersdam Telléus, Gry; Jepsen, Jens Richardt; Bentz, Mette; Christiansen, Eva; Jensen, Signe O W; Fagerlund, Birgitte; Thomsen, Per Hove
2015-01-01
Objective Few studies of cognitive functioning in children and adolescents with anorexia nervosa (AN) have been conducted. The aim of this study was to examine the neurocognitive and intelligence profile of this clinical group. Method The study was a matched case–control (N = 188), multi-centre study including children and adolescents with AN (N = 94) and healthy control participants (N = 94). Results The results suggest that Full Scale Intelligence Quotient (Wechsler Intelligence Scale for Children-III/Wechsler Adult Intelligence Scale-III) in this patient group is close to the normal population mean of 100. Individuals with AN exhibited significantly worse performance in nonverbal intelligence functions (i.e. Wechsler Intelligence Scale for Children-III/Wechsler Adult Intelligence Scale-III, Perceptual Organization Index) and in verbal memory (Test of Memory and Learning—Second Edition, Memory for Stories) and motor speed (Cambridge Neuropsychological Test Automated Battery, Simple and Choice Reaction Time) compared with healthy control participants. No significant difference in set-shifting ability (Cambridge Neuropsychological Test Automated Battery, Intra-Extra Dimensional Set Shift and Trail Making Test B) was found. Conclusions Inefficiency in nonverbal intelligence functions and in specific cognitive functions was found in this study of children and adolescents with AN. © 2014 The Authors. European Eating Disorders Review published by John Wiley & Sons, Ltd. PMID:25504443
Cognitive profile of children and adolescents with anorexia nervosa.
Kjaersdam Telléus, Gry; Jepsen, Jens Richardt; Bentz, Mette; Christiansen, Eva; Jensen, Signe O W; Fagerlund, Birgitte; Thomsen, Per Hove
2015-01-01
Few studies of cognitive functioning in children and adolescents with anorexia nervosa (AN) have been conducted. The aim of this study was to examine the neurocognitive and intelligence profile of this clinical group. The study was a matched case-control (N = 188), multi-centre study including children and adolescents with AN (N = 94) and healthy control participants (N = 94). The results suggest that Full Scale Intelligence Quotient (Wechsler Intelligence Scale for Children-III/Wechsler Adult Intelligence Scale-III) in this patient group is close to the normal population mean of 100. Individuals with AN exhibited significantly worse performance in nonverbal intelligence functions (i.e. Wechsler Intelligence Scale for Children-III/Wechsler Adult Intelligence Scale-III, Perceptual Organization Index) and in verbal memory (Test of Memory and Learning-Second Edition, Memory for Stories) and motor speed (Cambridge Neuropsychological Test Automated Battery, Simple and Choice Reaction Time) compared with healthy control participants. No significant difference in set-shifting ability (Cambridge Neuropsychological Test Automated Battery, Intra-Extra Dimensional Set Shift and Trail Making Test B) was found. Inefficiency in nonverbal intelligence functions and in specific cognitive functions was found in this study of children and adolescents with AN. © 2014 The Authors. European Eating Disorders Review published by John Wiley & Sons, Ltd.
Gender, g, Gender Identity Concepts, and Self-Constructs as Predictors of the Self-Estimated IQ
Storek, Josephine
2013-01-01
In all 102 participants completed 2 intelligence tests, a self-estimated domain-masculine (DMIQ) intelligence rating (which is a composite of self-rated mathematical–logical and spatial intelligence), a measure of self-esteem, and of self-control. The aim was to confirm and extend previous findings about the role of general intelligence and gender identity in self-assessed intelligence. It aimed to examine further correlates of the Hubris–Humility Effect that shows men believe they are more intelligent than women. The DMIQ scores were correlated significantly with gender, psychometrically assessed IQ, and masculinity but not self-esteem or self-control. Stepwise regressions indicated that gender and gender role were the strongest predictors of DMIQ accounting for a third of the variance. PMID:24303578
Gender, g, gender identity concepts, and self-constructs as predictors of the self-estimated IQ.
Storek, Josephine; Furnham, Adrian
2013-01-01
In all 102 participants completed 2 intelligence tests, a self-estimated domain-masculine (DMIQ) intelligence rating (which is a composite of self-rated mathematical-logical and spatial intelligence), a measure of self-esteem, and of self-control. The aim was to confirm and extend previous findings about the role of general intelligence and gender identity in self-assessed intelligence. It aimed to examine further correlates of the Hubris-Humility Effect that shows men believe they are more intelligent than women. The DMIQ scores were correlated significantly with gender, psychometrically assessed IQ, and masculinity but not self-esteem or self-control. Stepwise regressions indicated that gender and gender role were the strongest predictors of DMIQ accounting for a third of the variance.
... OPERATIONS Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip DRUG INFO Drug Fact Sheets ... Operations Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip Drug Info Drug Fact Sheets ...
... OPERATIONS Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip DRUG INFO Drug Fact Sheets ... Operations Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip Drug Info Drug Fact Sheets ...
... OPERATIONS Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip DRUG INFO Drug Fact Sheets ... Operations Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip Drug Info Drug Fact Sheets ...
Borges, Nicole J; Thompson, Britta M; Roman, Brenda J; Townsend, Mark H; Carchedi, Lisa R; Cluver, Jeff S; Frank, Julia B; Haidet, Paul M; Levine, Ruth E
2015-12-01
This study examined the relationship between team emotional intelligence, quality of team interactions, and gender. Psychiatry clerkship students participating in Team-Based Learning (TBL, n = 484) or no TBL (control, n = 265) completed the Workgroup Emotional Intelligence Profile (WEIP-S) and the Team Performance Scale (TPS). Significant correlations (p < 0.01) existed between quality of team interactions (i.e., TPS) and team emotional intelligence (i.e., WEIP-S) subscales, but not gender. Control and TBL groups experienced significant increases in WEIP-S subscales pre to post (p < 0.01, η (2) = .08), with the TBL group experiencing significantly higher gains in three of four subscales. Control group scored higher on TPS. A significant relationship exists between team emotional intelligence and quality of team interactions. Gender was unrelated to TPS or WEIP-S subscales. TBL group experienced higher gains in WEIP-S subscales while the control group experienced slightly higher TPS scores. Results suggest implications for medical educators who use TBL.
Using generic tool kits to build intelligent systems
NASA Technical Reports Server (NTRS)
Miller, David J.
1994-01-01
The Intelligent Systems and Robots Center at Sandia National Laboratories is developing technologies for the automation of processes associated with environmental remediation and information-driven manufacturing. These technologies, which focus on automated planning and programming and sensor-based and model-based control, are used to build intelligent systems which are able to generate plans of action, program the necessary devices, and use sensors to react to changes in the environment. By automating tasks through the use of programmable devices tied to computer models which are augmented by sensing, requirements for faster, safer, and cheaper systems are being satisfied. However, because of the need for rapid cost-effect prototyping and multi-laboratory teaming, it is also necessary to define a consistent approach to the construction of controllers for such systems. As a result, the Generic Intelligent System Controller (GISC) concept has been developed. This concept promotes the philosophy of producing generic tool kits which can be used and reused to build intelligent control systems.
Creating high-purity angular-momentum-state Rydberg atoms by a pair of unipolar laser pulses
NASA Astrophysics Data System (ADS)
Xin, PeiPei; Cheng, Hong; Zhang, ShanShan; Wang, HanMu; Xu, ZiShan; Liu, HongPing
2018-04-01
We propose a method of producing high-purity angular-momentum-state Rydberg atoms by a pair of unipolar laser pulses. The first positive-polarity optical half-cycle pulse is used to prepare an excited-state wave packet while the second one is less intense, but with opposite polarity and time delayed, and is employed to drag back the escaping free electron and clip the shape of the bound Rydberg wave packet, selectively increasing or decreasing a fraction of the angular-momentum components. An intelligent choice of laser parameters such as phase and amplitude helps us to control the orbital-angular-momentum composition of an electron wave packet with more facility; thus, a specified angular-momentum state with high purity can be achieved. This scheme of producing high-purity angular-momentum-state Rydberg atoms has significant application in quantum-information processing.
Quantum-enhanced deliberation of learning agents using trapped ions
NASA Astrophysics Data System (ADS)
Dunjko, V.; Friis, N.; Briegel, H. J.
2015-02-01
A scheme that successfully employs quantum mechanics in the design of autonomous learning agents has recently been reported in the context of the projective simulation (PS) model for artificial intelligence. In that approach, the key feature of a PS agent, a specific type of memory which is explored via random walks, was shown to be amenable to quantization, allowing for a speed-up. In this work we propose an implementation of such classical and quantum agents in systems of trapped ions. We employ a generic construction by which the classical agents are ‘upgraded’ to their quantum counterparts by a nested process of adding coherent control, and we outline how this construction can be realized in ion traps. Our results provide a flexible modular architecture for the design of PS agents. Furthermore, we present numerical simulations of simple PS agents which analyze the robustness of our proposal under certain noise models.
NASA Astrophysics Data System (ADS)
Cui, Gaoying; Fan, Jie; Qin, Yuchen; Wang, Dong; Chen, Guangyan
2017-05-01
In order to promote the effective use of demand response load side resources, promote the interaction between supply and demand, enhance the level of customer service and achieve the overall utilization of energy, this paper briefly explain the background significance of design demand response information platform and current situation of domestic and foreign development; Analyse the new demand of electricity demand response combined with the application of Internet and big data technology; Design demand response information platform architecture, construct demand responsive system, analyse process of demand response strategy formulate and intelligent execution implement; study application which combined with the big data, Internet and demand response technology; Finally, from information interaction architecture, control architecture and function design perspective design implementation of demand response information platform, illustrate the feasibility of the proposed platform design scheme implemented in a certain extent.
Fire Play: ICCARUS--Intelligent Command and Control, Acquisition and Review Using Simulation
ERIC Educational Resources Information Center
Powell, James; Wright, Theo; Newland, Paul; Creed, Chris; Logan, Brian
2008-01-01
Is it possible to educate a fire officer to deal intelligently with the command and control of a major fire event he will never have experienced? The authors of this paper believe there is, and present here just one solution to this training challenge. It involves the development of an intelligent simulation based upon computer managed interactive…
... OPERATIONS Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip DRUG INFO Drug Fact Sheets ... Operations Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip Drug Info Drug Fact Sheets ...
Large Efficient Intelligent Heating Relay Station System
NASA Astrophysics Data System (ADS)
Wu, C. Z.; Wei, X. G.; Wu, M. Q.
2017-12-01
The design of large efficient intelligent heating relay station system aims at the improvement of the existing heating system in our country, such as low heating efficiency, waste of energy and serious pollution, and the control still depends on the artificial problem. In this design, we first improve the existing plate heat exchanger. Secondly, the ATM89C51 is used to control the whole system and realize the intelligent control. The detection part is using the PT100 temperature sensor, pressure sensor, turbine flowmeter, heating temperature, detection of user end liquid flow, hydraulic, and real-time feedback, feedback signal to the microcontroller through the heating for users to adjust, realize the whole system more efficient, intelligent and energy-saving.
Rice-obot 1: An intelligent autonomous mobile robot
NASA Technical Reports Server (NTRS)
Defigueiredo, R.; Ciscon, L.; Berberian, D.
1989-01-01
The Rice-obot I is the first in a series of Intelligent Autonomous Mobile Robots (IAMRs) being developed at Rice University's Cooperative Intelligent Mobile Robots (CIMR) lab. The Rice-obot I is mainly designed to be a testbed for various robotic and AI techniques, and a platform for developing intelligent control systems for exploratory robots. Researchers present the need for a generalized environment capable of combining all of the control, sensory and knowledge systems of an IAMR. They introduce Lisp-Nodes as such a system, and develop the basic concepts of nodes, messages and classes. Furthermore, they show how the control system of the Rice-obot I is implemented as sub-systems in Lisp-Nodes.
An intelligent training system for payload-assist module deploys
NASA Technical Reports Server (NTRS)
Loftin, R. Bowen; Wang, Lui; Baffes, Paul; Rua, Monica
1987-01-01
An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The Payload-Assist Module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system has, so far, proven to be a potentially valuable addition to the training tools available for training Flight Dynamics Officers in shuttle ground control. The authors are convinced that the basic structure of PD/ICAT can be extended to form a general architecture for intelligent training systems for training flight controllers and crew members in the performance of complex, mission-critical tasks.
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.
Modeling of Feedback Stabilization of External MHD Modes in Toroidal Geometry
NASA Astrophysics Data System (ADS)
Chu, M. S.; Chance, M. S.; Okabayashi, M.
2000-10-01
The intelligent shell feedback scheme(C.M. Bishop, Plasma Phys. Contr. Nucl. Fusion 31), 1179 (1989). seeks to utilize external coils to suppress the unstable MHD modes slowed down by the resistive shell. We present a new formulation and numerical results of the interaction between the plasma and its outside vacuum region, with complete plasma response and the inclusion of a resistive vessel in general toroidal geometry. This is achieved by using the Green's function technique, which is a generalization of that previously used for the VACUUM(M.S. Chance, Phys. Plasmas 4), 2161 (1997). code and coupled with the ideal MHD code GATO. The effectiveness of different realizations of the intelligent shell concept is gauged by their ability to minimize the available free energy to drive the MHD mode. Computations indicate poloidal coverage of 30% of the total resistive wall surface area and 6 or 7 segments of ``intelligent coil'' arrays superimposed on the resistive wall will allow recovery of up to 90% the effectiveness of the ideal shell in stabilizing the ideal external kink.
iHelp: an intelligent online helpdesk system.
Wang, Dingding; Li, Tao; Zhu, Shenghuo; Gong, Yihong
2011-02-01
Due to the importance of high-quality customer service, many companies use intelligent helpdesk systems (e.g., case-based systems) to improve customer service quality. However, these systems face two challenges: 1) Case retrieval measures: most case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases and 2) result representation: most case-based systems return a list of past cases ranked by their relevance to a new request, and customers have to go through the list and examine the cases one by one to identify their desired cases. To address these challenges, we develop iHelp, an intelligent online helpdesk system, to automatically find problem-solution patterns from the past customer-representative interactions. When a new customer request arrives, iHelp searches and ranks the past cases based on their semantic relevance to the request, groups the relevant cases into different clusters using a mixture language model and symmetric matrix factorization, and summarizes each case cluster to generate recommended solutions. Case and user studies have been conducted to show the full functionality and the effectiveness of iHelp.
[Intelligent watch system for health monitoring based on Bluetooth low energy technology].
Wang, Ji; Guo, Hailiang; Ren, Xiaoli
2017-08-01
According to the development status of wearable technology and the demand of intelligent health monitoring, we studied the multi-function integrated smart watches solution and its key technology. First of all, the sensor technology with high integration density, Bluetooth low energy (BLE) and mobile communication technology were integrated and used in develop practice. Secondly, for the hardware design of the system in this paper, we chose the scheme with high integration density and cost-effective computer modules and chips. Thirdly, we used real-time operating system FreeRTOS to develop the friendly graphical interface interacting with touch screen. At last, the high-performance application software which connected with BLE hardware wirelessly and synchronized data was developed based on android system. The function of this system included real-time calendar clock, telephone message, address book management, step-counting, heart rate and sleep quality monitoring and so on. Experiments showed that the collecting data accuracy of various sensors, system data transmission capacity, the overall power consumption satisfy the production standard. Moreover, the system run stably with low power consumption, which could realize intelligent health monitoring effectively.
Synthetic biology routes to bio-artificial intelligence.
Nesbeth, Darren N; Zaikin, Alexey; Saka, Yasushi; Romano, M Carmen; Giuraniuc, Claudiu V; Kanakov, Oleg; Laptyeva, Tetyana
2016-11-30
The design of synthetic gene networks (SGNs) has advanced to the extent that novel genetic circuits are now being tested for their ability to recapitulate archetypal learning behaviours first defined in the fields of machine and animal learning. Here, we discuss the biological implementation of a perceptron algorithm for linear classification of input data. An expansion of this biological design that encompasses cellular 'teachers' and 'students' is also examined. We also discuss implementation of Pavlovian associative learning using SGNs and present an example of such a scheme and in silico simulation of its performance. In addition to designed SGNs, we also consider the option to establish conditions in which a population of SGNs can evolve diversity in order to better contend with complex input data. Finally, we compare recent ethical concerns in the field of artificial intelligence (AI) and the future challenges raised by bio-artificial intelligence (BI). © 2016 The Author(s). This is an open access article published by Portland Press Limited on behalf of the Biochemical Society and distributed under the Creative Commons Attribution License 4.0 (CC BY).
Secure, Autonomous, Intelligent Controller for Integrating Distributed Sensor Webs
NASA Technical Reports Server (NTRS)
Ivancic, William D.
2007-01-01
This paper describes the infrastructure and protocols necessary to enable near-real-time commanding, access to space-based assets, and the secure interoperation between sensor webs owned and controlled by various entities. Select terrestrial and aeronautics-base sensor webs will be used to demonstrate time-critical interoperability between integrated, intelligent sensor webs both terrestrial and between terrestrial and space-based assets. For this work, a Secure, Autonomous, Intelligent Controller and knowledge generation unit is implemented using Virtual Mission Operation Center technology.
The real-time control of planetary rovers through behavior modification
NASA Technical Reports Server (NTRS)
Miller, David P.
1991-01-01
It is not yet clear of what type, and how much, intelligence is needed for a planetary rover to function semi-autonomously on a planetary surface. Current designs assume an advanced AI system that maintains a detailed map of its journeys and the surroundings, and that carefully calculates and tests every move in advance. To achieve these abilities, and because of the limitations of space-qualified electronics, the supporting rover is quite sizable, massing a large fraction of a ton, and requiring technology advances in everything from power to ground operations. An alternative approach is to use a behavior driven control scheme. Recent research has shown that many complex tasks may be achieved by programming a robot with a set of behaviors and activation or deactivating a subset of those behaviors as required by the specific situation in which the robot finds itself. Behavior control requires much less computation than is required by tradition AI planning techniques. The reduced computation requirements allows the entire rover to be scaled down as appropriate (only down-link communications and payload do not scale under these circumstances). The missions that can be handled by the real-time control and operation of a set of small, semi-autonomous, interacting, behavior-controlled planetary rovers are discussed.
Control of a HexaPOD treatment couch for robot-assisted radiotherapy.
Hermann, Christian; Ma, Lei; Wilbert, Jürgen; Baier, Kurt; Schilling, Klaus
2012-10-01
Moving tumors, for example in the vicinity of the lungs, pose a challenging problem in radiotherapy, as healthy tissue should not be irradiated. Apart from gating approaches, one standard method is to irradiate the complete volume within which a tumor moves plus a safety margin containing a considerable volume of healthy tissue. This work deals with a system for tumor motion compensation using the HexaPOD® robotic treatment couch (Medical Intelligence GmbH, Schwabmünchen, Germany). The HexaPOD, carrying the patient during treatment, is instructed to perform translational movements such that the tumor motion, from the beams-eye view of the linear accelerator, is eliminated. The dynamics of the HexaPOD are characterized by time delays, saturations, and other non-linearities that make the design of control a challenging task. The focus of this work lies on two control methods for the HexaPOD that can be used for reference tracking. The first method uses a model predictive controller based on a model gained through system identification methods, and the second method uses a position control scheme useful for reference tracking. We compared the tracking performance of both methods in various experiments with real hardware using ideal reference trajectories, prerecorded patient trajectories, and human volunteers whose breathing motion was compensated by the system.
F-15 IFCS: Intelligent Flight Control System
NASA Technical Reports Server (NTRS)
Bosworth, John
2007-01-01
This viewgraph presentation describes the F-15 Intelligent Flight Control System (IFCS). The goals of this project include: 1) Demonstrate revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions; and 2) Demonstrate advance neural network-based flight control technology for new aerospace systems designs.
Fluid intelligence and brain functional organization in aging yoga and meditation practitioners
Gard, Tim; Taquet, Maxime; Dixit, Rohan; Hölzel, Britta K.; de Montjoye, Yves-Alexandre; Brach, Narayan; Salat, David H.; Dickerson, Bradford C.; Gray, Jeremy R.; Lazar, Sara W.
2014-01-01
Numerous studies have documented the normal age-related decline of neural structure, function, and cognitive performance. Preliminary evidence suggests that meditation may reduce decline in specific cognitive domains and in brain structure. Here we extended this research by investigating the relation between age and fluid intelligence and resting state brain functional network architecture using graph theory, in middle-aged yoga and meditation practitioners, and matched controls. Fluid intelligence declined slower in yoga practitioners and meditators combined than in controls. Resting state functional networks of yoga practitioners and meditators combined were more integrated and more resilient to damage than those of controls. Furthermore, mindfulness was positively correlated with fluid intelligence, resilience, and global network efficiency. These findings reveal the possibility to increase resilience and to slow the decline of fluid intelligence and brain functional architecture and suggest that mindfulness plays a mechanistic role in this preservation. PMID:24795629
NASA Technical Reports Server (NTRS)
Erickson, Jon D. (Editor)
1992-01-01
The present volume on cooperative intelligent robotics in space discusses sensing and perception, Space Station Freedom robotics, cooperative human/intelligent robot teams, and intelligent space robotics. Attention is given to space robotics reasoning and control, ground-based space applications, intelligent space robotics architectures, free-flying orbital space robotics, and cooperative intelligent robotics in space exploration. Topics addressed include proportional proximity sensing for telerobots using coherent lasar radar, ground operation of the mobile servicing system on Space Station Freedom, teleprogramming a cooperative space robotic workcell for space stations, and knowledge-based task planning for the special-purpose dextrous manipulator. Also discussed are dimensions of complexity in learning from interactive instruction, an overview of the dynamic predictive architecture for robotic assistants, recent developments at the Goddard engineering testbed, and parallel fault-tolerant robot control.
Hurtado, M M; Triviño, M; Arnedo, M; Roldán, G; Tudela, P
2016-12-30
This research explored the relationship between executive functions (working memory and reasoning subtests of the Wechsler Adult Intelligence Scale, Trail Making and Stroop tests, fluency and planning tasks, and Wisconsin Card Sorting Test) and emotional intelligence measured by the Mayer-Salovey-Caruso Emotional Intelligence Test in patients with schizophrenia or borderline personality disorder compared to a control group. As expected, both clinical groups performed worse than the control group in executive functions and emotional intelligence, although the impairment was greater in the borderline personality disorder group. Executive functions significantly correlated with social functioning. Results are discussed in relation to the brain circuits that mediate executive functions and emotional intelligence and the findings obtained with other models of social cognition. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Context-Dependent Upper Limb Prosthesis Control for Natural and Robust Use.
Amsuess, Sebastian; Vujaklija, Ivan; Goebel, Peter; Roche, Aidan D; Graimann, Bernhard; Aszmann, Oskar C; Farina, Dario
2016-07-01
Pattern recognition and regression methods applied to the surface EMG have been used for estimating the user intended motor tasks across multiple degrees of freedom (DOF), for prosthetic control. While these methods are effective in several conditions, they are still characterized by some shortcomings. In this study we propose a methodology that combines these two approaches for mutually alleviating their limitations. This resulted in a control method capable of context-dependent movement estimation that switched automatically between sequential (one DOF at a time) or simultaneous (multiple DOF) prosthesis control, based on an online estimation of signal dimensionality. The proposed method was evaluated in scenarios close to real-life situations, with the control of a physical prosthesis in applied tasks of varying difficulties. Test prostheses were individually manufactured for both able-bodied and transradial amputee subjects. With these prostheses, two amputees performed the Southampton Hand Assessment Procedure test with scores of 58 and 71 points. The five able-bodied individuals performed standardized tests, such as the box&block and clothes pin test, reducing the completion times by up to 30%, with respect to using a state-of-the-art pure sequential control algorithm. Apart from facilitating fast simultaneous movements, the proposed control scheme was also more intuitive to use, since human movements are predominated by simultaneous activations across joints. The proposed method thus represents a significant step towards intelligent, intuitive and natural control of upper limb prostheses.
Intelligent routing protocol for ad hoc wireless network
NASA Astrophysics Data System (ADS)
Peng, Chaorong; Chen, Chang Wen
2006-05-01
A novel routing scheme for mobile ad hoc networks (MANETs), which combines hybrid and multi-inter-routing path properties with a distributed topology discovery route mechanism using control agents is proposed in this paper. In recent years, a variety of hybrid routing protocols for Mobile Ad hoc wireless networks (MANETs) have been developed. Which is proactively maintains routing information for a local neighborhood, while reactively acquiring routes to destinations beyond the global. The hybrid protocol reduces routing discovery latency and the end-to-end delay by providing high connectivity without requiring much of the scarce network capacity. On the other side the hybrid routing protocols in MANETs likes Zone Routing Protocol still need route "re-discover" time when a route between zones link break. Sine the topology update information needs to be broadcast routing request on local zone. Due to this delay, the routing protocol may not be applicable for real-time data and multimedia communication. We utilize the advantages of a clustering organization and multi-routing path in routing protocol to achieve several goals at the same time. Firstly, IRP efficiently saves network bandwidth and reduces route reconstruction time when a routing path fails. The IRP protocol does not require global periodic routing advertisements, local control agents will automatically monitor and repair broke links. Secondly, it efficiently reduces congestion and traffic "bottlenecks" for ClusterHeads in clustering network. Thirdly, it reduces significant overheads associated with maintaining clusters. Fourthly, it improves clusters stability due to dynamic topology changing frequently. In this paper, we present the Intelligent Routing Protocol. First, we discuss the problem of routing in ad hoc networks and the motivation of IRP. We describe the hierarchical architecture of IRP. We describe the routing process and illustrate it with an example. Further, we describe the control manage mechanisms, which are used to control active route and reduce the traffic amount in the route discovery procedure. Finial, the numerical experiments are given to show the effectiveness of IRP routing protocol.
Intelligent building system for airport
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ancevic, M.
1997-11-01
The Munich airport uses a state-of-the-art intelligent building management system to control systems such as HVAC, runway lights, baggage handling, etc. Planning the new Munich II international airport provided a unique opportunity to use the latest state-of-the-art technical systems, while integrating their control through a single intelligent building management system. Opened in 1992, the airport is Germany`s second-largest airport after Frankfurt. The airport is staffed by 16,000 employees and can handle 17 million passengers a year. The sprawling site encompasses more than 120 buildings. The airport`s distributed control system is specifically designed to optimize the complex`s unique range of functions,more » while providing a high degree of comfort, convenience and safety for airport visitors. With the capacity to control 200,000 points, this system controls more than 112,000 points and integrates 13 major subsystems from nine different vendors. It provides convenient, accessible control of everything including the complex`s power plant, HVAC Control, the terminal`s people-moving functions, interior lighting controls, runway lights, baggage forwarding systems, elevators, and boarding bridges. The airport was named 1993 intelligent building of the year by the Intelligent Buildings Institute Foundation. Its building management system is a striking example of the degree to which a building complex`s functions can be integrated for greater operational control and efficiency.« less
[Control of intelligent car based on electroencephalogram and neurofeedback].
Li, Song; Xiong, Xin; Fu, Yunfa
2018-02-01
To improve the performance of brain-controlled intelligent car based on motor imagery (MI), a method based on neurofeedback (NF) with electroencephalogram (EEG) for controlling intelligent car is proposed. A mental strategy of MI in which the energy column diagram of EEG features related to the mental activity is presented to subjects with visual feedback in real time to train them to quickly master the skills of MI and regulate their EEG activity, and combination of multi-features fusion of MI and multi-classifiers decision were used to control the intelligent car online. The average, maximum and minimum accuracy of identifying instructions achieved by the trained group (trained by the designed feedback system before the experiment) were 85.71%, 90.47% and 76.19%, respectively and the corresponding accuracy achieved by the control group (untrained) were 73.32%, 80.95% and 66.67%, respectively. For the trained group, the average, longest and shortest time consuming were 92 s, 101 s, and 85 s, respectively, while for the control group the corresponding time were 115.7 s, 120 s, and 110 s, respectively. According to the results described above, it is expected that this study may provide a new idea for the follow-up development of brain-controlled intelligent robot by the neurofeedback with EEG related to MI.
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.
2007-09-01
AFRL-RZ-WP-TP-2008-2044 ADVANCED, ADAPTIVE, MODULAR, DISTRIBUTED, GENERIC UNIVERSAL FADEC FRAMEWORK FOR INTELLIGENT PROPULSION CONTROL...GRANT NUMBER 4. TITLE AND SUBTITLE ADVANCED, ADAPTIVE, MODULAR, DISTRIBUTED, GENERIC UNIVERSAL FADEC FRAMEWORK FOR INTELLIGENT PROPULSION... FADEC is unique and expensive to develop, produce, maintain, and upgrade for its particular application. Each FADEC is a centralized system, with a
Intelligent lead: a novel HRI sensor for guide robots.
Cho, Keum-Bae; Lee, Beom-Hee
2012-01-01
This paper addresses the introduction of a new Human Robot Interaction (HRI) sensor for guide robots. Guide robots for geriatric patients or the visually impaired should follow user's control command, keeping a certain desired distance allowing the user to work freely. Therefore, it is necessary to acquire control commands and a user's position on a real-time basis. We suggest a new sensor fusion system to achieve this objective and we will call this sensor the "intelligent lead". The objective of the intelligent lead is to acquire a stable distance from the user to the robot, speed-control volume and turn-control volume, even when the robot platform with the intelligent lead is shaken on uneven ground. In this paper we explain a precise Extended Kalman Filter (EKF) procedure for this. The intelligent lead physically consists of a Kinect sensor, the serial linkage attached with eight rotary encoders, and an IMU (Inertial Measurement Unit) and their measurements are fused by the EKF. A mobile robot was designed to test the performance of the proposed sensor system. After installing the intelligent lead in the mobile robot, several tests are conducted to verify that the mobile robot with the intelligent lead is capable of achieving its goal points while maintaining the appropriate distance between the robot and the user. The results show that we can use the intelligent lead proposed in this paper as a new HRI sensor joined a joystick and a distance measure in the mobile environments such as the robot and the user are moving at the same time.
Research to Assembly Scheme for Satellite Deck Based on Robot Flexibility Control Principle
NASA Astrophysics Data System (ADS)
Guo, Tao; Hu, Ruiqin; Xiao, Zhengyi; Zhao, Jingjing; Fang, Zhikai
2018-03-01
Deck assembly is critical quality control point in final satellite assembly process, and cable extrusion and structure collision problems in assembly process will affect development quality and progress of satellite directly. Aimed at problems existing in deck assembly process, assembly project scheme for satellite deck based on robot flexibility control principle is proposed in this paper. Scheme is introduced firstly; secondly, key technologies on end force perception and flexible docking control in the scheme are studied; then, implementation process of assembly scheme for satellite deck is described in detail; finally, actual application case of assembly scheme is given. Result shows that compared with traditional assembly scheme, assembly scheme for satellite deck based on robot flexibility control principle has obvious advantages in work efficiency, reliability and universality aspects etc.
Methamphetamine Lab Incidents, 2004-2014
... OPERATIONS Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip DRUG INFO Drug Fact Sheets ... Operations Diversion Control Programs Most Wanted Fugitives Training Intelligence Submit a Tip Drug Info Drug Fact Sheets ...
NASA Astrophysics Data System (ADS)
Mohamed, Ahmed
Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.
ERIC Educational Resources Information Center
Jaramillo, James Anthony Montrose
2013-01-01
Both Pre-K and K-3rd grade exceptional or talented children/students not only want but need more of an "accommodative" ambiance where their senses are given novel multiple-intelligences data so that they can continue to intellectually grow with respect to Piaget, Erickson, and Vygotsky's developmental schemes. Thus, to do this requires us to…
A knowledge-based tool for multilevel decomposition of a complex design problem
NASA Technical Reports Server (NTRS)
Rogers, James L.
1989-01-01
Although much work has been done in applying artificial intelligence (AI) tools and techniques to problems in different engineering disciplines, only recently has the application of these tools begun to spread to the decomposition of complex design problems. A new tool based on AI techniques has been developed to implement a decomposition scheme suitable for multilevel optimization and display of data in an N x N matrix format.
Arslan, Ruben C; Penke, Lars; Johnson, Wendy; Iacono, William G; McGue, Matt
2014-01-01
Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father's age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents' trait levels measured with the same precision as offspring's. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents' intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (<1% of variance explained) on intelligence. We discuss future avenues for studies of paternal age effects and suggest that stronger research designs are needed to rule out confounding factors involving birth order and the Flynn effect.
An application of artificial intelligence theory to reconfigurable flight control
NASA Technical Reports Server (NTRS)
Handelman, David A.
1987-01-01
Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.
Song, Yuan; Liu, Ya; Pan, Yun; Yuan, Xiaofeng; Chang, Pengyu; Tian, Yuan; Cui, Weiwei
2018-01-01
Background Low birth weight infant (LBWIs) are prone to mental and behavioural problems. As an important constituent of the brain and retina, long chain polyunsaturated fatty acids are essential for foetal infant mental and visual development. The effect of lactation supplemented with long chain polyunsaturated fatty acids (LCPUFA) on the improvement of intelligence in low birth weight children requires further validation. Methods In this study, a comprehensive search of multiple databases was performed to identify studies focused the association between intelligence and long chain polyunsaturated fatty acid supplementation in LBWIs. Studies that compared the Bayley Scales of Infant Development (BSID) or the Wechsler Abbreviated Scale of Intelligence for Children (WISC) scores between LBWIs who were supplemented and controls that were not supplemented with LCPUFA during lactation were selected for inclusion in the meta-analysis. Results The main outcome was the mean difference in the mental development index (MDI) and psychomotor development index (PDI) of the BSID and the full scale intelligence quotient (FSIQ), verbal intelligence quotient (VIQ) and performance intelligence quotient (PIQ) of the WISC between LBWIs and controls. Our findings indicated that the mean BSID or WISC scores in LBWIs did not differ between the supplemented groups and controls. Conclusion This meta-analysis does not reveal that LCPUFA supplementation has a significant impact on the level of intelligence in LBWIs. PMID:29634752
Intelligent Transportation Systems (ITS) plan for Canada : en route to intelligent mobility
DOT National Transportation Integrated Search
1999-11-01
Intelligent Transportation Systems (ITS) include the application of advanced information processing, communications, sensor and control technologies and management strategies in an integrated manner to improve the functioning of the transportation sy...
Intelligent Intersection Traffic Control Laboratory Fact Sheet
DOT National Transportation Integrated Search
2006-07-27
The Intelligent Intersection 11:affic Control Laboratory (IITCL) is an outdoor facility that supports the Federal Highway Administration's (FHWA) various research programs and research activities conducted by other U.S. Department of 11:ansportation ...
NASA Astrophysics Data System (ADS)
An, Meiyan; Wang, Zhaokui; Zhang, Yulin
2017-01-01
The self-organizing control strategy for asteroid intelligent detection swarm, which is considered as a space application instance of intelligent swarm, is developed. The leader-follower model for the asteroid intelligent detection swarm is established, and the further analysis is conducted for massive asteroid and small asteroid. For a massive asteroid, the leader spacecraft flies under the gravity field of the asteroid. For a small asteroid, the asteroid gravity is negligible, and a trajectory planning method is proposed based on elliptic cavity virtual potential field. The self-organizing control strategy for the follower spacecraft is developed based on a mechanism of velocity planning and velocity tracking. The simulation results show that the self-organizing control strategy is valid for both massive asteroid and small asteroid, and the exploration swarm forms a stable configuration.
Ohtani, Toshiyuki; Nestor, Paul G; Bouix, Sylvain; Newell, Dominick; Melonakos, Eric D; McCarley, Robert W; Shenton, Martha E; Kubicki, Marek
2017-01-26
We combined diffusion tension imaging (DTI) of prefrontal white matter integrity and neuropsychological measures to examine the functional neuroanatomy of human intelligence. Healthy participants completed the Wechsler Adult Intelligence Scale-Third Edition (WAIS-III) along with neuropsychological tests of attention and executive control, as measured by Trail Making Test (TMT) and Wisconsin Card Sorting Test (WCST). Stochastic tractography, considered the most effective DTI method, quantified white matter integrity of the medial orbital frontal cortex (mOFC) and rostral anterior cingulate cortex (rACC) circuitry. Based on prior studies, we hypothesized that posterior mOFC-rACC connections may play a key structural role linking attentional control processes and intelligence. Behavioral results provided strong support for this hypothesis, specifically linking attentional control processes, measured by Trails B and WCST perseverative errors, to intelligent quotient (IQ). Hierarchical regression results indicated left posterior mOFC-rACC fractional anisotropy (FA) and Trails B performance time, but not WCST perseverative errors, each contributed significantly to IQ, accounting for approximately 33.95-51.60% of the variance in IQ scores. These findings suggested that left posterior mOFC-rACC white matter connections may play a key role in supporting the relationship of executive functions of attentional control and general intelligence in healthy cognition. Copyright © 2016. Published by Elsevier Ltd.
Control algorithms of SONET integrated self-healing networks
NASA Astrophysics Data System (ADS)
Hasegawa, Satoshi; Okaoue, Yasuyo; Egawa, Takashi; Sakauchi, Hideki
1994-01-01
As the deployment of high-speed fiber transmission systems has been accelerated, they are widely recognized as a firm infrastructure of information society. Under this circumstance, the importance of network survivability has been increasing rapidly in these days. In SONET, the self-healing networks have been highlighted as one of the most advanced mechanisms to realize SONET survivable networks. Several schemes have been proposed and studied actively due to a rapid progress on the development of highly intelligent NE's. Among them in this paper, a DCS based distributed self-healing network is discussed from a viewpoint of its control algorithms. Specifically, our self-healing algorithm called TRANS is explained in detail, which possesses such desirable features as providing fast and flexible restoration with line and path level restoration applied to an individual STS-1 channel, capability to handle multiple and even node failures, and so on. Both software simulation and hardware experiment verify that TRANS works properly in a real distributed environment, the result of which is shown in the paper. In addition, the combined use of TRANS and the ring restoration control is proposed taking into account the use in a practical SONET.
NASA Astrophysics Data System (ADS)
Zhang, Chongfu; Wang, Zhengsuan; Jin, Wei; Qiu, Kun
2012-11-01
A novel realization method of the optical virtual private networks (OVPN) over multiprotocol label switching/optical packet switching (MPLS/OPS) networks is proposed. In this scheme, the introduction of MPLS control plane makes OVPN over OPS networks more reliable and easier; OVPN makes use of the concept of high reconfiguration of light-paths offered by MPLS, to set up secure tunnels of high bandwidth across intelligent OPS networks. Through resource management, the signal mechanism, connection control, and the architecture of the creation and maintenance of OVPN are efficiently realized. We also present an OVPN architecture with two traffic priorities, which is used to analyze the capacity, throughput, delay time of the proposed networks, and the packet loss rate performance of the OVPN over MPLS/OPS networks based on full mesh topology. The results validate the applicability of such reliable connectivity to high quality services in the OVPN over MPLS/OPS networks. Along with the results, the feasibility of the approach as the basis for the next generation networks is demonstrated and discussed.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1992-01-01
The theory of intelligent machines proposes a hierarchical organization for the functions of an autonomous robot based on the principle of increasing precision with decreasing intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed. The authors present a computer architecture that implements the lower two levels of the intelligent machine. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Execution-level controllers for motion and vision systems are briefly addressed, as well as the Petri net transducer software used to implement coordination-level functions. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Projective simulation for artificial intelligence
NASA Astrophysics Data System (ADS)
Briegel, Hans J.; de Las Cuevas, Gemma
2012-05-01
We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.
Projective simulation for artificial intelligence
Briegel, Hans J.; De las Cuevas, Gemma
2012-01-01
We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690
A collision model for safety evaluation of autonomous intelligent cruise control.
Touran, A; Brackstone, M A; McDonald, M
1999-09-01
This paper describes a general framework for safety evaluation of autonomous intelligent cruise control in rear-end collisions. Using data and specifications from prototype devices, two collision models are developed. One model considers a train of four cars, one of which is equipped with autonomous intelligent cruise control. This model considers the car in front and two cars following the equipped car. In the second model, none of the cars is equipped with the device. Each model can predict the possibility of rear-end collision between cars under various conditions by calculating the remaining distance between cars after the front car brakes. Comparing the two collision models allows one to evaluate the effectiveness of autonomous intelligent cruise control in preventing collisions. The models are then subjected to Monte Carlo simulation to calculate the probability of collision. Based on crash probabilities, an expected value is calculated for the number of cars involved in any collision. It is found that given the model assumptions, while equipping a car with autonomous intelligent cruise control can significantly reduce the probability of the collision with the car ahead, it may adversely affect the situation for the following cars.
Lucas, Victoria; Laschinger, Heather K Spence; Wong, Carol A
2008-11-01
To test a model linking nurses' perceptions of their nurse manager's emotionally intelligent leadership style and nurses' structural empowerment, and the impact of nurse manager span of control (number of direct reports) on the emotional intelligence/empowerment relationship. Hospital restructuring in the 1990s resulted in a dramatic reduction in nurse manager positions, yet nurse managers are critical to empowering nurses for professional practice. A descriptive correlational survey design was used to test the hypothesized model in two community hospitals in Ontario. Two hundred and three nurses from two hospitals returned useable questionnaires (68% response rate). Span of control was a significant moderator of the relationship between nurses perceptions of their managers' emotionally intelligent behaviour and feelings of workplace empowerment. The results suggest that even managers with strong emotional intelligence may not be able to empower their staff if their span of control is large. Every effort must be made to ensure that managers have reasonable spans of control that allow them to develop and use the leadership skill necessary for empowering their staff to practice to the full scope of their professional role.
Najafi, Mostafa; Akouchekian, Shahla; Ghaderi, Alireza; Mahaki, Behzad; Rezaei, Mariam
2017-01-01
Attention deficit and hyperactivity disorder (ADHD) is a common psychological problem during childhood. This study aimed to evaluate multiple intelligences profiles of children with ADHD in comparison with non-ADHD. This cross-sectional descriptive analytical study was done on 50 children of 6-13 years old in two groups of with and without ADHD. Children with ADHD were referred to Clinics of Child and Adolescent Psychiatry, Isfahan University of Medical Sciences, in 2014. Samples were selected based on clinical interview (based on Diagnostic and Statistical Manual of Mental Disorders IV and parent-teacher strengths and difficulties questionnaire), which was done by psychiatrist and psychologist. Raven intelligence quotient (IQ) test was used, and the findings were compared to the results of multiple intelligences test. Data analysis was done using a multivariate analysis of covariance using SPSS20 software. Comparing the profiles of multiple intelligence among two groups, there are more kinds of multiple intelligences in control group than ADHD group, a difference which has been more significant in logical, interpersonal, and intrapersonal intelligence ( P < 0.05). There was no significant difference with the other kinds of multiple intelligences in two groups ( P > 0.05). The IQ average score in the control group and ADHD group was 102.42 ± 16.26 and 96.72 ± 16.06, respectively, that reveals the negative effect of ADHD on IQ average value. There was an insignificance relationship between linguistic and naturalist intelligence ( P > 0.05). However, in other kinds of multiple intelligences, direct and significant relationships were observed ( P < 0.05). Since the levels of IQ (Raven test) and MI in control group were more significant than ADHD group, ADHD is likely to be associated with logical-mathematical, interpersonal, and intrapersonal profiles.
The relationship between emotional intelligence and task-switching in temporal lobe epilepsy.
Gul, Amara; Hussain, Imtiaz
2016-01-01
To examine the role of emotional intelligence (EI) in task-switching performance of patients with temporal lobe epilepsy (TLE). An experimental research design conducted at Sheikh Zayed Hospital, Rahim Yar Khan, Mayo and Services Hospital, Lahore, Pakistan from March 2013 to October 2014. Twenty-five patients with TLE and 25 healthy individuals from local community participated in the study. Participants completed measures of intelligence, EI, depression, anxiety, stress, and task-switching experiment. Patients and controls showed an average intelligence quotient, and normal levels of depression, anxiety, and stress. In contrast to controls, patients showed lower EI and impaired task-switching abilities. This result can be seen in the context of disintegrated white matter and cerebral connectivity in patients with TLE. Emotional intelligence was found to be a significant predictor of task-switching performance. Emotional intelligence is a potential marker of higher order cognitive functioning in patients with TLE.
77 FR 27202 - 36(b)(1) Arms Sales Notification
Federal Register 2010, 2011, 2012, 2013, 2014
2012-05-09
... includes: Electronic Warfare Systems, Command, Control, Communication, Computers and Intelligence/Communication, Navigational and Identifications (C4I/CNI), Autonomic Logistics Global Support System (ALGS... Systems, Command, Control, Communication, Computers and Intelligence/Communication, Navigational and...
An intelligent FFR with a self-adjustable ventilation fan.
Zhou, Song; Li, Hui; Shen, Shengnan; Li, Siyu; Wang, Wei; Zhang, Xiaotie; Yang, James
2017-11-01
This article presents an intelligent Filtering Facepiece Respirator (FFR) with a self-adjustable ventilation fan for improved comfort. The ventilation fan with an intelligent control aims to reduce temperature, relative humidity, and CO 2 concentrations inside the facepiece. Compared with a previous version of the FFR, the advantage of this new FFR is the intelligent control of the fan's rotation speed based on the change in temperature and relative humidity in the FFR dead space. The design of the control system utilizes an 8-bit, ultra-low power STC15W404AS microcontroller (HongJin technology, Shenzhen, China), and adopts a high-precision AM2320 device (AoSong electronic, Guangzhou, China) as temperature and relative humidity sensor so that control of temperature and relative humidity is realized in real time within the FFR dead space. The ventilation fan is intelligently driven and runs on a rechargeable lithium battery with a power-save mode that provides a correspondingly longer operational time. Meanwhile, the design is simplistic. Two experiments were performed to determine the best location to place the fan.
Hardware accelerator design for change detection in smart camera
NASA Astrophysics Data System (ADS)
Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Chaudhury, Santanu; Vohra, Anil
2011-10-01
Smart Cameras are important components in Human Computer Interaction. In any remote surveillance scenario, smart cameras have to take intelligent decisions to select frames of significant changes to minimize communication and processing overhead. Among many of the algorithms for change detection, one based on clustering based scheme was proposed for smart camera systems. However, such an algorithm could achieve low frame rate far from real-time requirements on a general purpose processors (like PowerPC) available on FPGAs. This paper proposes the hardware accelerator capable of detecting real time changes in a scene, which uses clustering based change detection scheme. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA board. Resulted frame rate is 30 frames per second for QVGA resolution in gray scale.
Pass-band reconfigurable spoof surface plasmon polaritons
NASA Astrophysics Data System (ADS)
Zhang, Hao Chi; He, Pei Hang; Gao, Xinxin; Tang, Wen Xuan; Cui, Tie Jun
2018-04-01
In this paper, we introduce a new scheme to construct the band-pass tunable filter based on the band-pass reconfigurable spoof surface plasmon polaritons (SPPs), whose cut-off frequencies at both sides of the passband can be tuned through changing the direct current (DC) bias of varactors. Compared to traditional technology (e.g. microstrip filters), the spoof SPP structure can provide more tight field confinement and more significant field enhancement, which is extremely valuable for many system applications. In order to achieve this scheme, we proposed a specially designed SPP filter integrated with varactors and DC bias feeding structure to support the spoof SPP passband reconfiguration. Furthermore, the full-wave simulated result verifies the outstanding performance on both efficiency and reconfiguration, which has the potential to be widely used in advanced intelligent systems.
[Intelligence level and structure in school age children with fetal growth restriction].
Ma, Jian; Ma, Hong-Wei; Tian, Xiao-Bo; Liu, Fang
2009-10-01
To study the intelligence level and structure in school age children with fetal growth restriction (FGR). The intelligence levels were tested by the Wechsler Children Scales of Intelligence (C-WISC) in 54 children with FGR and in 84 normal children. The full intelligence quotient (FIQ), verbal IQ (VIQ) and performance IQ (PIQ) in the FGR group were 105.9+/-10.3, 112.4+/-11.2 and 97.1+/-10.6 respectively, and they all were in a normal range. But the PIQ was significantly lower than that in the control group (104.8+/-10.5; p<0.001), and the picture arrangement and the decipher subtest scores were significantly lower than those in the control group (p<0.01). The scores of perception/organization and memory/attention factors in the FGR group were 99.8+/-11.1 and 116.3+/-14.4, respectively, which were inferior to those in the control group (104.6+/-11.5 and 113.4+/-14.5 respectively; p<0.05). The total intelligence level of children with FGR is normal, but there are imbalances in the intelligence structure and dysfunctions in performance ability related to right cerebral hemisphere. Performance trainings should be done from the infancy in children with FGR.
Speech Prosody Across Stimulus Types for Individuals with Parkinson's Disease.
K-Y Ma, Joan; Schneider, Christine B; Hoffmann, Rüdiger; Storch, Alexander
2015-01-01
Up to 89% of the individuals with Parkinson's disease (PD) experience speech problem over the course of the disease. Speech prosody and intelligibility are two of the most affected areas in hypokinetic dysarthria. However, assessment of these areas could potentially be problematic as speech prosody and intelligibility could be affected by the type of speech materials employed. To comparatively explore the effects of different types of speech stimulus on speech prosody and intelligibility in PD speakers. Speech prosody and intelligibility of two groups of individuals with varying degree of dysarthria resulting from PD was compared to that of a group of control speakers using sentence reading, passage reading and monologue. Acoustic analysis including measures on fundamental frequency (F0), intensity and speech rate was used to form a prosodic profile for each individual. Speech intelligibility was measured for the speakers with dysarthria using direct magnitude estimation. Difference in F0 variability between the speakers with dysarthria and control speakers was only observed in sentence reading task. Difference in the average intensity level was observed for speakers with mild dysarthria to that of the control speakers. Additionally, there were stimulus effect on both intelligibility and prosodic profile. The prosodic profile of PD speakers was different from that of the control speakers in the more structured task, and lower intelligibility was found in less structured task. This highlighted the value of both structured and natural stimulus to evaluate speech production in PD speakers.
Design of a robotic vehicle with self-contained intelligent wheels
NASA Astrophysics Data System (ADS)
Poulson, Eric A.; Jacob, John S.; Gunderson, Robert W.; Abbott, Ben A.
1998-08-01
The Center for Intelligent Systems has developed a small robotic vehicle named the Advanced Rover Chassis 3 (ARC 3) with six identical intelligent wheel units attached to a payload via a passive linkage suspension system. All wheels are steerable, so the ARC 3 can move in any direction while rotating at any rate allowed by the terrain and motors. Each intelligent wheel unit contains a drive motor, steering motor, batteries, and computer. All wheel units are identical, so manufacturing, programing, and spare replacement are greatly simplified. The intelligent wheel concept would allow the number and placement of wheels on the vehicle to be changed with no changes to the control system, except to list the position of all the wheels relative to the vehicle center. The task of controlling the ARC 3 is distributed between one master computer and the wheel computers. Tasks such as controlling the steering motors and calculating the speed of each wheel relative to the vehicle speed in a corner are dependent on the location of a wheel relative to the vehicle center and ar processed by the wheel computers. Conflicts between the wheels are eliminated by computing the vehicle velocity control in the master computer. Various approaches to this distributed control problem, and various low level control methods, have been explored.
ERIC Educational Resources Information Center
Safara, Maryam; Ghasemi, Pejman
2017-01-01
The aim of this study was to evaluate the efficacy of yoga on spiritual intelligence in air traffic controllers in Tehran flight control center. This was a quasi-experimental research and the study population includes all air traffic controllers in Tehran flight control center. The sample consisted of 40 people of the study population that were…
Algorithms for adaptive stochastic control for a class of linear systems
NASA Technical Reports Server (NTRS)
Toda, M.; Patel, R. V.
1977-01-01
Control of linear, discrete time, stochastic systems with unknown control gain parameters is discussed. Two suboptimal adaptive control schemes are derived: one is based on underestimating future control and the other is based on overestimating future control. Both schemes require little on-line computation and incorporate in their control laws some information on estimation errors. The performance of these laws is studied by Monte Carlo simulations on a computer. Two single input, third order systems are considered, one stable and the other unstable, and the performance of the two adaptive control schemes is compared with that of the scheme based on enforced certainty equivalence and the scheme where the control gain parameters are known.
Intelligent system of coordination and control for manufacturing
NASA Astrophysics Data System (ADS)
Ciortea, E. M.
2016-08-01
This paper wants shaping an intelligent system monitoring and control, which leads to optimizing material and information flows of the company. The paper presents a model for tracking and control system using intelligent real. Production system proposed for simulation analysis provides the ability to track and control the process in real time. Using simulation models be understood: the influence of changes in system structure, commands influence on the general condition of the manufacturing process conditions influence the behavior of some system parameters. Practical character consists of tracking and real-time control of the technological process. It is based on modular systems analyzed using mathematical models, graphic-analytical sizing, configuration, optimization and simulation.
Rule-based mechanisms of learning for intelligent adaptive flight control
NASA Technical Reports Server (NTRS)
Handelman, David A.; Stengel, Robert F.
1990-01-01
How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.
Intelligent cruise control field operational test : interim report
DOT National Transportation Integrated Search
1997-03-01
This interim document reports on a cooperative agreement between NHTSA and UMTRI entitled Intelligent Cruise Control (ICC) Field Operational Test (FOT). The overarching goal of the work is to characterize safety and comfort issues that are fundamenta...
Artificial intelligence in process control: Knowledge base for the shuttle ECS model
NASA Technical Reports Server (NTRS)
Stiffler, A. Kent
1989-01-01
The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.
Cognitive Science: Persistent Apes Are Intelligent Apes.
Eisenreich, Benjamin R; Hayden, Benjamin Y
2018-02-19
In humans, self-control is correlated with general intelligence; a new study finds that this correlation extends to chimpanzees as well. The new results highlight the cognitive bases of self-control and suggest a common evolutionary history for human and primate self-control. Copyright © 2018 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Chu, Rose W.; Mitchell, Christine M.
1993-01-01
In supervisory control systems such as satellite ground control, there is a need for human-centered automation where the focus is to understand and enhance the human-system interaction experience in the complex task environment. Operator support in the form of off-line intelligent tutoring and on-line intelligent aiding is one approach towards this effort. The tutor/aid paradigm is proposed here as a design approach that integrates the two aspects of operator support in one system for technically oriented adults in complex domains. This paper also presents GT-VITA, a proof-of-concept graphical, interactive, intelligent tutoring system that is a first attempt to illustrate the tutoring aspect of the tutor/aid paradigm in the domain of satellite ground control. Evaluation on GT-VITA is conducted with NASA personnel with very positive results. GT-VITA is presented being fielded as it is at Goddard Space Flight Center.
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.
NASA Technical Reports Server (NTRS)
Malin, Jane T.; Flores, Luis; Fleming, Land; Throop, Daiv
2002-01-01
A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center
A Human Factors Analysis of Proactive Support in Human-Robot Teaming
2015-09-28
teammate is remotely controlling a robot while working with an intelligent robot teammate ‘Mary’. Our main result shows that the subjects generally...IEEE/RSJ Intl. Conference on Intelligent Robots and Systems Conference Date: September 28, 2015 A Human Factors Analysis of Proactive Support in Human...human teammate is remotely controlling a robot while working with an intelligent robot teammate ‘Mary’. Our main result shows that the subjects
An overview of the artificial intelligence and expert systems component of RICIS
NASA Technical Reports Server (NTRS)
Feagin, Terry
1987-01-01
Artificial Intelligence and Expert Systems are the important component of RICIS (Research Institute and Information Systems) research program. For space applications, a number of problem areas that should be able to make good use of the above tools include: resource allocation and management, control and monitoring, environmental control and life support, power distribution, communications scheduling, orbit and attitude maintenance, redundancy management, intelligent man-machine interfaces and fault detection, isolation and recovery.
1990-06-01
the form of structured objects was first pioneered by Marvin Minsky . In his seminal article " A Framework for Representing Knowl- edge" he introduced... Minsky felt that the existing methods of knowledge representation were too finely grained and he proposed that knowledge is more than just a...not work" in realistic, complex domains. ( Minsky , 1981, pp. 95-128) According to Minsky "A frame is a data-structure for representing a stereo- typed
First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach.
Neocleous, Andreas C; Nicolaides, Kypros H; Schizas, Christos N
2016-09-01
The objective of this study is to examine the potential value of using machine learning techniques such as artificial neural network (ANN) schemes for the noninvasive estimation, at 11-13 weeks of gestation, the risk for euploidy, trisomy 21 (T21), and other chromosomal aneuploidies (O.C.A.), from suitable sonographic, biochemical markers, and other relevant data. A database(1) (1)The dataset can become available for academic purposes by communicating directly with the authors.
Strong Genetic Overlap Between Executive Functions and Intelligence
Engelhardt, Laura E.; Mann, Frank D.; Briley, Daniel A.; Church, Jessica A.; Harden, K. Paige; Tucker-Drob, Elliot M.
2016-01-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision-making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7-15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically-mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. PMID:27359131
Delamination detection using methods of computational intelligence
NASA Astrophysics Data System (ADS)
Ihesiulor, Obinna K.; Shankar, Krishna; Zhang, Zhifang; Ray, Tapabrata
2012-11-01
Abstract Reliable delamination prediction scheme is indispensable in order to prevent potential risks of catastrophic failures in composite structures. The existence of delaminations changes the vibration characteristics of composite laminates and hence such indicators can be used to quantify the health characteristics of laminates. An approach for online health monitoring of in-service composite laminates is presented in this paper that relies on methods based on computational intelligence. Typical changes in the observed vibration characteristics (i.e. change in natural frequencies) are considered as inputs to identify the existence, location and magnitude of delaminations. The performance of the proposed approach is demonstrated using numerical models of composite laminates. Since this identification problem essentially involves the solution of an optimization problem, the use of finite element (FE) methods as the underlying tool for analysis turns out to be computationally expensive. A surrogate assisted optimization approach is hence introduced to contain the computational time within affordable limits. An artificial neural network (ANN) model with Bayesian regularization is used as the underlying approximation scheme while an improved rate of convergence is achieved using a memetic algorithm. However, building of ANN surrogate models usually requires large training datasets. K-means clustering is effectively employed to reduce the size of datasets. ANN is also used via inverse modeling to determine the position, size and location of delaminations using changes in measured natural frequencies. The results clearly highlight the efficiency and the robustness of the approach.
NASA Astrophysics Data System (ADS)
Xiao, Jian; Luo, Xiaoping; Feng, Zhenfei; Zhang, Jinxin
2018-01-01
This work combines fuzzy logic and a support vector machine (SVM) with a principal component analysis (PCA) to create an artificial-intelligence system that identifies nanofluid gas-liquid two-phase flow states in a vertical mini-channel. Flow-pattern recognition requires finding the operational details of the process and doing computer simulations and image processing can be used to automate the description of flow patterns in nanofluid gas-liquid two-phase flow. This work uses fuzzy logic and a SVM with PCA to improve the accuracy with which the flow pattern of a nanofluid gas-liquid two-phase flow is identified. To acquire images of nanofluid gas-liquid two-phase flow patterns of flow boiling, a high-speed digital camera was used to record four different types of flow-pattern images, namely annular flow, bubbly flow, churn flow, and slug flow. The textural features extracted by processing the images of nanofluid gas-liquid two-phase flow patterns are used as inputs to various identification schemes such as fuzzy logic, SVM, and SVM with PCA to identify the type of flow pattern. The results indicate that the SVM with reduced characteristics of PCA provides the best identification accuracy and requires less calculation time than the other two schemes. The data reported herein should be very useful for the design and operation of industrial applications.
Design and implementation of green intelligent lights based on the ZigBee
NASA Astrophysics Data System (ADS)
Gan, Yong; Jia, Chunli; Zou, Dongyao; Yang, Jiajia; Guo, Qianqian
2013-03-01
By analysis of the low degree of intelligence of the traditional lighting control methods, the paper uses the singlechip microcomputer for the control core, and uses a pyroelectric infrared technology to detect the existence of the human body, light sensors to sense the light intensity; the interface uses infrared sensor module, photosensitive sensor module, relay module to transmit the signal, which based on ZigBee wireless network. The main function of the design is to realize that the lighting can intelligently adjust the brightness according to the indoor light intensity when people in door, and it can turn off the light when people left. The circuit and program design of this system is flexible, and the system achieves the effect of intelligent energy saving control.
EEG Control of a Virtual Helicopter in 3-Dimensional Space Using Intelligent Control Strategies
Royer, Audrey S.; Doud, Alexander J.; Rose, Minn L.
2011-01-01
Films like Firefox, Surrogates, and Avatar have explored the possibilities of using brain-computer interfaces (BCIs) to control machines and replacement bodies with only thought. Real world BCIs have made great progress toward that end. Invasive BCIs have enabled monkeys to fully explore 3-dimensional (3D) space using neuroprosthetics. However, non-invasive BCIs have not been able to demonstrate such mastery of 3D space. Here, we report our work, which demonstrates that human subjects can use a non-invasive BCI to fly a virtual helicopter to any point in a 3D world. Through use of intelligent control strategies, we have facilitated the realization of controlled flight in 3D space. We accomplished this through a reductionist approach that assigns subject-specific control signals to the crucial components of 3D flight. Subject control of the helicopter was comparable when using either the BCI or a keyboard. By using intelligent control strategies, the strengths of both the user and the BCI system were leveraged and accentuated. Intelligent control strategies in BCI systems such as those presented here may prove to be the foundation for complex BCIs capable of doing more than we ever imagined. PMID:20876032
EEG control of a virtual helicopter in 3-dimensional space using intelligent control strategies.
Royer, Audrey S; Doud, Alexander J; Rose, Minn L; He, Bin
2010-12-01
Films like Firefox, Surrogates, and Avatar have explored the possibilities of using brain-computer interfaces (BCIs) to control machines and replacement bodies with only thought. Real world BCIs have made great progress toward that end. Invasive BCIs have enabled monkeys to fully explore 3-D space using neuroprosthetics. However, noninvasive BCIs have not been able to demonstrate such mastery of 3-D space. Here, we report our work, which demonstrates that human subjects can use a noninvasive BCI to fly a virtual helicopter to any point in a 3-D world. Through use of intelligent control strategies, we have facilitated the realization of controlled flight in 3-D space. We accomplished this through a reductionist approach that assigns subject-specific control signals to the crucial components of 3-D flight. Subject control of the helicopter was comparable when using either the BCI or a keyboard. By using intelligent control strategies, the strengths of both the user and the BCI system were leveraged and accentuated. Intelligent control strategies in BCI systems such as those presented here may prove to be the foundation for complex BCIs capable of doing more than we ever imagined.
Colom, Roberto; Stein, Jason L.; Rajagopalan, Priya; Martínez, Kenia; Hermel, David; Wang, Yalin; Álvarez-Linera, Juan; Burgaleta, Miguel; Quiroga, MªÁngeles; Shih, Pei Chun; Thompson, Paul M.
2014-01-01
Here we apply a method for automated segmentation of the hippocampus in 3D high-resolution structural brain MRI scans. One hundred and four healthy young adults completed twenty one tasks measuring abstract, verbal, and spatial intelligence, along with working memory, executive control, attention, and processing speed. After permutation tests corrected for multiple comparisons across vertices (p < .05) significant relationships were found for spatial intelligence, spatial working memory, and spatial executive control. Interactions with sex revealed significant relationships with the general factor of intelligence (g), along with abstract and spatial intelligence. These correlations were mainly positive for males but negative for females, which might support the efficiency hypothesis in women. Verbal intelligence, attention, and processing speed were not related to hippocampal structural differences. PMID:25632167
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.
Yalcin, Bektas Murat; Karahan, Tevfik Fikret; Ozcelik, Muhittin; Igde, Fusun Artiran
2008-01-01
The purpose of the study is to investigate the effect of an emotional intelligence program on the health-related quality of life and well-being of individuals with type 2 diabetes. The BarOn Emotional Intelligence Scale (EQ-I), WHO Well-Being Questionnaire (WHO-WBQ-22), WHO Quality of Life Measure (WHOQOL-Bref), and the Medical Outcomes Study 36-Item Health Survey (SF-36) were administered to 184 patients with type 2 diabetes who volunteered to participate. Thirty-six patients with the lowest test scores on the WHO-WBQ-22, WHOQOL-Bref, and SF-36 were randomized into study and control groups (18 patients each). A 12-week emotional intelligence program was administered to the study group. At the end of the program, scales were readministered to both groups and again at 3 and 6 months. There were no differences between the quality of life, well-being, and emotional intelligence levels of the study and control groups before the commencement of the program (P > .05). At the conclusion of the program, quality of life, well-being, and emotional intelligence levels of study group patients increased in comparison with those in the control group (P < .001). The positive effect of the program on study groups' quality of life, wellbeing, and emotional intelligence persisted at the 3- and 6-month follow-up. The emotional intelligence program may have positive effects on quality of life and well-being of individuals with type 2 diabetes.
Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight
NASA Technical Reports Server (NTRS)
Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.
2003-01-01
This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.
Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants
NASA Astrophysics Data System (ADS)
Masri Husam Fayiz, Al
2017-01-01
The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms.
ERIC Educational Resources Information Center
Duchastel, P.; And Others
1989-01-01
Discusses intelligent computer assisted instruction (ICAI) and presents various models of learning which have been proposed. Topics discussed include artificial intelligence; intelligent tutorial systems; tutorial strategies; learner control; system design; learning theory; and knowledge representation of proper and improper (i.e., incorrect)…
Code of Federal Regulations, 2012 CFR
2012-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY CONDUCT ON AGENCY..., leased, or otherwise controlled by the Central Intelligence Agency). Authorized person. An officer of the Security Protective Service, or any other Central Intelligence Agency employee who has been authorized by...
Code of Federal Regulations, 2013 CFR
2013-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY CONDUCT ON AGENCY..., leased, or otherwise controlled by the Central Intelligence Agency). Authorized person. An officer of the Security Protective Service, or any other Central Intelligence Agency employee who has been authorized by...
Code of Federal Regulations, 2010 CFR
2010-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY CONDUCT ON AGENCY..., leased, or otherwise controlled by the Central Intelligence Agency). Authorized person. An officer of the Security Protective Service, or any other Central Intelligence Agency employee who has been authorized by...
Code of Federal Regulations, 2014 CFR
2014-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY CONDUCT ON AGENCY..., leased, or otherwise controlled by the Central Intelligence Agency). Authorized person. An officer of the Security Protective Service, or any other Central Intelligence Agency employee who has been authorized by...
Code of Federal Regulations, 2011 CFR
2011-07-01
... Defense Other Regulations Relating to National Defense CENTRAL INTELLIGENCE AGENCY CONDUCT ON AGENCY..., leased, or otherwise controlled by the Central Intelligence Agency). Authorized person. An officer of the Security Protective Service, or any other Central Intelligence Agency employee who has been authorized by...
Measuring the Performance and Intelligence of Systems: Proceedings of the 2002 PerMIS Workshop
NASA Technical Reports Server (NTRS)
Messina, E. R.; Meystel, A. M.
2002-01-01
Contents include the following: Performance Metrics; Performance of Multiple Agents; Performance of Mobility Systems; Performance of Planning Systems; General Discussion Panel 1; Uncertainty of Representation I; Performance of Robots in Hazardous Domains; Modeling Intelligence; Modeling of Mind; Measuring Intelligence; Grouping: A Core Procedure of Intelligence; Uncertainty in Representation II; Towards Universal Planning/Control Systems.
Beblo, Thomas; Pastuszak, Anna; Griepenstroh, Julia; Fernando, Silvia; Driessen, Martin; Schütz, Astrid; Rentzsch, Katrin; Schlosser, Nicole
2010-05-01
Emotional dysfunction is a key feature of patients with borderline personality disorder (BPD) but emotional intelligence (EI) has rarely been investigated in this sample. This study aimed at an investigation of ability EI, general intelligence, and self-reported emotion regulation in BPD. We included 19 patients with BPD and 20 healthy control subjects in the study. EI was assessed by means of the Mayer-Salovey-Caruso emotional intelligence test and the test of emotional intelligence. For the assessment of general intelligence, we administered the multidimensional "Leistungsprüfsystem-Kurzversion." The emotion regulation questionnaire and the difficulties in Emotion Regulation Scale were used to assess emotion regulation. The patients with BPD did not exhibit impairments of ability EI and general intelligence but reported severe impairments in emotion regulation. Ability EI was related both to general intelligence (patients and controls) and to self-reported emotion regulation (patients). In conclusion, emotional dysfunction in BPD might primarily affect self-perceived behavior rather than abilities. Intense negative emotions in everyday life may trigger dysfunctional emotion regulation strategies in BPD although patients possess sufficient theoretical knowledge about optimal regulation strategies.
Evaluation of the intelligent cruise control system. Volume 2, Appendices
DOT National Transportation Integrated Search
1999-10-01
The Intelligent Cruise Control (ICC) system evaluation was sponsored by the National Highway Traffic Safety Administration (NHTSA) and based on an ICC Field Operational Test (FOT) conducted under a cooperative agreement between the NHTSA and the Univ...
Murphy, Niamh C; Diviney, Mairead M; Donnelly, Jennifer C; Cooley, Sharon M; Kirkham, Colin H; Foran, Adrienne M; Breathnach, Fionnuala M; Malone, Fergal D; Geary, Michael P
2015-10-01
In Ireland, pregnant women are not routinely screened for subclinical hypothyroidism (SCH). Our objective was to compare the intelligence quotient (IQ) of children whose mothers had been diagnosed with SCH prenatally with matched controls using a case-control retrospective study. In a previous study from our group, 1000 healthy nulliparous women were screened anonymously for SCH. This was a laboratory diagnosis involving elevated TSH with normal fT4 or normal TSH with hypothyroxinaemia. We identified 23 cases who agreed to participate. These were matched with 47 controls. All children underwent neurodevelopmental assessment at age 7-8. Wechsler Intelligence Scale for Children IV assessment scores were used to compare the groups. Our main outcome measure was to identify whether there was a difference in IQ between the groups. From the cohort of cases, 23 mothers agreed to the assessment of their children as well as 47 controls. The children in the control group had higher mean scores than those in the case group across Verbal Comprehension Intelligence, Perceptual Reasoning Intelligence, Working Memory Intelligence, Processing Speed Intelligence and Full Scale IQ. Mann-Whitney U-test confirmed a significant difference in IQ between the cases (composite score 103.87) and the controls (composite score 109.11) with a 95% confidence interval (0.144, 10.330). Our results highlight significant differences in IQ of children of mothers who had unrecognised SCH during pregnancy. While our study size and design prevents us from making statements on causation, our data suggest significant potential public health implications for routine prenatal screening. © 2015 The Royal Australian and New Zealand College of Obstetricians and Gynaecologists.
Towards Intelligent Control for Next Generation CESTOL Aircraft
NASA Technical Reports Server (NTRS)
Acosta, Diana Michelle
2008-01-01
This talk will present the motivation, research approach and status of intelligent control research for Next Generation Cruise Efficient Short Take Off and Landing (CESTOL) aircraft. An introduction to the challenges of CESTOL control will be given, leading into an assessment of potential control solutions. The approach of the control research will be discussed, including a brief overview of the technical aspects of the research.
Arslan, Ruben C.; Penke, Lars; Johnson, Wendy; Iacono, William G.; McGue, Matt
2014-01-01
Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father’s age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents’ trait levels measured with the same precision as offspring’s. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents’ intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (<1% of variance explained) on intelligence. We discuss future avenues for studies of paternal age effects and suggest that stronger research designs are needed to rule out confounding factors involving birth order and the Flynn effect. PMID:24587224
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.
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.
NASA Astrophysics Data System (ADS)
Khan, Muazzam A.; Ahmad, Jawad; Javaid, Qaisar; Saqib, Nazar A.
2017-03-01
Wireless Sensor Networks (WSN) is widely deployed in monitoring of some physical activity and/or environmental conditions. Data gathered from WSN is transmitted via network to a central location for further processing. Numerous applications of WSN can be found in smart homes, intelligent buildings, health care, energy efficient smart grids and industrial control systems. In recent years, computer scientists has focused towards findings more applications of WSN in multimedia technologies, i.e. audio, video and digital images. Due to bulky nature of multimedia data, WSN process a large volume of multimedia data which significantly increases computational complexity and hence reduces battery time. With respect to battery life constraints, image compression in addition with secure transmission over a wide ranged sensor network is an emerging and challenging task in Wireless Multimedia Sensor Networks. Due to the open nature of the Internet, transmission of data must be secure through a process known as encryption. As a result, there is an intensive demand for such schemes that is energy efficient as well as highly secure since decades. In this paper, discrete wavelet-based partial image encryption scheme using hashing algorithm, chaotic maps and Hussain's S-Box is reported. The plaintext image is compressed via discrete wavelet transform and then the image is shuffled column-wise and row wise-wise via Piece-wise Linear Chaotic Map (PWLCM) and Nonlinear Chaotic Algorithm, respectively. To get higher security, initial conditions for PWLCM are made dependent on hash function. The permuted image is bitwise XORed with random matrix generated from Intertwining Logistic map. To enhance the security further, final ciphertext is obtained after substituting all elements with Hussain's substitution box. Experimental and statistical results confirm the strength of the anticipated scheme.
Optical sensors for application in intelligent food-packaging technology
NASA Astrophysics Data System (ADS)
McEvoy, Aisling K.; Von Bueltzingsloewen, Christoph; McDonagh, Colette M.; MacCraith, Brian D.; Klimant, Ingo; Wolfbeis, Otto S.
2003-03-01
Modified Atmosphere Packaged (MAP) food employs a protective gas mixture, which normally contains selected amounts of carbon dioxide (CO2) and oxygen (O2), in order to extend the shelf life of food. Conventional MAP analysis of package integrity involves destructive sampling of packages followed by carbon dioxide and oxygen detection. For quality control reasons, as well as to enhance food safety, the concept of optical on-pack sensors for monitoring the gas composition of the MAP package at different stages of the distribution process is very attractive. The objective of this work was to develop printable formulations of oxygen and carbon dioxide sensors for use in food packaging. Oxygen sensing is achieved by detecting the degree of quenching of a fluorescent ruthenium complex entrapped in a sol-gel matrix. In particular, a measurement technique based on the quenching of the fluorescence decay time, phase fluorometric detection, is employed. A scheme for detecting CO2 has been developed which is compatible with the oxygen detection scheme. It is fluorescence-based and uses the pH-sensitive 8-hydroxypyrene-1,3,6-trisulfonic acid (HPTS) indicator dye encapsulated in an organically modified silica (ORMOSIL) glass matrix. Dual Luminophore Referencing (DLR) has been employed as an internal referencing scheme, which provides many of the advantages of lifetime-based fluorometric methods. Oxygen cross-sensitivity was minimised by encapsulating the reference luminophore in dense sol-gel microspheres. The sensor performance compared well with standard methods for both oxygen and carbon dioxide detection. The results of preliminary on-pack print trials are presented and a preliminary design of an integrated dual gas optical read-out device is discussed.
Lee, Oi Sun; Gu, Mee Ock
2014-12-01
This study was conducted to develop and test the effects of an emotional intelligence program for undergraduate nursing students. The study design was a mixed method research. Participants were 36 nursing students (intervention group: 17, control group: 19). The emotional intelligence program was provided for 4 weeks (8 sessions, 20 hours). Data were collected between August 6 and October 4, 2013. Quantitative data were analyzed using Chi-square, Fisher's exact test, t-test, repeated measure ANOVA, and paired t-test with SPSS/WIN 18.0. Qualitative data were analyzed using content analysis. Quantitative results showed that emotional intelligence, communication skills, resilience, stress coping strategy, and clinical competence were significantly better in the experimental group compared to the control group. According to the qualitative results, the nursing students experienced improvement in emotional intelligence, interpersonal relationships, and empowerment, as well as a reduction in clinical practice stress after participation in the emotional intelligence program. Study findings indicate that the emotional intelligence program for undergraduate nursing students is effective and can be recommended as an intervention for improving the clinical competence of undergraduate students in a nursing curriculum.
Fostering Emotional Intelligence in Online Higher Education Courses
ERIC Educational Resources Information Center
Majeski, Robin A.; Stover, Merrily; Valais, Teresa; Ronch, Judah
2017-01-01
Given the complex challenges organizations face and the importance of emotional intelligence to effective leadership, management education has begun to help adult learners develop emotional intelligence competencies. These include emotional self-control, conflict management, teamwork, cultural awareness, and inspirational leadership, among other…
An effective and secure key-management scheme for hierarchical access control in E-medicine system.
Odelu, Vanga; Das, Ashok Kumar; Goswami, Adrijit
2013-04-01
Recently several hierarchical access control schemes are proposed in the literature to provide security of e-medicine systems. However, most of them are either insecure against 'man-in-the-middle attack' or they require high storage and computational overheads. Wu and Chen proposed a key management method to solve dynamic access control problems in a user hierarchy based on hybrid cryptosystem. Though their scheme improves computational efficiency over Nikooghadam et al.'s approach, it suffers from large storage space for public parameters in public domain and computational inefficiency due to costly elliptic curve point multiplication. Recently, Nikooghadam and Zakerolhosseini showed that Wu-Chen's scheme is vulnerable to man-in-the-middle attack. In order to remedy this security weakness in Wu-Chen's scheme, they proposed a secure scheme which is again based on ECC (elliptic curve cryptography) and efficient one-way hash function. However, their scheme incurs huge computational cost for providing verification of public information in the public domain as their scheme uses ECC digital signature which is costly when compared to symmetric-key cryptosystem. In this paper, we propose an effective access control scheme in user hierarchy which is only based on symmetric-key cryptosystem and efficient one-way hash function. We show that our scheme reduces significantly the storage space for both public and private domains, and computational complexity when compared to Wu-Chen's scheme, Nikooghadam-Zakerolhosseini's scheme, and other related schemes. Through the informal and formal security analysis, we further show that our scheme is secure against different attacks and also man-in-the-middle attack. Moreover, dynamic access control problems in our scheme are also solved efficiently compared to other related schemes, making our scheme is much suitable for practical applications of e-medicine systems.
Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)
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
Neural computing thermal comfort index PMV for the indoor environment intelligent control system
NASA Astrophysics Data System (ADS)
Liu, Chang; Chen, Yifei
2013-03-01
Providing indoor thermal comfort and saving energy are two main goals of indoor environmental control system. An intelligent comfort control system by combining the intelligent control and minimum power control strategies for the indoor environment is presented in this paper. In the system, for realizing the comfort control, the predicted mean vote (PMV) is designed as the control goal, and with chastening formulas of PMV, it is controlled to optimize for improving indoor comfort lever by considering six comfort related variables. On the other hand, a RBF neural network based on genetic algorithm is designed to calculate PMV for better performance and overcoming the nonlinear feature of the PMV calculation better. The formulas given in the paper are presented for calculating the expected output values basing on the input samples, and the RBF network model is trained depending on input samples and the expected output values. The simulation result is proved that the design of the intelligent calculation method is valid. Moreover, this method has a lot of advancements such as high precision, fast dynamic response and good system performance are reached, it can be used in practice with requested calculating error.
ERIC Educational Resources Information Center
Unsworth, Nash; Spillers, Gregory J.
2010-01-01
The current study examined the extent to which attention control abilities, secondary memory abilities, or both accounted for variation in working memory capacity (WMC) and its relation to fluid intelligence. Participants performed various attention control, secondary memory, WMC, and fluid intelligence measures. Confirmatory factor analyses…
1983-06-06
Command, Control, Communications, and Intelligence presented by the Armed Forced Communications Electronics Association and the perusal of many ...A great deal was also learned from the knowledgeable and helpful USAWC faculty and SSI staff as well as the curriculum which provided many insights to...actually an _ umbrella-label covering many disciplines. Thus, after a definition of Al, descriptions of a selection of its subfields will follow to set the
Chaos-order transition in foraging behavior of ants.
Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian; Schellnhuber, Hans Joachim
2014-06-10
The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. Biologists have discovered that single ants exhibit low-dimensional deterministic-chaotic activities. However, the influences of the nest, ants' physical abilities, and ants' knowledge (or experience) on foraging behavior have received relatively little attention in studies of the collective behavior of ants. This paper provides new insights into basic mechanisms of effective foraging for social insects or group animals that have a home. We propose that the whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. A mathematical model is developed to study this complex scheme. We show that the transition from chaotic to periodic regimes observed in our model results from an optimization scheme for group animals with a home. According to our investigation, the behavior of such insects is not represented by random but rather deterministic walks (as generated by deterministic dynamical systems, e.g., by maps) in a random environment: the animals use their intelligence and experience to guide them. The more knowledge an ant has, the higher its foraging efficiency is. When young insects join the collective to forage with old and middle-aged ants, it benefits the whole colony in the long run. The resulting strategy can even be optimal.
Chaos–order transition in foraging behavior of ants
Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Yang, Yixian; Schellnhuber, Hans Joachim
2014-01-01
The study of the foraging behavior of group animals (especially ants) is of practical ecological importance, but it also contributes to the development of widely applicable optimization problem-solving techniques. Biologists have discovered that single ants exhibit low-dimensional deterministic-chaotic activities. However, the influences of the nest, ants’ physical abilities, and ants’ knowledge (or experience) on foraging behavior have received relatively little attention in studies of the collective behavior of ants. This paper provides new insights into basic mechanisms of effective foraging for social insects or group animals that have a home. We propose that the whole foraging process of ants is controlled by three successive strategies: hunting, homing, and path building. A mathematical model is developed to study this complex scheme. We show that the transition from chaotic to periodic regimes observed in our model results from an optimization scheme for group animals with a home. According to our investigation, the behavior of such insects is not represented by random but rather deterministic walks (as generated by deterministic dynamical systems, e.g., by maps) in a random environment: the animals use their intelligence and experience to guide them. The more knowledge an ant has, the higher its foraging efficiency is. When young insects join the collective to forage with old and middle-aged ants, it benefits the whole colony in the long run. The resulting strategy can even be optimal. PMID:24912159
Zijlmans, L J M; Embregts, P J C M; Gerits, L; Bosman, A M T; Derksen, J J L
2015-07-01
Recent research addressed the relationship between staff behaviour and challenging behaviour of individuals with an intellectual disability (ID). Consequently, research on interventions aimed at staff is warranted. The present study focused on the effectiveness of a staff training aimed at emotional intelligence and interactions between staff and clients. The effects of the training on emotional intelligence, coping style and emotions of support staff were investigated. Participants were 214 support staff working within residential settings for individuals with ID and challenging behaviour. The experimental group consisted of 76 staff members, 138 staff members participated in two different control groups. A pre-test, post-test, follow-up control group design was used. Effectiveness was assessed using questionnaires addressing emotional intelligence, coping and emotions. Emotional intelligence of the experimental group changed significantly more than that of the two control groups. The experimental group showed an increase in task-oriented coping, whereas one control group did not. The results with regard to emotions were mixed. Follow-up data revealed that effects within the experimental group were still present four months after the training ended. A staff training aimed at emotional intelligence and staff-client interactions is effective in improving emotional intelligence and coping styles of support staff. However, the need for more research aiming at the relationship between staff characteristics, organisational factors and their mediating role in the effectiveness of staff training is emphasised. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.
Evaluation of the intelligent cruise control system : volume 1 : study results
DOT National Transportation Integrated Search
1999-10-01
The Intelligent Cruise Control (ICC) system evaluation was based on an ICC Field Operational Test (FOT) performed in Michigan. The FOT involved 108 volunteers recruited to drive ten ICC-equipped Chrysler Concordes. Testing was initiated in July 1996 ...
Intelligent cruise control field operational test. Volume I, Technical report
DOT National Transportation Integrated Search
1998-05-01
This document reports on a cooperative agreement between NHTSA and UMTRI entitled Intelligent Cruise Control (ICC) Field Operational Test (FOT). The main goal of the work is to characterize safety and comfort issues that are fundamental to human inte...
Intelligent Flow Control Valve
NASA Technical Reports Server (NTRS)
Kelley, Anthony R (Inventor)
2015-01-01
The present invention is an intelligent flow control valve which may be inserted into the flow coming out of a pipe and activated to provide a method to stop, measure, and meter flow coming from the open or possibly broken pipe. The intelligent flow control valve may be used to stop the flow while repairs are made. Once repairs have been made, the valve may be removed or used as a control valve to meter the amount of flow from inside the pipe. With the addition of instrumentation, the valve may also be used as a variable area flow meter and flow controller programmed based upon flowing conditions. With robotic additions, the valve may be configured to crawl into a desired pipe location, anchor itself, and activate flow control or metering remotely.
The Effects of Taekwondo Training on Brain Connectivity and Body Intelligence.
Kim, Young Jae; Cha, Eun Joo; Kim, Sun Mi; Kang, Kyung Doo; Han, Doug Hyun
2015-07-01
Many studies have reported that Taekwondo training could improve body perception, control and brain activity, as assessed with an electroencephalogram. This study aimed to assess body intelligence and brain connectivity in children with Taekwondo training as compared to children without Taekwondo training. Fifteen children with Taekwondo training (TKD) and 13 age- and sex-matched children who had no previous experience of Taekwondo training (controls) were recruited. Body intelligence, clinical characteristics and brain connectivity in all children were assessed with the Body Intelligence Scale (BIS), self-report, and resting state functional magnetic resonance imaging. The mean BIS score in the TKD group was higher than that in the control group. The TKD group showed increased low-frequency fluctuations in the right frontal precentral gyrus and the right parietal precuneus, compared to the control group. The TKD group showed positive cerebellum vermis (lobe VII) seed to the right frontal, left frontal, and left parietal lobe. The control group showed positive cerebellum seed to the left frontal, parietal, and occipital cortex. Relative to the control group, the TKD group showed increased functional connectivity from cerebellum seed to the right inferior frontal gyrus. To the best of our knowledge, this is the first study to assess the effect of Taekwondo training on brain connectivity in children. Taekwondo training improved body intelligence and brain connectivity from the cerebellum to the parietal and frontal cortex.
A demonstration of an intelligent control system for a reusable rocket engine
NASA Technical Reports Server (NTRS)
Musgrave, Jeffrey L.; Paxson, Daniel E.; Litt, Jonathan S.; Merrill, Walter C.
1992-01-01
An Intelligent Control System for reusable rocket engines is under development at NASA Lewis Research Center. The primary objective is to extend the useful life of a reusable rocket propulsion system while minimizing between flight maintenance and maximizing engine life and performance through improved control and monitoring algorithms and additional sensing and actuation. This paper describes current progress towards proof-of-concept of an Intelligent Control System for the Space Shuttle Main Engine. A subset of identifiable and accommodatable engine failure modes is selected for preliminary demonstration. Failure models are developed retaining only first order effects and included in a simplified nonlinear simulation of the rocket engine for analysis under closed loop control. The engine level coordinator acts as an interface between the diagnostic and control systems, and translates thrust and mixture ratio commands dictated by mission requirements, and engine status (health) into engine operational strategies carried out by a multivariable control. Control reconfiguration achieves fault tolerance if the nominal (healthy engine) control cannot. Each of the aforementioned functionalities is discussed in the context of an example to illustrate the operation of the system in the context of a representative failure. A graphical user interface allows the researcher to monitor the Intelligent Control System and engine performance under various failure modes selected for demonstration.
Expert system constant false alarm rate processor
NASA Astrophysics Data System (ADS)
Baldygo, William J., Jr.; Wicks, Michael C.
1993-10-01
The requirements for high detection probability and low false alarm probability in modern wide area surveillance radars are rarely met due to spatial variations in clutter characteristics. Many filtering and CFAR detection algorithms have been developed to effectively deal with these variations; however, any single algorithm is likely to exhibit excessive false alarms and intolerably low detection probabilities in a dynamically changing environment. A great deal of research has led to advances in the state of the art in Artificial Intelligence (AI) and numerous areas have been identified for application to radar signal processing. The approach suggested here, discussed in a patent application submitted by the authors, is to intelligently select the filtering and CFAR detection algorithms being executed at any given time, based upon the observed characteristics of the interference environment. This approach requires sensing the environment, employing the most suitable algorithms, and applying an appropriate multiple algorithm fusion scheme or consensus algorithm to produce a global detection decision.
Intelligent web image retrieval system
NASA Astrophysics Data System (ADS)
Hong, Sungyong; Lee, Chungwoo; Nah, Yunmook
2001-07-01
Recently, the web sites such as e-business sites and shopping mall sites deal with lots of image information. To find a specific image from these image sources, we usually use web search engines or image database engines which rely on keyword only retrievals or color based retrievals with limited search capabilities. This paper presents an intelligent web image retrieval system. We propose the system architecture, the texture and color based image classification and indexing techniques, and representation schemes of user usage patterns. The query can be given by providing keywords, by selecting one or more sample texture patterns, by assigning color values within positional color blocks, or by combining some or all of these factors. The system keeps track of user's preferences by generating user query logs and automatically add more search information to subsequent user queries. To show the usefulness of the proposed system, some experimental results showing recall and precision are also explained.
Intelligent search in Big Data
NASA Astrophysics Data System (ADS)
Birialtsev, E.; Bukharaev, N.; Gusenkov, A.
2017-10-01
An approach to data integration, aimed on the ontology-based intelligent search in Big Data, is considered in the case when information objects are represented in the form of relational databases (RDB), structurally marked by their schemes. The source of information for constructing an ontology and, later on, the organization of the search are texts in natural language, treated as semi-structured data. For the RDBs, these are comments on the names of tables and their attributes. Formal definition of RDBs integration model in terms of ontologies is given. Within framework of the model universal RDB representation ontology, oil production subject domain ontology and linguistic thesaurus of subject domain language are built. Technique of automatic SQL queries generation for subject domain specialists is proposed. On the base of it, information system for TATNEFT oil-producing company RDBs was implemented. Exploitation of the system showed good relevance with majority of queries.
Towards a Bio-inspired Security Framework for Mission-Critical Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Ren, Wei; Song, Jun; Ma, Zhao; Huang, Shiyong
Mission-critical wireless sensor networks (WSNs) have been found in numerous promising applications in civil and military fields. However, the functionality of WSNs extensively relies on its security capability for detecting and defending sophisticated adversaries, such as Sybil, worm hole and mobile adversaries. In this paper, we propose a bio-inspired security framework to provide intelligence-enabled security mechanisms. This scheme is composed of a middleware, multiple agents and mobile agents. The agents monitor the network packets, host activities, make decisions and launch corresponding responses. Middleware performs an infrastructure for the communication between various agents and corresponding mobility. Certain cognitive models and intelligent algorithms such as Layered Reference Model of Brain and Self-Organizing Neural Network with Competitive Learning are explored in the context of sensor networks that have resource constraints. The security framework and implementation are also described in details.
Road Nail: Experimental Solar Powered Intelligent Road Marking System
NASA Astrophysics Data System (ADS)
Samardžija, Dragan; Teslić, Nikola; Todorović, Branislav M.; Kovač, Erne; Isailović, Đorđe; Miladinović, Bojan
2012-03-01
Driving in low visibility conditions (night time, fog or heavy precipitation) is particularly challenging task with an increased probability of traffic accidents and possible injuries. Road Nail is a solar powered intelligent road marking system of wirelessly networked signaling devices that improve driver safety in low visibility conditions along hazardous roadways. Nails or signaling devices are autonomous nodes with capability to accumulate energy, exchange wireless messages, detect approaching vehicles and emit signalization light. We have built an experimental test-bed that consists of 20 nodes and a cellular gateway. Implementation details of the above system, including extensive measurements and performance evaluations in realistic field deployments are presented. A novel distributed network topology discovery scheme is proposed which integrates both sensor and wireless communication aspects, where nodes act autonomously. Finally, integration of the Road Nail system with the cellular network and the Internet is described.
A heuristic for deriving the optimal number and placement of reconnaissance sensors
NASA Astrophysics Data System (ADS)
Nanda, S.; Weeks, J.; Archer, M.
2008-04-01
A key to mastering asymmetric warfare is the acquisition of accurate intelligence on adversaries and their assets in urban and open battlefields. To achieve this, one needs adequate numbers of tactical sensors placed in locations to optimize coverage, where optimality is realized by covering a given area of interest with the least number of sensors, or covering the largest possible subsection of an area of interest with a fixed set of sensors. Unfortunately, neither problem admits a polynomial time algorithm as a solution, and therefore, the placement of such sensors must utilize intelligent heuristics instead. In this paper, we present a scheme implemented on parallel SIMD processing architectures to yield significantly faster results, and that is highly scalable with respect to dynamic changes in the area of interest. Furthermore, the solution to the first problem immediately translates to serve as a solution to the latter if and when any sensors are rendered inoperable.
Raja, Muhammad Asif Zahoor; Khan, Junaid Ali; Ahmad, Siraj-ul-Islam; Qureshi, Ijaz Mansoor
2012-01-01
A methodology for solution of Painlevé equation-I is presented using computational intelligence technique based on neural networks and particle swarm optimization hybridized with active set algorithm. The mathematical model of the equation is developed with the help of linear combination of feed-forward artificial neural networks that define the unsupervised error of the model. This error is minimized subject to the availability of appropriate weights of the networks. The learning of the weights is carried out using particle swarm optimization algorithm used as a tool for viable global search method, hybridized with active set algorithm for rapid local convergence. The accuracy, convergence rate, and computational complexity of the scheme are analyzed based on large number of independents runs and their comprehensive statistical analysis. The comparative studies of the results obtained are made with MATHEMATICA solutions, as well as, with variational iteration method and homotopy perturbation method. PMID:22919371
Contextual analysis of fluid intelligence.
Salthouse, Timothy A; Pink, Jeffrey E; Tucker-Drob, Elliot M
2008-01-01
The nature of fluid intelligence was investigated by identifying variables that were, and were not, significantly related to this construct. Relevant information was obtained from three sources: re-analyses of data from previous studies, a study in which 791 adults performed storage-plus-processing working memory tasks, and a study in which 236 adults performed a variety of working memory, updating, and cognitive control tasks. The results suggest that fluid intelligence represents a broad individual difference dimension contributing to diverse types of controlled or effortful processing. The analyses also revealed that very few of the age-related effects on the target variables were statistically independent of effects on established cognitive abilities, which suggests most of the age-related influences on a wide variety of cognitive control variables overlap with age-related influences on cognitive abilities such as fluid intelligence, episodic memory, and perceptual speed.
NASA Astrophysics Data System (ADS)
Na, Yongyi
2017-03-01
The design of simple intelligent car, using AT89S52 single chip microcomputer as the car detection and control core; The metal sensor TL - Q5MC induction to iron, to detect the way to send feedback to the signal of single chip microcomputer, make SCM according to the scheduled work mode to control the car in the area according to the predetermined speed, and the operation mode of the microcontroller choose different also can control the car driving along s-shaped iron; Use A44E hall element to detect the car speeds; Adopts 1602 LCD display time of car driving, driving the car to stop, take turns to show the car driving time, distance, average speed and the speed of time. This design has simple structure and is easy to implement, but are highly intelligent, humane, to a certain extent reflects the intelligence.
Intelligent Propulsion System Foundation Technology: Summary of Research
NASA Technical Reports Server (NTRS)
2008-01-01
The purpose of this cooperative agreement was to develop a foundation of intelligent propulsion technologies for NASA and industry that will have an impact on safety, noise, emissions, and cost. These intelligent engine technologies included sensors, electronics, communications, control logic, actuators, smart materials and structures, and system studies. Furthermore, this cooperative agreement helped prepare future graduates to develop the revolutionary intelligent propulsion technologies that will be needed to ensure pre-eminence of the U.S. aerospace industry. This Propulsion 21 - Phase 11 program consisted of four primary research areas and associated work elements at Ohio universities: 1.0 Turbine Engine Prognostics, 2.0 Active Controls for Emissions and Noise Reduction, 3.0 Active Structural Controls and Performance, and 4.0 System Studies and Integration. Phase l, which was conducted during the period August 1, 2003, through September 30, 2004, has been reported separately.
Fine motor skills in children with rolandic epilepsy.
Ayaz, Muhammed; Kara, Bülent; Soylu, Nusret; Ayaz, Ayşe Burcu
2013-11-01
This study aimed to evaluate fine motor skills in children with rolandic epilepsy (RE). The research included 44 children diagnosed with typical RE and 44 controls matched in terms of age, gender, and level of education. Fine motor skills were evaluated with the Purdue Pegboard Test, and intelligence was measured with the Wechsler Intelligence Scale for Children. After controlling for the effect of intelligence on fine motor skills, the results showed that the children with RE did not perform as well as the controls in the PPT dominant hand, both hands, and assembly subtests. Epileptic focus, treatment status, type of antiepileptic treatment, age at the time of the first seizure, time since the last seizure, and total number of seizures did not affect motor skills. Rolandic epilepsy negatively affected fine motor skills regardless of the children's level of intelligence. © 2013.
The effect of compression and attention allocation on speech intelligibility
NASA Astrophysics Data System (ADS)
Choi, Sangsook; Carrell, Thomas
2003-10-01
Research investigating the effects of amplitude compression on speech intelligibility for individuals with sensorineural hearing loss has demonstrated contradictory results [Souza and Turner (1999)]. Because percent-correct measures may not be the best indicator of compression effectiveness, a speech intelligibility and motor coordination task was developed to provide data that may more thoroughly explain the perception of compressed speech signals. In the present study, a pursuit rotor task [Dlhopolsky (2000)] was employed along with word identification task to measure the amount of attention required to perceive compressed and non-compressed words in noise. Monosyllabic words were mixed with speech-shaped noise at a fixed signal-to-noise ratio and compressed using a wide dynamic range compression scheme. Participants with normal hearing identified each word with or without a simultaneous pursuit-rotor task. Also, participants completed the pursuit-rotor task without simultaneous word presentation. It was expected that the performance on the additional motor task would reflect effect of the compression better than simple word-accuracy measures. Results were complex. For example, in some conditions an irrelevant task actually improved performance on a simultaneous listening task. This suggests there might be an optimal level of attention required for recognition of monosyllabic words.
Fang, Chunying; Li, Haifeng; Ma, Lin; Zhang, Mancai
2017-01-01
Pathological speech usually refers to speech distortion resulting from illness or other biological insults. The assessment of pathological speech plays an important role in assisting the experts, while automatic evaluation of speech intelligibility is difficult because it is usually nonstationary and mutational. In this paper, we carry out an independent innovation of feature extraction and reduction, and we describe a multigranularity combined feature scheme which is optimized by the hierarchical visual method. A novel method of generating feature set based on S -transform and chaotic analysis is proposed. There are BAFS (430, basic acoustics feature), local spectral characteristics MSCC (84, Mel S -transform cepstrum coefficients), and chaotic features (12). Finally, radar chart and F -score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96 dimensions based on NKI-CCRT corpus and 104 dimensions based on SVD corpus. The experimental results denote that new features by support vector machine (SVM) have the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus and 78.7% on SVD corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.
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.
Raul, Pramod R; Pagilla, Prabhakar R
2015-05-01
In this paper, two adaptive Proportional-Integral (PI) control schemes are designed and discussed for control of web tension in Roll-to-Roll (R2R) manufacturing systems. R2R systems are used to transport continuous materials (called webs) on rollers from the unwind roll to the rewind roll. Maintaining web tension at the desired value is critical to many R2R processes such as printing, coating, lamination, etc. Existing fixed gain PI tension control schemes currently used in industrial practice require extensive tuning and do not provide the desired performance for changing operating conditions and material properties. The first adaptive PI scheme utilizes the model reference approach where the controller gains are estimated based on matching of the actual closed-loop tension control systems with an appropriately chosen reference model. The second adaptive PI scheme utilizes the indirect adaptive control approach together with relay feedback technique to automatically initialize the adaptive PI gains. These adaptive tension control schemes can be implemented on any R2R manufacturing system. The key features of the two adaptive schemes is that their designs are simple for practicing engineers, easy to implement in real-time, and automate the tuning process. Extensive experiments are conducted on a large experimental R2R machine which mimics many features of an industrial R2R machine. These experiments include trials with two different polymer webs and a variety of operating conditions. Implementation guidelines are provided for both adaptive schemes. Experimental results comparing the two adaptive schemes and a fixed gain PI tension control scheme used in industrial practice are provided and discussed. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Event-triggered attitude control of spacecraft
NASA Astrophysics Data System (ADS)
Wu, Baolin; Shen, Qiang; Cao, Xibin
2018-02-01
The problem of spacecraft attitude stabilization control system with limited communication and external disturbances is investigated based on an event-triggered control scheme. In the proposed scheme, information of attitude and control torque only need to be transmitted at some discrete triggered times when a defined measurement error exceeds a state-dependent threshold. The proposed control scheme not only guarantees that spacecraft attitude control errors converge toward a small invariant set containing the origin, but also ensures that there is no accumulation of triggering instants. The performance of the proposed control scheme is demonstrated through numerical simulation.
Intelligent Flight Control System and Aeronautics Research at NASA Dryden
NASA Technical Reports Server (NTRS)
Brown, Nelson A.
2009-01-01
This video presentation reviews the F-15 Intelligent Flight Control System and contains clips of flight tests and aircraft performance in the areas of target tracking, takeoff and differential stabilators. Video of the APG milestone flight 1g formation is included.
Intelligent cruise control field operational test. Vol II, Appendices A-F
DOT National Transportation Integrated Search
1998-05-01
This document reports on a cooperative agreement between NHTSA and UMTRI entitled Intelligent Cruise Control (ICC) Field Operational Test (FOT). The main goal of the work is to characterize safety and comfort issues that are fundamental to human inte...
Strong genetic overlap between executive functions and intelligence.
Engelhardt, Laura E; Mann, Frank D; Briley, Daniel A; Church, Jessica A; Harden, K Paige; Tucker-Drob, Elliot M
2016-09-01
Executive functions (EFs) are cognitive processes that control, monitor, and coordinate more basic cognitive processes. EFs play instrumental roles in models of complex reasoning, learning, and decision making, and individual differences in EFs have been consistently linked with individual differences in intelligence. By middle childhood, genetic factors account for a moderate proportion of the variance in intelligence, and these effects increase in magnitude through adolescence. Genetic influences on EFs are very high, even in middle childhood, but the extent to which these genetic influences overlap with those on intelligence is unclear. We examined genetic and environmental overlap between EFs and intelligence in a racially and socioeconomically diverse sample of 811 twins ages 7 to 15 years (M = 10.91, SD = 1.74) from the Texas Twin Project. A general EF factor representing variance common to inhibition, switching, working memory, and updating domains accounted for substantial proportions of variance in intelligence, primarily via a genetic pathway. General EF continued to have a strong, genetically mediated association with intelligence even after controlling for processing speed. Residual variation in general intelligence was influenced only by shared and nonshared environmental factors, and there remained no genetic variance in general intelligence that was unique of EF. Genetic variance independent of EF did remain, however, in a more specific perceptual reasoning ability. These results provide evidence that genetic influences on general intelligence are highly overlapping with those on EF. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
An Intrinsically Digital Amplification Scheme for Hearing Aids
NASA Astrophysics Data System (ADS)
Blamey, Peter J.; Macfarlane, David S.; Steele, Brenton R.
2005-12-01
Results for linear and wide-dynamic range compression were compared with a new 64-channel digital amplification strategy in three separate studies. The new strategy addresses the requirements of the hearing aid user with efficient computations on an open-platform digital signal processor (DSP). The new amplification strategy is not modeled on prior analog strategies like compression and linear amplification, but uses statistical analysis of the signal to optimize the output dynamic range in each frequency band independently. Using the open-platform DSP processor also provided the opportunity for blind trial comparisons of the different processing schemes in BTE and ITE devices of a high commercial standard. The speech perception scores and questionnaire results show that it is possible to provide improved audibility for sound in many narrow frequency bands while simultaneously improving comfort, speech intelligibility in noise, and sound quality.
Driving the brain towards creativity and intelligence: A network control theory analysis.
Kenett, Yoed N; Medaglia, John D; Beaty, Roger E; Chen, Qunlin; Betzel, Richard F; Thompson-Schill, Sharon L; Qiu, Jiang
2018-01-04
High-level cognitive constructs, such as creativity and intelligence, entail complex and multiple processes, including cognitive control processes. Recent neurocognitive research on these constructs highlight the importance of dynamic interaction across neural network systems and the role of cognitive control processes in guiding such a dynamic interaction. How can we quantitatively examine the extent and ways in which cognitive control contributes to creativity and intelligence? To address this question, we apply a computational network control theory (NCT) approach to structural brain imaging data acquired via diffusion tensor imaging in a large sample of participants, to examine how NCT relates to individual differences in distinct measures of creative ability and intelligence. Recent application of this theory at the neural level is built on a model of brain dynamics, which mathematically models patterns of inter-region activity propagated along the structure of an underlying network. The strength of this approach is its ability to characterize the potential role of each brain region in regulating whole-brain network function based on its anatomical fingerprint and a simplified model of node dynamics. We find that intelligence is related to the ability to "drive" the brain system into easy to reach neural states by the right inferior parietal lobe and lower integration abilities in the left retrosplenial cortex. We also find that creativity is related to the ability to "drive" the brain system into difficult to reach states by the right dorsolateral prefrontal cortex (inferior frontal junction) and higher integration abilities in sensorimotor areas. Furthermore, we found that different facets of creativity-fluency, flexibility, and originality-relate to generally similar but not identical network controllability processes. We relate our findings to general theories on intelligence and creativity. Copyright © 2018 Elsevier Ltd. All rights reserved.
Cao, Wujing; Yu, Hongliu; Zhao, Weiliang; Li, Jin; Wei, Xiaodong
2018-01-01
Prosthetic knee is the most important component of lower limb prosthesis. Speed adaptive for prosthetic knee during swing flexion is the key method to realize physiological gait. This study aims to discuss the target of physiological gait, propose a speed adaptive control method during swing flexion and research the damping adjustment law of intelligent hydraulic prosthetic knee. According to the physiological gait trials of healthy people, the control target during swing flexion is defined. A new prosthetic knee with fuzzy logical control during swing flexion is designed to realize the damping adjustment automatically. The function simulation and evaluation system of intelligent knee prosthesis is provided. Speed adaptive control test of the intelligent prosthetic knee in different velocities are researched. The maximum swing flexion of the knee angle is set between sixty degree and seventy degree as the target of physiological gait. Preliminary experimental results demonstrate that the prosthetic knee with fuzzy logical control is able to realize physiological gait under different speeds. The faster the walking, the bigger the valve closure percentage of the hydraulic prosthetic knee. The proposed fuzzy logical control strategy and intelligent hydraulic prosthetic knee are effective for the amputee to achieve physiological gait.
NASA Technical Reports Server (NTRS)
Kim, Won S.
1992-01-01
Two schemes of force reflecting control, position-error based force reflection and low-pass-filtered force reflection, both combined with shared compliance control, were developed for dissimilar master-slave arms. These schemes enabled high force reflection gains, which were not possible with a conventional scheme when the slave arm was much stiffer than the master arm. The experimental results with a peg-in-hole task indicated that the newly force reflecting control schemes combined with compliance control resulted in best task performances. As a related application, a simulated force reflection/shared compliance control teleoperation trainer was developed that provided the operator with the feel of kinesthetic force virtual reality.
Tactical assessment in a squad of intelligent bots
NASA Astrophysics Data System (ADS)
Gołuński, Marcel; Wasiewicz, Piotr
2010-09-01
In this paper we explore the problem of communication and coordination in a team of intelligent game bots (aka embodied agents). It presents a tactical decision making system controlling the behavior of an autonomous bot followed by the concept of a team tactical decision making system controlling the team of intelligent bots. The algorithms to be introduced have been implemented in the Java language by means of Pogamut 2 framework, interfacing the bot logic with Unreal Tournament 2004 virtual environment.
NASA Technical Reports Server (NTRS)
1984-01-01
The two manufacturing concepts developed represent innovative, technologically advanced manufacturing schemes. The concepts were selected to facilitate an in depth analysis of manufacturing automation requirements in the form of process mechanization, teleoperation and robotics, and artificial intelligence. While the cost effectiveness of these facilities has not been analyzed as part of this study, both appear entirely feasible for the year 2000 timeframe. The growing demand for high quality gallium arsenide microelectronics may warrant the ventures.
A Simple Hierarchical Pooling Data Structure for Loop Closure
2016-10-16
ticated agglomerative schemes at a fraction of the effort. 1.1 Related work Loop closure is a key component in robotic mapping (SLAM) [37], autonomous...appearance-only slam-fab-map 2.0. In: Robotics : Science and Systems. vol. 5. Seattle, USA (2009) 7. Dong, J., Soatto, S.: Domain size pooling in local...detection with bags of binary words. In: Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ Intl. Conf. on. pp. 51–58. IEEE (2011) 9. Geiger, A
An architecture for rapid prototyping of control schemes for artificial ventricles.
Ficola, Antonio; Pagnottelli, Stefano; Valigi, Paolo; Zoppitelli, Maurizio
2004-01-01
This paper presents an experimental system aimed at rapid prototyping of feedback control schemes for ventricular assist devices, and artificial ventricles in general. The system comprises a classical mock circulatory system, an actuated bellow-based ventricle chamber, and a software architecture for control schemes implementation and experimental data acquisition, visualization and storing. Several experiments have been carried out, showing good performance of ventricular pressure tracking control schemes.
Najafi, Mostafa; Akouchekian, Shahla; Ghaderi, Alireza; Mahaki, Behzad; Rezaei, Mariam
2017-01-01
Background: Attention deficit and hyperactivity disorder (ADHD) is a common psychological problem during childhood. This study aimed to evaluate multiple intelligences profiles of children with ADHD in comparison with non-ADHD. Materials and Methods: This cross-sectional descriptive analytical study was done on 50 children of 6–13 years old in two groups of with and without ADHD. Children with ADHD were referred to Clinics of Child and Adolescent Psychiatry, Isfahan University of Medical Sciences, in 2014. Samples were selected based on clinical interview (based on Diagnostic and Statistical Manual of Mental Disorders IV and parent–teacher strengths and difficulties questionnaire), which was done by psychiatrist and psychologist. Raven intelligence quotient (IQ) test was used, and the findings were compared to the results of multiple intelligences test. Data analysis was done using a multivariate analysis of covariance using SPSS20 software. Results: Comparing the profiles of multiple intelligence among two groups, there are more kinds of multiple intelligences in control group than ADHD group, a difference which has been more significant in logical, interpersonal, and intrapersonal intelligence (P < 0.05). There was no significant difference with the other kinds of multiple intelligences in two groups (P > 0.05). The IQ average score in the control group and ADHD group was 102.42 ± 16.26 and 96.72 ± 16.06, respectively, that reveals the negative effect of ADHD on IQ average value. There was an insignificance relationship between linguistic and naturalist intelligence (P > 0.05). However, in other kinds of multiple intelligences, direct and significant relationships were observed (P < 0.05). Conclusions: Since the levels of IQ (Raven test) and MI in control group were more significant than ADHD group, ADHD is likely to be associated with logical-mathematical, interpersonal, and intrapersonal profiles. PMID:29285478
Students Can Control Their Emotions
ERIC Educational Resources Information Center
Harati, Saba; Parsa, Nasrin Arian
2014-01-01
As emotional intelligence contributes extensively in people's lives, it can also find some significance in language teaching. From this perspective, it is inevitable for teachers to know how to improve students' emotional intelligence. This paper made an effort to provide procedures to develop emotional intelligence. Although success has various…
Human-computer interaction in distributed supervisory control tasks
NASA Technical Reports Server (NTRS)
Mitchell, Christine M.
1989-01-01
An overview of activities concerned with the development and applications of the Operator Function Model (OFM) is presented. The OFM is a mathematical tool to represent operator interaction with predominantly automated space ground control systems. The design and assessment of an intelligent operator aid (OFMspert and Ally) is particularly discussed. The application of OFM to represent the task knowledge in the design of intelligent tutoring systems, designated OFMTutor and ITSSO (Intelligent Tutoring System for Satellite Operators), is also described. Viewgraphs from symposia presentations are compiled along with papers addressing the intent inferencing capabilities of OFMspert, the OFMTutor system, and an overview of intelligent tutoring systems and the implications for complex dynamic systems.
Intelligent Control of Flexible-Joint Robotic Manipulators
NASA Technical Reports Server (NTRS)
Colbaugh, R.; Gallegos, G.
1997-01-01
This paper considers the trajectory tracking problem for uncertain rigid-link. flexible.joint manipulators, and presents a new intelligent controller as a solution to this problem. The proposed control strategy is simple and computationally efficient, requires little information concerning either the manipulator or actuator/transmission models and ensures uniform boundedness of all signals and arbitrarily accurate task-space trajectory tracking.
Considering User's Access Pattern in Multimedia File Systems
NASA Astrophysics Data System (ADS)
Cho, KyoungWoon; Ryu, YeonSeung; Won, Youjip; Koh, Kern
2002-12-01
Legacy buffer cache management schemes for multimedia server are grounded at the assumption that the application sequentially accesses the multimedia file. However, user access pattern may not be sequential in some circumstances, for example, in distance learning application, where the user may exploit the VCR-like function(rewind and play) of the system and accesses the particular segments of video repeatedly in the middle of sequential playback. Such a looping reference can cause a significant performance degradation of interval-based caching algorithms. And thus an appropriate buffer cache management scheme is required in order to deliver desirable performance even under the workload that exhibits looping reference behavior. We propose Adaptive Buffer cache Management(ABM) scheme which intelligently adapts to the file access characteristics. For each opened file, ABM applies either the LRU replacement or the interval-based caching depending on the Looping Reference Indicator, which indicates that how strong temporally localized access pattern is. According to our experiment, ABM exhibits better buffer cache miss ratio than interval-based caching or LRU, especially when the workload exhibits not only sequential but also looping reference property.
Hu, Wenfeng; Liu, Lu; Feng, Gang
2016-09-02
This paper addresses the output consensus problem of heterogeneous linear multi-agent systems. We first propose a novel distributed event-triggered control scheme. It is shown that, with the proposed control scheme, the output consensus problem can be solved if two matrix equations are satisfied. Then, we further propose a novel self-triggered control scheme, with which continuous monitoring is avoided. By introducing a fixed timer into both event- and self-triggered control schemes, Zeno behavior can be ruled out for each agent. The effectiveness of the event- and self-triggered control schemes is illustrated by an example.
Developing Realistic Behaviors in Adversarial Agents for Air Combat Simulation
1993-12-01
34Building Symbolic Primitives with Continuous Control Rou- tines." Proceedings of the 1st International Conference on Aritificial Intelligence Planning...shortcoming is the minimal Air Force participation in this field. 1-1 Some of the artificial intelligence (AI) personnel at the Air Force Institute of... intelligent system that operates in a moderately complex or unpredictable environment must be reactive. In being reactive the intelligent system must
On Emotional Intelligence: A Conversation with Daniel Goleman.
ERIC Educational Resources Information Center
O'Neil, John
1996-01-01
Emotional intelligence involves a cluster of skills, including self-control, zeal, persistence, and self-motivation. Every child must be taught the essentials of handling anger, managing conflicts, developing empathy, and controlling impulses. Schools must help children recognize and manage their emotions. Educators should model emotional…
Making the Net More Intelligent.
ERIC Educational Resources Information Center
Somers, Doug
1998-01-01
Discusses how service providers can address the challenge of costs and the need for attractive services valuable to business customers. Focuses on Internet service control; applying intelligent networking features to the internet working services dilemma; and providing access control over network-based applications for Internet virtual private…
Multiobjective hyper heuristic scheme for system design and optimization
NASA Astrophysics Data System (ADS)
Rafique, Amer Farhan
2012-11-01
As system design is becoming more and more multifaceted, integrated, and complex, the traditional single objective optimization trends of optimal design are becoming less and less efficient and effective. Single objective optimization methods present a unique optimal solution whereas multiobjective methods present pareto front. The foremost intent is to predict a reasonable distributed pareto-optimal solution set independent of the problem instance through multiobjective scheme. Other objective of application of intended approach is to improve the worthiness of outputs of the complex engineering system design process at the conceptual design phase. The process is automated in order to provide the system designer with the leverage of the possibility of studying and analyzing a large multiple of possible solutions in a short time. This article presents Multiobjective Hyper Heuristic Optimization Scheme based on low level meta-heuristics developed for the application in engineering system design. Herein, we present a stochastic function to manage meta-heuristics (low-level) to augment surety of global optimum solution. Generic Algorithm, Simulated Annealing and Swarm Intelligence are used as low-level meta-heuristics in this study. Performance of the proposed scheme is investigated through a comprehensive empirical analysis yielding acceptable results. One of the primary motives for performing multiobjective optimization is that the current engineering systems require simultaneous optimization of conflicting and multiple. Random decision making makes the implementation of this scheme attractive and easy. Injecting feasible solutions significantly alters the search direction and also adds diversity of population resulting in accomplishment of pre-defined goals set in the proposed scheme.
Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments.
Lee, Jaeseung; Sung, Yunsick; Park, Jong Hyuk
2016-12-01
The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments.
Lightweight Sensor Authentication Scheme for Energy Efficiency in Ubiquitous Computing Environments
Lee, Jaeseung; Sung, Yunsick; Park, Jong Hyuk
2016-01-01
The Internet of Things (IoT) is the intelligent technologies and services that mutually communicate information between humans and devices or between Internet-based devices. In IoT environments, various device information is collected from the user for intelligent technologies and services that control the devices. Recently, wireless sensor networks based on IoT environments are being used in sectors as diverse as medicine, the military, and commerce. Specifically, sensor techniques that collect relevant area data via mini-sensors after distributing smart dust in inaccessible areas like forests or military zones have been embraced as the future of information technology. IoT environments that utilize smart dust are composed of the sensor nodes that detect data using wireless sensors and transmit the detected data to middle nodes. Currently, since the sensors used in these environments are composed of mini-hardware, they have limited memory, processing power, and energy, and a variety of research that aims to make the best use of these limited resources is progressing. This paper proposes a method to utilize these resources while considering energy efficiency, and suggests lightweight mutual verification and key exchange methods based on a hash function that has no restrictions on operation quantity, velocity, and storage space. This study verifies the security and energy efficiency of this method through security analysis and function evaluation, comparing with existing approaches. The proposed method has great value in its applicability as a lightweight security technology for IoT environments. PMID:27916962
Fast packet switching algorithms for dynamic resource control over ATM networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tsang, R.P.; Keattihananant, P.; Chang, T.
1996-12-01
Real-time continuous media traffic, such as digital video and audio, is expected to comprise a large percentage of the network load on future high speed packet switch networks such as ATM. A major feature which distinguishes high speed networks from traditional slower speed networks is the large amount of data the network must process very quickly. For efficient network usage, traffic control mechanisms are essential. Currently, most mechanisms for traffic control (such as flow control) have centered on the support of Available Bit Rate (ABR), i.e., non real-time, traffic. With regard to ATM, for ABR traffic, two major types ofmore » schemes which have been proposed are rate- control and credit-control schemes. Neither of these schemes are directly applicable to Real-time Variable Bit Rate (VBR) traffic such as continuous media traffic. Traffic control for continuous media traffic is an inherently difficult problem due to the time- sensitive nature of the traffic and its unpredictable burstiness. In this study, we present a scheme which controls traffic by dynamically allocating/de- allocating resources among competing VCs based upon their real-time requirements. This scheme incorporates a form of rate- control, real-time burst-level scheduling and link-link flow control. We show analytically potential performance improvements of our rate- control scheme and present a scheme for buffer dimensioning. We also present simulation results of our schemes and discuss the tradeoffs inherent in maintaining high network utilization and statistically guaranteeing many users` Quality of Service.« less
Intelligence and cortical thickness in children with complex partial seizures.
Tosun, Duygu; Caplan, Rochelle; Siddarth, Prabha; Seidenberg, Michael; Gurbani, Suresh; Toga, Arthur W; Hermann, Bruce
2011-07-15
Prior studies on healthy children have demonstrated regional variations and a complex and dynamic relationship between intelligence and cerebral tissue. Yet, there is little information regarding the neuroanatomical correlates of general intelligence in children with epilepsy compared to healthy controls. In vivo imaging techniques, combined with methods for advanced image processing and analysis, offer the potential to examine quantitative mapping of brain development and its abnormalities in childhood epilepsy. A surface-based, computational high resolution 3-D magnetic resonance image analytic technique was used to compare the relationship of cortical thickness with age and intelligence quotient (IQ) in 65 children and adolescents with complex partial seizures (CPS) and 58 healthy controls, aged 6-18 years. Children were grouped according to health status (epilepsy; controls) and IQ level (average and above; below average) and compared on age-related patterns of cortical thickness. Our cross-sectional findings suggest that disruption in normal age-related cortical thickness expression is associated with intelligence in pediatric CPS patients both with average and below average IQ scores. Copyright © 2011 Elsevier Inc. All rights reserved.
Nuclear propulsion control and health monitoring
NASA Technical Reports Server (NTRS)
Walter, P. B.; Edwards, R. M.
1993-01-01
An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.
2006-12-01
intelligent control algorithm embedded in the FADEC . This paper evaluates the LEC, based on critical components research, to demonstrate how an...control action, engine component life usage, and designing an intelligent control algorithm embedded in the FADEC . This paper evaluates the LEC, based on...simulation code for each simulator. One is typically configured to operate as a Full- Authority Digital Electronic Controller ( FADEC
Nuclear propulsion control and health monitoring
NASA Astrophysics Data System (ADS)
Walter, P. B.; Edwards, R. M.
1993-11-01
An integrated control and health monitoring architecture is being developed for the Pratt & Whitney XNR2000 nuclear rocket. Current work includes further development of the dynamic simulation modeling and the identification and configuration of low level controllers to give desirable performance for the various operating modes and faulted conditions. Artificial intelligence and knowledge processing technologies need to be investigated and applied in the development of an intelligent supervisory controller module for this control architecture.
Jahangard, Leila; Haghighi, Mohammad; Bajoghli, Hafez; Ahmadpanah, Mohammad; Ghaleiha, Ali; Zarrabian, Mohammad Kazem; Brand, Serge
2012-09-01
Borderline personality disorder (BPD) is defined as a pervasive pattern of instability in emotion, mood and interpersonal relationships, with a comorbidity between PBD and depressive disorders (DD). A key competence for successful management of interpersonal relationships is emotional intelligence (EI). Given the low EI of patients suffering from BPD, the present study aimed at investigating the effect on both emotional intelligence and depression of training emotional intelligence in patients with BPD and DD. A total of 30 inpatients with BPD and DD (53% females; mean age 24.20 years) took part in the study. Patients were randomly assigned either to the treatment or to the control group. Pre- and post-testing 4 weeks later involved experts' rating of depressive disorder and self-reported EI. The treatment group received 12 sessions of training in components of emotional intelligence. Relative to the control group, EI increased significantly in the treatment group over time. Depressive symptoms decreased significantly over time in both groups, though improvement was greater in the treatment than the control group. For inpatients suffering from BPD and DD, regular skill training in EI can be successfully implemented and leads to improvements both in EI and depression. Results suggest an additive effect of EI training on both EI and depressive symptoms.
Skakkebæk, Anne; Moore, Philip J; Pedersen, Anders Degn; Bojesen, Anders; Kristensen, Maria Krarup; Fedder, Jens; Laurberg, Peter; Hertz, Jens Michael; Østergaard, John Rosendahl; Wallentin, Mikkel; Gravholt, Claus Højbjerg
2017-03-01
The determinants of cognitive deficits among individuals with Klinefelter syndrome (KS) are not well understood. This study was conducted to assess the impact of general intelligence, personality, and social engagement on cognitive performance among patients with KS and a group of controls matched for age and years of education. Sixty-nine patients with KS and 69 controls were assessed in terms of IQ, NEO personality inventory, the Autism Spectrum Quotient (AQ) scale, and measures of cognitive performance reflecting working memory and executive function. Patients with KS performed more poorly on memory and executive-function tasks. Patients with KS also exhibited greater neuroticism and less extraversion, openness, and conscientiousness than controls. Memory deficits among patients with KS were associated with lower intelligence, while diminished executive functioning was mediated by both lower intelligence and less social engagement. Our results suggest that among patients with KS, memory deficits are principally a function of lower general intelligence, while executive-function deficits are associated with both lower intelligence and poorer social skills. This suggests a potential influence of social engagement on executive cognitive functioning (and/or vice-versa) among individuals with KS, and perhaps those with other genetic disorders. Future longitudinal research would be important to further clarify this and other issues discussed in this research.
Intelligent systems technology infrastructure for integrated systems
NASA Technical Reports Server (NTRS)
Lum, Henry, Jr.
1991-01-01
Significant advances have occurred during the last decade in intelligent systems technologies (a.k.a. knowledge-based systems, KBS) including research, feasibility demonstrations, and technology implementations in operational environments. Evaluation and simulation data obtained to date in real-time operational environments suggest that cost-effective utilization of intelligent systems technologies can be realized for Automated Rendezvous and Capture applications. The successful implementation of these technologies involve a complex system infrastructure integrating the requirements of transportation, vehicle checkout and health management, and communication systems without compromise to systems reliability and performance. The resources that must be invoked to accomplish these tasks include remote ground operations and control, built-in system fault management and control, and intelligent robotics. To ensure long-term evolution and integration of new validated technologies over the lifetime of the vehicle, system interfaces must also be addressed and integrated into the overall system interface requirements. An approach for defining and evaluating the system infrastructures including the testbed currently being used to support the on-going evaluations for the evolutionary Space Station Freedom Data Management System is presented and discussed. Intelligent system technologies discussed include artificial intelligence (real-time replanning and scheduling), high performance computational elements (parallel processors, photonic processors, and neural networks), real-time fault management and control, and system software development tools for rapid prototyping capabilities.
Intelligent Systems: Shaping the Future of Aeronautics and Space Exploration
NASA Technical Reports Server (NTRS)
Krishnakumar, Kalmanje; Lohn, Jason; Kaneshige, John
2004-01-01
Intelligent systems are nature-inspired, mathematically sound, computationally intensive problem solving tools and methodologies that have become important for NASA's future roles in Aeronautics and Space Exploration. Intelligent systems will enable safe, cost and mission-effective approaches to air& control, system design, spacecraft autonomy, robotic space exploration and human exploration of Moon, Mars, and beyond. In this talk, we will discuss intelligent system technologies and expand on the role of intelligent systems in NASA's missions. We will also present several examples of which some are highlighted m this extended abstract.
Technicians for Intelligent Buildings. Final Report.
ERIC Educational Resources Information Center
Prescott, Carolyn; Thomson, Ron
"Intelligent building" is a term that has been coined in recent years to describe buildings in which computer technology is intensely applied in two areas of building operations: control systems and shared tenant services. This two-part study provides an overview of the intelligent building industry and reports on issues related to the…
Federal Register 2010, 2011, 2012, 2013, 2014
2010-12-23
... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention [Docket Number NIOSH 161-A] Draft Current Intelligence Bulletin ``Occupational Exposure to Carbon Nanotubes and... carbon nanotubes and to issue its findings on the potential health risks. A draft Current Intelligence...
76 FR 77575 - Information Collection Requests Under OMB Review; Proposed Collection of Information
Federal Register 2010, 2011, 2012, 2013, 2014
2011-12-13
... proposed information collection, Intelligence Background Questionnaire (OMB Control Number 0420--pending... employment any persons who have engaged in intelligence activity or related work or who have been employed by or connected with an intelligence Agency. It is crucial to the Peace Corps in carrying out its...
NASA Technical Reports Server (NTRS)
Lum, Henry, Jr.
1988-01-01
Information on systems autonomy is given in viewgraph form. Information is given on space systems integration, intelligent autonomous systems, automated systems for in-flight mission operations, the Systems Autonomy Demonstration Project on the Space Station Thermal Control System, the architecture of an autonomous intelligent system, artificial intelligence research issues, machine learning, and real-time image processing.
ERIC Educational Resources Information Center
Noe, Jeff
2012-01-01
The purpose of this study was to examine the relationship between secondary school principal's emotional intelligence quotient, school culture, and student achievement. Partial correlation was conducted to examine the degree of relationships between principal's emotional intelligence quotient and school culture controlling for the effect of…
Research of home energy management system based on technology of PLC and ZigBee
NASA Astrophysics Data System (ADS)
Wei, Qi; Shen, Jiaojiao
2015-12-01
In view of the problem of saving effectively energy and energy management in home, this paper designs a home energy intelligent control system based on power line carrier communication and wireless ZigBee sensor networks. The system is based on ARM controller, power line carrier communication and wireless ZigBee sensor network as the terminal communication mode, and realizes the centralized and intelligent control of home appliances. Through the combination of these two technologies, the advantages of the two technologies complement each other, and provide a feasible plan for the construction of energy-efficient, intelligent home energy management system.
Sensor and Actuator Needs for More Intelligent Gas Turbine Engines
NASA Technical Reports Server (NTRS)
Garg, Sanjay; Schadow, Klaus; Horn, Wolfgang; Pfoertner, Hugo; Stiharu, Ion
2010-01-01
This paper provides an overview of the controls and diagnostics technologies, that are seen as critical for more intelligent gas turbine engines (GTE), with an emphasis on the sensor and actuator technologies that need to be developed for the controls and diagnostics implementation. The objective of the paper is to help the "Customers" of advanced technologies, defense acquisition and aerospace research agencies, understand the state-of-the-art of intelligent GTE technologies, and help the "Researchers" and "Technology Developers" for GTE sensors and actuators identify what technologies need to be developed to enable the "Intelligent GTE" concepts and focus their research efforts on closing the technology gap. To keep the effort manageable, the focus of the paper is on "On-Board Intelligence" to enable safe and efficient operation of the engine over its life time, with an emphasis on gas path performance
Defence R&D Canada's autonomous intelligent systems program
NASA Astrophysics Data System (ADS)
Digney, Bruce L.; Hubbard, Paul; Gagnon, Eric; Lauzon, Marc; Rabbath, Camille; Beckman, Blake; Collier, Jack A.; Penzes, Steven G.; Broten, Gregory S.; Monckton, Simon P.; Trentini, Michael; Kim, Bumsoo; Farell, Philip; Hopkin, Dave
2004-09-01
The Defence Research and Development Canada's (DRDC has been given strategic direction to pursue research to increase the independence and effectiveness of military vehicles and systems. This has led to the creation of the Autonomous Intelligent Systems (AIS) prgram and is notionally divide into air, land and marine vehicle systems as well as command, control and decision support systems. This paper presents an overarching description of AIS research issues, challenges and directions as well as a nominal path that vehicle intelligence will take. The AIS program requires a very close coordination between research and implementation on real vehicles. This paper briefly discusses the symbiotic relationship between intelligence algorithms and implementation mechanisms. Also presented are representative work from two vehicle specific research program programs. Work from the Autonomous Air Systems program discusses the development of effective cooperate control for multiple air vehicle. The Autonomous Land Systems program discusses its developments in platform and ground vehicle intelligence.
A computer architecture for intelligent machines
NASA Technical Reports Server (NTRS)
Lefebvre, D. R.; Saridis, G. N.
1991-01-01
The Theory of Intelligent Machines proposes a hierarchical organization for the functions of an autonomous robot based on the Principle of Increasing Precision With Decreasing Intelligence. An analytic formulation of this theory using information-theoretic measures of uncertainty for each level of the intelligent machine has been developed in recent years. A computer architecture that implements the lower two levels of the intelligent machine is presented. The architecture supports an event-driven programming paradigm that is independent of the underlying computer architecture and operating system. Details of Execution Level controllers for motion and vision systems are addressed, as well as the Petri net transducer software used to implement Coordination Level functions. Extensions to UNIX and VxWorks operating systems which enable the development of a heterogeneous, distributed application are described. A case study illustrates how this computer architecture integrates real-time and higher-level control of manipulator and vision systems.
Heising, Jenneke K; Claassen, G D H; Dekker, Matthijs
2017-10-01
Optimising supply chain management can help to reduce food waste. This paper describes how intelligent packaging can be used to reduce food waste when used in supply chain management based on quality-controlled logistics (QCL). Intelligent packaging senses compounds in the package that correlate with the critical quality attribute of a food product. The information on the quality of each individual packaged food item that is provided by the intelligent packaging can be used for QCL. In a conceptual approach it is explained that monitoring food quality by intelligent packaging sensors makes it possible to obtain information about the variation in the quality of foods and to use a dynamic expiration date (IP-DED) on a food package. The conceptual approach is supported by quantitative data from simulations on the effect of using the information of intelligent packaging in supply chain management with the goal to reduce food waste. This simulation shows that by using the information on the quality of products that is provided by intelligent packaging, QCL can substantially reduce food waste. When QCL is combined with dynamic pricing based on the predicted expiry dates, a further waste reduction is envisaged.
A shared position/force control methodology for teleoperation
NASA Technical Reports Server (NTRS)
Lee, Jin S.
1987-01-01
A flexible and computationally efficient shared position/force control concept and its implementation in the Robot Control C Library (RCCL) are presented form the point of teleoperation. This methodology enables certain degrees of freedom to be position-controlled through real time manual inputs and the remaining degrees of freedom to be force-controlled by computer. Functionally, it is a hybrid control scheme in that certain degrees of freedom are designated to be under position control, and the remaining degrees of freedom to be under force control. However, the methodology is also a shared control scheme because some degrees of freedom can be put under manual control and the other degrees of freedom put under computer control. Unlike other hybrid control schemes, which process position and force commands independently, this scheme provides a force control loop built on top of a position control inner loop. This feature minimizes the computational burden and increases disturbance rejection. A simple implementation is achieved partly because the joint control servos that are part of most robots can be used to provide the position control inner loop. Along with this control scheme, several menus were implemented for the convenience of the user. The implemented control scheme was successfully demonstrated for the tasks of hinged-panel opening and peg-in-hole insertion.
Intelligent electric vehicle charging: Rethinking the valley-fill
NASA Astrophysics Data System (ADS)
Valentine, Keenan; Temple, William G.; Zhang, K. Max
This study proposes an intelligent PEV charging scheme that significantly reduces power system cost while maintaining reliability compared to the widely discussed valley-fill method of aggregated charging in the early morning. This study considers optimal PEV integration into the New York Independent System Operator's (NYISO) day-ahead and real-time wholesale energy markets for 21 days in June, July, and August of 2006, a record-setting summer for peak load. NYISO market and load data is used to develop a statistical Locational Marginal Price (LMP) and wholesale energy cost model. This model considers the high cost of ramping generators at peak-load and the traditional cost of steady-state operation, resulting in a framework with two competing cost objectives. Results show that intelligent charging assigns roughly 80% of PEV load to valley hours to take advantage of low steady-state cost, while placing the remaining 20% equally at shoulder and peak hours to reduce ramping cost. Compared to unregulated PEV charging, intelligent charging reduces system cost by 5-16%; a 4-9% improvement over the flat valley-fill approach. Moreover, a Charge Flexibility Constraint (CFC), independent of market modeling, is constructed from a vehicle-at-home profile and the mixture of Level 1 and Level 2 charging infrastructure. The CFC is found to severely restrict the ability to charge vehicles during the morning load valley. This study further shows that adding more Level 2 chargers without regulating PEV charging will significantly increase wholesale energy cost. Utilizing the proposed intelligent PEV charging method, there is a noticeable reduction in system cost if the penetration of Level 2 chargers is increased from 70/30 to 50/50 (Level 1/Level 2). However, the system benefit is drastically diminished for higher penetrations of Level 2 chargers.
A threat intelligence framework for access control security in the oil industry
NASA Astrophysics Data System (ADS)
Alaskandrani, Faisal T.
The research investigates the problem raised by the rapid development in the technology industry giving security concerns in facilities built by the energy industry containing diverse platforms. The difficulty of continuous updates to network security architecture and assessment gave rise to the need to use threat intelligence frameworks to better assess and address networks security issues. Focusing on access control security to the ICS and SCADA systems that is being utilized to carry out mission critical and life threatening operations. The research evaluates different threat intelligence frameworks that can be implemented in the industry seeking the most suitable and applicable one that address the issue and provide more security measures. The validity of the result is limited to the same environment that was researched as well as the technologies being utilized. The research concludes that it is possible to utilize a Threat Intelligence framework to prioritize security in Access Control Measures in the Oil Industry.
An intelligent control and virtual display system for evolutionary space station workstation design
NASA Technical Reports Server (NTRS)
Feng, Xin; Niederjohn, Russell J.; Mcgreevy, Michael W.
1992-01-01
Research and development of the Advanced Display and Computer Augmented Control System (ADCACS) for the space station Body-Ported Cupola Virtual Workstation (BP/VCWS) were pursued. The potential applications were explored of body ported virtual display and intelligent control technology for the human-system interfacing applications is space station environment. The new system is designed to enable crew members to control and monitor a variety of space operations with greater flexibility and efficiency than existing fixed consoles. The technologies being studied include helmet mounted virtual displays, voice and special command input devices, and microprocessor based intelligent controllers. Several research topics, such as human factors, decision support expert systems, and wide field of view, color displays are being addressed. The study showed the significant advantages of this uniquely integrated display and control system, and its feasibility for human-system interfacing applications in the space station command and control environment.
Intelligent Tracking Control for a Class of Uncertain High-Order Nonlinear Systems.
Zhao, Xudong; Shi, Peng; Zheng, Xiaolong; Zhang, Jianhua
2016-09-01
This brief is concerned with the problem of intelligent tracking control for a class of high-order nonlinear systems with completely unknown nonlinearities. An intelligent adaptive control algorithm is presented by combining the adaptive backstepping technique with the neural networks' approximation ability. It is shown that the practical output tracking performance of the system is achieved using the proposed state-feedback controller under two mild assumptions. In particular, by introducing a parameter in the derivations, the tracking error between the time-varying target signal and the output can be reduced via tuning the controller design parameters. Moreover, in order to solve the problem of overparameterization, which is a common issue in adaptive control design, a controller with one adaptive law is also designed. Finally, simulation results are given to show the effectiveness of the theoretical approaches and the potential of the proposed new design techniques.
F-15 837 IFCS Intelligent Flight Control System Project
NASA Technical Reports Server (NTRS)
Bosworth, John T.
2007-01-01
This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.
Development of advanced control schemes for telerobot manipulators
NASA Technical Reports Server (NTRS)
Nguyen, Charles C.; Zhou, Zhen-Lei
1991-01-01
To study space applications of telerobotics, Goddard Space Flight Center (NASA) has recently built a testbed composed mainly of a pair of redundant slave arms having seven degrees of freedom and a master hand controller system. The mathematical developments required for the computerized simulation study and motion control of the slave arms are presented. The slave arm forward kinematic transformation is presented which is derived using the D-H notation and is then reduced to its most simplified form suitable for real-time control applications. The vector cross product method is then applied to obtain the slave arm Jacobian matrix. Using the developed forward kinematic transformation and quaternions representation of the slave arm end-effector orientation, computer simulation is conducted to evaluate the efficiency of the Jacobian in converting joint velocities into Cartesian velocities and to investigate the accuracy of the Jacobian pseudo-inverse for various sampling times. In addition, the equivalence between Cartesian velocities and quaternion is also verified using computer simulation. The motion control of the slave arm is examined. Three control schemes, the joint-space adaptive control scheme, the Cartesian adaptive control scheme, and the hybrid position/force control scheme are proposed for controlling the motion of the slave arm end-effector. Development of the Cartesian adaptive control scheme is presented and some preliminary results of the remaining control schemes are presented and discussed.
Cortés, Ulises; Annicchiarico, Roberta; Campana, Fabio; Vázquez-Salceda, Javier; Urdiales, Cristina; Canãmero, Lola; López, Maite; Sánchez-Marrè, Miquel; Di Vincenzo, Sarah; Caltagirone, Carlo
2004-04-01
A project based on the integration of new technologies and artificial intelligence to develop a device--e-tool--for disabled patients and elderly people is presented. A mobile platform in intelligent environments (skilled-care facilities and home-care), controlled and managed by a multi-level architecture, is proposed to support patients and caregivers to increase self-dependency in activities of daily living.
The 1990 Goddard Conference on Space Applications of Artificial Intelligence
NASA Technical Reports Server (NTRS)
Rash, James L. (Editor)
1990-01-01
The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.
Active control of multiple resistive wall modes
NASA Astrophysics Data System (ADS)
Brunsell, P. R.; Yadikin, D.; Gregoratto, D.; Paccagnella, R.; Liu, Y. Q.; Bolzonella, T.; Cecconello, M.; Drake, J. R.; Kuldkepp, M.; Manduchi, G.; Marchiori, G.; Marrelli, L.; Martin, P.; Menmuir, S.; Ortolani, S.; Rachlew, E.; Spizzo, G.; Zanca, P.
2005-12-01
A two-dimensional array of saddle coils at Mc poloidal and Nc toroidal positions is used on the EXTRAP T2R reversed-field pinch (Brunsell P R et al 2001 Plasma Phys. Control. Fusion 43 1457) to study active control of resistive wall modes (RWMs). Spontaneous growth of several RWMs with poloidal mode number m = 1 and different toroidal mode number n is observed experimentally, in agreement with linear MHD modelling. The measured plasma response to a controlled coil field and the plasma response computed using the linear circular cylinder MHD model are in quantitive agreement. Feedback control introduces a linear coupling of modes with toroidal mode numbers n, n' that fulfil the condition |n - n'| = Nc. Pairs of coupled unstable RWMs are present in feedback experiments with an array of Mc × Nc = 4 × 16 coils. Using intelligent shell feedback, the coupled modes are generally not controlled even though the field is suppressed at the active coils. A better suppression of coupled modes may be achieved in the case of rotating modes by using the mode control feedback scheme with individually set complex gains. In feedback with a larger array of Mc × Nc = 4 × 32 coils, the coupling effect largely disappears, and with this array, the main internal RWMs n = -11, -10, +5, +6 are all simultaneously suppressed throughout the discharge (7 8 wall times). With feedback there is a two-fold extension of the pulse length, compared to discharges without feedback.
ERIC Educational Resources Information Center
Duckworth, Angela L.; Quinn, Patrick D.; Tsukayama, Eli
2012-01-01
The increasing prominence of standardized testing to assess student learning motivated the current investigation. We propose that standardized achievement test scores assess competencies determined more by intelligence than by self-control, whereas report card grades assess competencies determined more by self-control than by intelligence. In…
A state-based approach to trend recognition and failure prediction for the Space Station Freedom
NASA Technical Reports Server (NTRS)
Nelson, Kyle S.; Hadden, George D.
1992-01-01
A state-based reasoning approach to trend recognition and failure prediction for the Altitude Determination, and Control System (ADCS) of the Space Station Freedom (SSF) is described. The problem domain is characterized by features (e.g., trends and impending failures) that develop over a variety of time spans, anywhere from several minutes to several years. Our state-based reasoning approach, coupled with intelligent data screening, allows features to be tracked as they develop in a time-dependent manner. That is, each state machine has the ability to encode a time frame for the feature it detects. As features are detected, they are recorded and can be used as input to other state machines, creating a hierarchical feature recognition scheme. Furthermore, each machine can operate independently of the others, allowing simultaneous tracking of features. State-based reasoning was implemented in the trend recognition and the prognostic modules of a prototype Space Station Freedom Maintenance and Diagnostic System (SSFMDS) developed at Honeywell's Systems and Research Center.
NASA Astrophysics Data System (ADS)
Koliopoulos, T. C.; Koliopoulou, G.
2007-10-01
We present an input-output solution for simulating the associated behavior and optimized physical needs of an environmental system. The simulations and numerical analysis determined the accurate boundary loads and areas that were required to interact for the proper physical operation of a complicated environmental system. A case study was conducted to simulate the optimum balance of an environmental system based on an artificial intelligent multi-interacting input-output numerical scheme. The numerical results were focused on probable further environmental management techniques, with the objective of minimizing any risks and associated environmental impact to protect the quality of public health and the environment. Our conclusions allowed us to minimize the associated risks, focusing on probable cases in an emergency to protect the surrounded anthropogenic or natural environment. Therefore, the lining magnitude could be determined for any useful associated technical works to support the environmental system under examination, taking into account its particular boundary necessities and constraints.
A reusable rocket engine intelligent control
NASA Technical Reports Server (NTRS)
Merrill, Walter C.; Lorenzo, Carl F.
1988-01-01
An intelligent control system for reusable space propulsion systems for future launch vehicles is described. The system description includes a framework for the design. The framework consists of an execution level with high-speed control and diagnostics, and a coordination level which marries expert system concepts with traditional control. A comparison is made between air breathing and rocket engine control concepts to assess the relative levels of development and to determine the applicability of air breathing control concepts ot future reusable rocket engine systems.
Automatic intelligibility classification of sentence-level pathological speech
Kim, Jangwon; Kumar, Naveen; Tsiartas, Andreas; Li, Ming; Narayanan, Shrikanth S.
2014-01-01
Pathological speech usually refers to the condition of speech distortion resulting from atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other physical or biological insult to the production system. Although automatic evaluation of speech intelligibility and quality could come in handy in these scenarios to assist experts in diagnosis and treatment design, the many sources and types of variability often make it a very challenging computational processing problem. In this work we propose novel sentence-level features to capture abnormal variation in the prosodic, voice quality and pronunciation aspects in pathological speech. In addition, we propose a post-classification posterior smoothing scheme which refines the posterior of a test sample based on the posteriors of other test samples. Finally, we perform feature-level fusions and subsystem decision fusion for arriving at a final intelligibility decision. The performances are tested on two pathological speech datasets, the NKI CCRT Speech Corpus (advanced head and neck cancer) and the TORGO database (cerebral palsy or amyotrophic lateral sclerosis), by evaluating classification accuracy without overlapping subjects’ data among training and test partitions. Results show that the feature sets of each of the voice quality subsystem, prosodic subsystem, and pronunciation subsystem, offer significant discriminating power for binary intelligibility classification. We observe that the proposed posterior smoothing in the acoustic space can further reduce classification errors. The smoothed posterior score fusion of subsystems shows the best classification performance (73.5% for unweighted, and 72.8% for weighted, average recalls of the binary classes). PMID:25414544
Martin, A K; Mowry, B; Reutens, D; Robinson, G A
2015-10-01
Patients with schizophrenia often display deficits on tasks thought to measure "executive" processes. Recently, it has been suggested that reductions in fluid intelligence test performance entirely explain deficits reported for patients with focal frontal lesions on classical executive tasks. For patients with schizophrenia, it is unclear whether deficits on executive tasks are entirely accountable by fluid intelligence and representative of a common general process or best accounted for by distinct contributions to the cognitive profile of schizophrenia. In the current study, 50 patients with schizophrenia and 50 age, sex and premorbid intelligence matched controls were assessed using a broad neuropsychological battery, including tasks considered sensitive to executive abilities, namely the Hayling Sentence Completion Test (HSCT), word fluency, Stroop test, digit-span backwards, and spatial working memory. Fluid intelligence was measured using both the Matrix reasoning subtest from the Weschler Abbreviated Scale of Intelligence (WASI) and a composite score derived from a number of cognitive tests. Patients with schizophrenia were impaired on all cognitive measures compared with controls, except smell identification and the optimal betting and risk-taking measures from the Cambridge Gambling Task. After introducing fluid intelligence as a covariate, significant differences remained for HSCT suppression errors, and classical executive function tests such as the Stroop test and semantic/phonemic word fluency, regardless of which fluid intelligence measure was included. Fluid intelligence does not entirely explain impaired performance on all tests considered as reflecting "executive" processes. For schizophrenia, these measures should remain part of a comprehensive neuropsychological assessment alongside a measure of fluid intelligence. Copyright © 2015 Elsevier Inc. All rights reserved.
Full-Scale Flight Research Testbeds: Adaptive and Intelligent Control
NASA Technical Reports Server (NTRS)
Pahle, Joe W.
2008-01-01
This viewgraph presentation describes the adaptive and intelligent control methods used for aircraft survival. The contents include: 1) Motivation for Adaptive Control; 2) Integrated Resilient Aircraft Control Project; 3) Full-scale Flight Assets in Use for IRAC; 4) NASA NF-15B Tail Number 837; 5) Gen II Direct Adaptive Control Architecture; 6) Limited Authority System; and 7) 837 Flight Experiments. A simulated destabilization failure analysis along with experience and lessons learned are also presented.
Intelligence and Academic Achievement With Asymptomatic Congenital Cytomegalovirus Infection.
Lopez, Adriana S; Lanzieri, Tatiana M; Claussen, Angelika H; Vinson, Sherry S; Turcich, Marie R; Iovino, Isabella R; Voigt, Robert G; Caviness, A Chantal; Miller, Jerry A; Williamson, W Daniel; Hales, Craig M; Bialek, Stephanie R; Demmler-Harrison, Gail
2017-11-01
To examine intelligence, language, and academic achievement through 18 years of age among children with congenital cytomegalovirus infection identified through hospital-based newborn screening who were asymptomatic at birth compared with uninfected infants. We used growth curve modeling to analyze trends in IQ (full-scale, verbal, and nonverbal intelligence), receptive and expressive vocabulary, and academic achievement in math and reading. Separate models were fit for each outcome, modeling the change in overall scores with increasing age for patients with normal hearing ( n = 78) or with sensorineural hearing loss (SNHL) diagnosed by 2 years of age ( n = 11) and controls ( n = 40). Patients with SNHL had full-scale intelligence and receptive vocabulary scores that were 7.0 and 13.1 points lower, respectively, compared with controls, but no significant differences were noted in these scores among patients with normal hearing and controls. No significant differences were noted in scores for verbal and nonverbal intelligence, expressive vocabulary, and academic achievement in math and reading among patients with normal hearing or with SNHL and controls. Infants with asymptomatic congenital cytomegalovirus infection identified through newborn screening with normal hearing by age 2 years do not appear to have differences in IQ, vocabulary or academic achievement scores during childhood, or adolescence compared with uninfected children. Copyright © 2017 by the American Academy of Pediatrics.
[Short-term sentence memory in children with auditory processing disorders].
Kiese-Himmel, C
2010-05-01
To compare sentence repetition performance of different groups of children with Auditory Processing Disorders (APD) and to examine the relationship between age or respectively nonverbal intelligence and sentence recall. Nonverbal intelligence was measured with the COLOURED MATRICES, in addition the children completed a standardized test of SENTENCE REPETITION (SR) which requires to repeat spoken sentences (subtest of the HEIDELBERGER SPRACHENTWICKLUNGSTEST). Three clinical groups (n=49 with monosymptomatic APD; n=29 with APD+developmental language impairment; n=14 with APD+developmental dyslexia); two control groups (n=13 typically developing peers without any clinical developmental disorder; n=10 children with slight reduced nonverbal intelligence). The analysis showed a significant group effect (p=0.0007). The best performance was achieved by the normal controls (T-score 52.9; SD 6.4; Min 42; Max 59) followed by children with monosymptomatic APD (43.2; SD 9.2), children with the co-morbid-conditions APD+developmental dyslexia (43.1; SD 10.3), and APD+developmental language impairment (39.4; SD 9.4). The clinical control group presented the lowest performance, on average (38.6; SD 9.6). Accordingly, language-impaired children and children with slight reductions in intelligence could poorly use their grammatical knowledge for SR. A statistically significant improvement in SR was verified with the increase of age with the exception of children belonging to the small group with lowered intelligence. This group comprised the oldest children. Nonverbal intelligence correlated positively with SR only in children with below average-range intelligence (0.62; p=0.054). The absence of APD, SLI as well as the presence of normal intelligence facilitated the use of phonological information for SR.
DOT National Transportation Integrated Search
1998-07-01
This report is one element of a cooperative agreement between NHTSA and UMTRI entitled Intelligent Cruise Control (ICC) Field Operational Test (FOT). It addresses the operation of a serial string or dense cluster of passenger cars equipped with a new...
Building intelligent systems: Artificial intelligence research at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Friedland, P.; Lum, H.
1987-01-01
The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a truly autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.
Building intelligent systems - Artificial intelligence research at NASA Ames Research Center
NASA Technical Reports Server (NTRS)
Friedland, Peter; Lum, Henry
1987-01-01
The basic components that make up the goal of building autonomous intelligent systems are discussed, and ongoing work at the NASA Ames Research Center is described. It is noted that a clear progression of systems can be seen through research settings (both within and external to NASA) to Space Station testbeds to systems which actually fly on the Space Station. The starting point for the discussion is a 'truly' autonomous Space Station intelligent system, responsible for a major portion of Space Station control. Attention is given to research in fiscal 1987, including reasoning under uncertainty, machine learning, causal modeling and simulation, knowledge from design through operations, advanced planning work, validation methodologies, and hierarchical control of and distributed cooperation among multiple knowledge-based systems.
Birth order has no effect on intelligence: a reply and extension of previous findings.
Wichman, Aaron L; Rodgers, Joseph Lee; Maccallum, Robert C
2007-09-01
We address points raised by Zajonc and Sulloway, who reject findings showing that birth order has no effect on intelligence. Many objections to findings of null birth-order results seem to stem from a misunderstanding of the difference between study designs where birth order is confounded with true causal influences on intelligence across families and designs that control for some of these influences. We discuss some of the consequences of not appreciating the nature of this difference. When between-family confounds are controlled using appropriate study designs and techniques such as multilevel modeling, birth order is shown not to influence intelligence. We conclude with an empirical investigation of the replicability and generalizability of this approach.
Da Fonseca, D; Cury, F; Rufo, M; Poinso, F
2007-10-01
The aim of this study was to complete the identification of predictive factors of depression during adolescence. For some authors, depression is characterized by a style of attribution, which consists essentially in attributing most of the negative outcomes to internal, stable, and uncontrollable factors. It seems that these attributions depend essentially on the type of their beliefs and in particular, those concerning the nature of intelligence. These beliefs called "implicit theories of intelligence", are the entity theory of intelligence and the incremental theory of intelligence. The entity theory of intelligence corresponds to the belief according to which intelligence is the expression of a relatively stable, fixed, and noncontrollable feature, and which we cannot change. In contrast, the incremental theory corresponds to the belief according to which intelligence is a controllable quality, which we can develop through effort and work. Several studies have demonstrated that the adolescents who consider intelligence as a malleable quality explain their bad results by internal, unstable, and controllable factors. Conversely, students who consider intelligence as a fixed capacity tend to strongly attribute their failure to internal, stable, and uncontrollable factors. We have consequently formulated the hypothesis according to which the entity theory should be a predictive factor of depression. We have also tested the fact that anxiety should be a mediating factor within the relation between the entity theory and depression. The sample was composed of 424 adolescents. Using different questionnaires, we measured implicit theories of the intelligence (TIDI), self-esteem (EES), anxiety (STAI-Form Y-B) and depression (CDI). Multiple regression analyses demonstrated that the entity theory of intelligence positively predicts depression. Self-esteem negatively predicts anxiety and depression. Moreover, anxiety is a mediator of the relation between self-esteem and depression, on one hand, and the relation between the entity theory of intelligence and depression, on the other. Finally, the effect of the entity theory of intelligence appears to be modulated by the level of self-esteem. This study explains the mechanisms by which the implicit theories of intelligence engender anxiety and depression. Furthermore, this approach provides interesting perspectives in the prevention and management of adolescents presenting depression.
Active optical control system design of the SONG-China Telescope
NASA Astrophysics Data System (ADS)
Ye, Yu; Kou, Songfeng; Niu, Dongsheng; Li, Cheng; Wang, Guomin
2012-09-01
The standard SONG node structure of control system is presented. The active optical control system of the project is a distributed system, and a host computer and a slave intelligent controller are included. The host control computer collects the information from wave front sensor and sends commands to the slave computer to realize a closed loop model. For intelligent controller, a programmable logic controller (PLC) system is used. This system combines with industrial personal computer (IPC) and PLC to make up a control system with powerful and reliable.
NASA Astrophysics Data System (ADS)
Ison, Mark; Artemiadis, Panagiotis
2014-10-01
Myoelectric control is filled with potential to significantly change human-robot interaction due to the ability to non-invasively measure human motion intent. However, current control schemes have struggled to achieve the robust performance that is necessary for use in commercial applications. As demands in myoelectric control trend toward simultaneous multifunctional control, multi-muscle coordinations, or synergies, play larger roles in the success of the control scheme. Detecting and refining patterns in muscle activations robust to the high variance and transient changes associated with surface electromyography is essential for efficient, user-friendly control. This article reviews the role of muscle synergies in myoelectric control schemes by dissecting each component of the scheme with respect to associated challenges for achieving robust simultaneous control of myoelectric interfaces. Electromyography recording details, signal feature extraction, pattern recognition and motor learning based control schemes are considered, and future directions are proposed as steps toward fulfilling the potential of myoelectric control in clinically and commercially viable applications.
A cascaded coding scheme for error control
NASA Technical Reports Server (NTRS)
Shu, L.; Kasami, T.
1985-01-01
A cascade coding scheme for error control is investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are evaluated. They seem to be quite suitable for satellite down-link error control.
A cascaded coding scheme for error control
NASA Technical Reports Server (NTRS)
Kasami, T.; Lin, S.
1985-01-01
A cascaded coding scheme for error control was investigated. The scheme employs a combination of hard and soft decisions in decoding. Error performance is analyzed. If the inner and outer codes are chosen properly, extremely high reliability can be attained even for a high channel bit-error-rate. Some example schemes are studied which seem to be quite suitable for satellite down-link error control.
[Intelligence and irritable bowel syndrome].
Díaz-Rubio García, Manuel
2006-01-01
The Syndrome of Irritable Intestine (SII) is a chronic functional dysfunction that it is characterized by abdominal pain and changes of intestinal rhythm without demonstrable organic alteration. It is avery prevelent dysfunction in the developed countries, there being involved in its physiopathology, among other, the psychosocial factors (illness behavior, social situation, stress, vital events, neuroticism, anxiety and somatization). However no study has been carried out on the Rational Intelligence and Experiential Intelligence or Constructive Thought in patient with SII in spite of knowing that the cognitive processes participate in its genesis. On the hypothesis that the patients with SII would have an experiencial intelligence smaller that the fellows controls, 100 cases of SII and 100 controls have been studied, being excluded of both patients groups with intellectual deficit or psychiatric illness in the last year. The cases of SII were distributed in two groups, one of 50 cases that habitually consulted with the doctor and other 50 that didn't make it. All the participants completed specific tests to evaluate all the psychological factors and Rational Intelligence and the Constructive Thought. The results show an alteration of the psychological factors in the SII, expressed by the antecedents of vital events, m even significant of anxiety feature and anxiety and a neuroticism statistically significant. As for Rational Intelligence and Experiential Intelligence in the SII, it was observed that to Rational Intelligence is same in the patients with SII that in the controls. Only in the group of SII that habitually consulted with the doctor a slightly significant decrease of the intellectual coefficient it was observed. As for the Experiential Intelligence a significant decrease of the Constructive Thought was observed in the patients with SII in comparison with the group control. Of their components a decrease of the emotionality exists and of the effectiveness, an increase of the superstitious thought and of the rigidity, being the occult thought and the illusion is the same as in the group control. In synthesis, they are associated factors to suffer SII a bigger neuroticism and an increase of the level of anxiety feature and state, and of the vital stressful events, as well as a decrease of the Constructive Thought. On the contrary they would be associated factors to consult the doctor an increase of the anxiety, a decrease of the Constructive Thought and a decrease of Rational Intelligence. The implications of these discoveries can be physiopathological and therapeutic, since the Experiencial Intelligence is relates with the stress grade auto-generated by the "normal" events of the daily life. Questions without answering are if it could be the biological answer to this auto-generated stress an important factor in the pathogenia of the SII or if this stress could be the nexus of union of the SII with the neuroticism and the anxiety. As for the therapy, and since the Experiential Intelligence is amendable, it would be necessary to think about if the modification of the Experiential Intelligence by means of a therapeutic intervention would bear an improvement of the symptoms of the SII.
Working Memory and Fluid Intelligence in Young Children
ERIC Educational Resources Information Center
Engel de Abreu, Pascale M. J.; Conway, Andrew R. A.; Gathercole, Susan E.
2010-01-01
The present study investigates how working memory and fluid intelligence are related in young children and how these links develop over time. The major aim is to determine which aspect of the working memory system--short-term storage or cognitive control--drives the relationship with fluid intelligence. A sample of 119 children was followed from…
2016-09-01
other associated grants. 15. SUBJECT TERMS SUNY Poly, STEM, Artificial Intelligence , Command and Control 16. SECURITY CLASSIFICATION OF: 17...neuromorphic system has the potential to be widely used in a high-efficiency artificial intelligence system. Simulation results have indicated that the...novel multiresolution fusion and advanced fusion performance evaluation tool for an Artificial Intelligence based natural language annotation engine for
The Development, Testing, and Evaluation of an Emotional Intelligence Curriculum.
ERIC Educational Resources Information Center
Fischer, Ronald G.; Fischer, Jerome M.
2003-01-01
Adult students using an emotional intelligence (EI) curriculum (n=13) and 15 controls in a composition class completed the Emotional Intelligence Test and Emotional Content Quality Index. Significant pre- to posttest changes in the EI group suggest the curriculum positively increased their ability to identify, reflect on, process, and manage…
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... OFFICE OF THE DIRECTOR OF NATIONAL INTELLIGENCE [OMB Control No.-3440-NEW] Office of the Chief... Intelligence (ODNI). ACTION: Information Collection Activities: Proposed Collection; Comment Request--30 Day... procedures for use by the Intelligence Community agencies and elements, as defined by the National Security...
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ERIC Educational Resources Information Center
Ashraf, Hamid; Hosseinnia, Mansooreh; Domsky, Javad GH.
2017-01-01
Emotional intelligence is the capability to realize, to create, to comprehend emotions and sentimental knowledge, and to reflectively control emotions and to improve emotional and mental growth. The purpose of this study is to examine the relationship between EFL teachers' commitment to professional ethics and their emotional intelligence. To…
75 FR 76664 - Commerce Control List: Revising Descriptions of Items and Foreign Availability
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2010-12-09
... intelligence advantage; and the availability of the item outside certain groups of countries. DATES: Comments... an item provides the United States with a military or intelligence advantage and (b) the availability... military or intelligence advantage to the United States. Tier 2 items are almost exclusively available from...
Maze learning by a hybrid brain-computer system
NASA Astrophysics Data System (ADS)
Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan
2016-09-01
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.
Maze learning by a hybrid brain-computer system.
Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan
2016-09-13
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.
Maze learning by a hybrid brain-computer system
Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan
2016-01-01
The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326
Evolvable mathematical models: A new artificial Intelligence paradigm
NASA Astrophysics Data System (ADS)
Grouchy, Paul
We develop a novel Artificial Intelligence paradigm to generate autonomously artificial agents as mathematical models of behaviour. Agent/environment inputs are mapped to agent outputs via equation trees which are evolved in a manner similar to Symbolic Regression in Genetic Programming. Equations are comprised of only the four basic mathematical operators, addition, subtraction, multiplication and division, as well as input and output variables and constants. From these operations, equations can be constructed that approximate any analytic function. These Evolvable Mathematical Models (EMMs) are tested and compared to their Artificial Neural Network (ANN) counterparts on two benchmarking tasks: the double-pole balancing without velocity information benchmark and the challenging discrete Double-T Maze experiments with homing. The results from these experiments show that EMMs are capable of solving tasks typically solved by ANNs, and that they have the ability to produce agents that demonstrate learning behaviours. To further explore the capabilities of EMMs, as well as to investigate the evolutionary origins of communication, we develop NoiseWorld, an Artificial Life simulation in which interagent communication emerges and evolves from initially noncommunicating EMM-based agents. Agents develop the capability to transmit their x and y position information over a one-dimensional channel via a complex, dialogue-based communication scheme. These evolved communication schemes are analyzed and their evolutionary trajectories examined, yielding significant insight into the emergence and subsequent evolution of cooperative communication. Evolved agents from NoiseWorld are successfully transferred onto physical robots, demonstrating the transferability of EMM-based AIs from simulation into physical reality.
Unified Approach To Control Of Motions Of Mobile Robots
NASA Technical Reports Server (NTRS)
Seraji, Homayoun
1995-01-01
Improved computationally efficient scheme developed for on-line coordinated control of both manipulation and mobility of robots that include manipulator arms mounted on mobile bases. Present scheme similar to one described in "Coordinated Control of Mobile Robotic Manipulators" (NPO-19109). Both schemes based on configuration-control formalism. Present one incorporates explicit distinction between holonomic and nonholonomic constraints. Several other prior articles in NASA Tech Briefs discussed aspects of configuration-control formalism. These include "Increasing the Dexterity of Redundant Robots" (NPO-17801), "Redundant Robot Can Avoid Obstacles" (NPO-17852), "Configuration-Control Scheme Copes with Singularities" (NPO-18556), "More Uses for Configuration Control of Robots" (NPO-18607/NPO-18608).
Controlled quantum perfect teleportation of multiple arbitrary multi-qubit states
NASA Astrophysics Data System (ADS)
Shi, Runhua; Huang, Liusheng; Yang, Wei; Zhong, Hong
2011-12-01
We present an efficient controlled quantum perfect teleportation scheme. In our scheme, multiple senders can teleport multiple arbitrary unknown multi-qubit states to a single receiver via a previously shared entanglement state with the help of one or more controllers. Furthermore, our scheme has a very good performance in the measurement and operation complexity, since it only needs to perform Bell state and single-particle measurements and to apply Controlled-Not gate and other single-particle unitary operations. In addition, compared with traditional schemes, our scheme needs less qubits as the quantum resources and exchanges less classical information, and thus obtains higher communication efficiency.