Constructive thinking, rational intelligence and irritable bowel syndrome

PubMed Central

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

Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.

PubMed

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.

An Adaptive Critic Approach to Reference Model Adaptation

NASA Technical Reports Server (NTRS)

Krishnakumar, K.; Limes, G.; Gundy-Burlet, K.; Bryant, D.

2003-01-01

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

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

PubMed

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

2016-01-01

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

The Intelligent Control System and Experiments for an Unmanned Wave Glider

PubMed Central

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

2016-01-01

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

Intelligent Integrated System Health Management

NASA Technical Reports Server (NTRS)

Figueroa, Fernando

2012-01-01

Intelligent Integrated System Health Management (ISHM) is the management of data, information, and knowledge (DIaK) with the purposeful objective of determining the health of a system (Management: storage, distribution, sharing, maintenance, processing, reasoning, and presentation). Presentation discusses: (1) ISHM Capability Development. (1a) ISHM Knowledge Model. (1b) Standards for ISHM Implementation. (1c) ISHM Domain Models (ISHM-DM's). (1d) Intelligent Sensors and Components. (2) ISHM in Systems Design, Engineering, and Integration. (3) Intelligent Control for ISHM-Enabled Systems

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Novel associative-memory-based self-learning neurocontrol model

NASA Astrophysics Data System (ADS)

Chen, Ke

1992-09-01

Intelligent control is an important field of AI application, which is closely related to machine learning, and the neurocontrol is a kind of intelligent control that controls actions of a physical system or a plant. Linear associative memory model is a good analytic tool for artificial neural networks. In this paper, we present a novel self-learning neurocontrol on the basis of the linear associative memory model to support intelligent control. Using our self-learning neurocontrol model, the learning process is viewed as an extension of one of J. Piaget's developmental stages. After a particular linear associative model developed by us is presented, a brief introduction to J. Piaget's cognitive theory is described as the basis of our self-learning style control. It follows that the neurocontrol model is presented, which usually includes two learning stages, viz. primary learning and high-level learning. As a demonstration of our neurocontrol model, an example is also presented with simulation techniques, called that `bird' catches an aim. The tentative experimental results show that the learning and controlling performance of this approach is surprisingly good. In conclusion, future research is pointed out to improve our self-learning neurocontrol model and explore other areas of application.

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

The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

NASA Astrophysics Data System (ADS)

Makahinda, T.

2018-02-01

The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

The impact of emotional intelligent leadership on staff nurse empowerment: the moderating effect of span of control.

PubMed

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.

An Intelligent Control for the Distributed Flexible Network Photovoltaic System using Autonomous Control and Agent

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.

Intelligence and Academic Achievement With Asymptomatic Congenital Cytomegalovirus Infection.

PubMed

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.

Working Memory Capacity: Attention Control, Secondary Memory, or Both? A Direct Test of the Dual-Component Model

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…

Driving the brain towards creativity and intelligence: A network control theory analysis.

PubMed

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.

A survey of fuzzy logic monitoring and control utilisation in medicine.

PubMed

Mahfouf, M; Abbod, M F; Linkens, D A

2001-01-01

Intelligent systems have appeared in many technical areas, such as consumer electronics, robotics and industrial control systems. Many of these intelligent systems are based on fuzzy control strategies which describe complex systems mathematical models in terms of linguistic rules. Since the 1980s new techniques have appeared from which fuzzy logic has been applied extensively in medical systems. The justification for such intelligent systems driven solutions is that biological systems are so complex that the development of computerised systems within such environments is not always a straightforward exercise. In practice, a precise model may not exist for biological systems or it may be too difficult to model. In most cases fuzzy logic is considered to be an ideal tool as human minds work from approximate data, extract meaningful information and produce crisp solutions. This paper surveys the utilisation of fuzzy logic control and monitoring in medical sciences with an analysis of its possible future penetration.

Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

PubMed

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.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

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.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

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

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…

Model Selection for Solving Kinematic Problems

DTIC Science & Technology

1990-09-01

Bundy78] A. Bundy. Will it Reach the Top? Prediction in the Mechanics World. Aritificial Intelligence , 10:111-122, 1978. [Bundy,Luger,Mellish&Pamer78] A...ELEMENT. PfOJECT. TASK Artificial Intelligence Laboratory AREA 4 WORK UNIT NUMBERS 545 Technology Square Cambridge, MA 02139 It. CONTROLLiNG OFFICE...tificial Intelligence community, particularly in its application to diagnosis and trou- bleshooting. The core issue in this thesis, simply put, is, model

An intelligent active force control algorithm to control an upper extremity exoskeleton for motor recovery

NASA Astrophysics Data System (ADS)

Hasbullah Mohd Isa, Wan; Taha, Zahari; Mohd Khairuddin, Ismail; Majeed, Anwar P. P. Abdul; Fikri Muhammad, Khairul; Abdo Hashem, Mohammed; Mahmud, Jamaluddin; Mohamed, Zulkifli

2016-02-01

This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. The Newton-Euler formulation was used in deriving the dynamic modelling of both the anthropometry based human upper extremity as well as the exoskeleton that consists of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. The Mamdani Fuzzy based rule is employed to approximate the estimated inertial properties of the system to ensure the AFC loop responds efficiently. It is found that the IAFC-PD performed well against the disturbances introduced into the system as compared to the conventional PD control architecture in performing the desired trajectory tracking.

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.

Execution environment for intelligent real-time control systems

NASA Technical Reports Server (NTRS)

Sztipanovits, Janos

1987-01-01

Modern telerobot control technology requires the integration of symbolic and non-symbolic programming techniques, different models of parallel computations, and various programming paradigms. The Multigraph Architecture, which has been developed for the implementation of intelligent real-time control systems is described. The layered architecture includes specific computational models, integrated execution environment and various high-level tools. A special feature of the architecture is the tight coupling between the symbolic and non-symbolic computations. It supports not only a data interface, but also the integration of the control structures in a parallel computing environment.

OFMTutor: An operator function model intelligent tutoring system

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

1989-01-01

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described.

Intelligent fuzzy controller for event-driven real time systems

NASA Technical Reports Server (NTRS)

Grantner, Janos; Patyra, Marek; Stachowicz, Marian S.

1992-01-01

Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

Towards using musculoskeletal models for intelligent control of physically assistive robots.

PubMed

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.

A hierarchical distributed control model for coordinating intelligent systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1991-01-01

A hierarchical distributed control (HDC) model for coordinating cooperative problem-solving among intelligent systems is described. The model was implemented using SOCIAL, an innovative object-oriented tool for integrating heterogeneous, distributed software systems. SOCIAL embeds applications in 'wrapper' objects called Agents, which supply predefined capabilities for distributed communication, control, data specification, and translation. The HDC model is realized in SOCIAL as a 'Manager'Agent that coordinates interactions among application Agents. The HDC Manager: indexes the capabilities of application Agents; routes request messages to suitable server Agents; and stores results in a commonly accessible 'Bulletin-Board'. This centralized control model is illustrated in a fault diagnosis application for launch operations support of the Space Shuttle fleet at NASA, Kennedy Space Center.

Coordinating complex problem-solving among distributed intelligent agents

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1992-01-01

A process-oriented control model is described for distributed problem solving. The model coordinates the transfer and manipulation of information across independent networked applications, both intelligent and conventional. The model was implemented using SOCIAL, a set of object-oriented tools for distributing computing. Complex sequences of distributed tasks are specified in terms of high level scripts. Scripts are executed by SOCIAL objects called Manager Agents, which realize an intelligent coordination model that routes individual tasks to suitable server applications across the network. These tools are illustrated in a prototype distributed system for decision support of ground operations for NASA's Space Shuttle fleet.

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

NASA Astrophysics Data System (ADS)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

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.

A Feasibility Study of Life-Extending Controls for Aircraft Turbine Engines Using a Generic Air Force Model (Preprint)

DTIC Science & Technology

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.

Fuzzy control of burnout of multilayer ceramic actuators

NASA Astrophysics Data System (ADS)

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

1996-08-01

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

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.

Are executive functions related to emotional intelligence? A correlational study in schizophrenia and borderline personality disorder.

PubMed

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.

Intelligent control of a planning system for astronaut training.

PubMed

Ortiz, J; Chen, G

1999-07-01

This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

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.

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.

Online intelligent controllers for an enzyme recovery plant: design methodology and performance.

PubMed

Leite, M S; Fujiki, T L; Silva, F V; Fileti, A M F

2010-12-27

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity.

Online Intelligent Controllers for an Enzyme Recovery Plant: Design Methodology and Performance

PubMed Central

Leite, M. S.; Fujiki, T. L.; Silva, F. V.; Fileti, A. M. F.

2010-01-01

This paper focuses on the development of intelligent controllers for use in a process of enzyme recovery from pineapple rind. The proteolytic enzyme bromelain (EC 3.4.22.4) is precipitated with alcohol at low temperature in a fed-batch jacketed tank. Temperature control is crucial to avoid irreversible protein denaturation. Fuzzy or neural controllers offer a way of implementing solutions that cover dynamic and nonlinear processes. The design methodology and a comparative study on the performance of fuzzy-PI, neurofuzzy, and neural network intelligent controllers are presented. To tune the fuzzy PI Mamdani controller, various universes of discourse, rule bases, and membership function support sets were tested. A neurofuzzy inference system (ANFIS), based on Takagi-Sugeno rules, and a model predictive controller, based on neural modeling, were developed and tested as well. Using a Fieldbus network architecture, a coolant variable speed pump was driven by the controllers. The experimental results show the effectiveness of fuzzy controllers in comparison to the neural predictive control. The fuzzy PI controller exhibited a reduced error parameter (ITAE), lower power consumption, and better recovery of enzyme activity. PMID:21234106

Self-organizing control strategy for asteroid intelligent detection swarm based on attraction and repulsion

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.

BDM-KAT; Report of Research Results

DTIC Science & Technology

1990-03-31

relations, constraints TASK PRC>CESS MODEL TASK MICRO FOR SENSOR DATA Figure 4. Computer Network for the Intelligent Control of the HIP Process...prototyped and used in preliminary knowledge acquisition for an intelligent process controller for Hot Isostatic Pressing (HIP). Both the volume of...information collected and structured and Lhe value of that knowledge for the developing controller attest to the value of the concepts implemented in BDM

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

NASA Astrophysics Data System (ADS)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Resilient control of cyber-physical systems against intelligent attacker: a hierarchal stackelberg game approach

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Sun, Fuchun; Liu, Huaping

2016-07-01

This paper is concerned with the resilient control under denial-of-service attack launched by the intelligent attacker. The resilient control system is modelled as a multi-stage hierarchical game with a corresponding hierarchy of decisions made at cyber and physical layer, respectively. Specifically, the interaction in the cyber layer between different security agents is modelled as a static infinite Stackelberg game, while in the underlying physical layer the full-information H∞ minimax control with package drops is modelled as a different Stackelberg game. Both games are solved sequentially, which is consistent with the actual situations. Finally, the proposed method is applied to the load frequency control of the power system, which demonstrates its effectiveness.

Hybrid Modeling for Testing Intelligent Software for Lunar-Mars Closed Life Support

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Nicholson, Leonard S. (Technical Monitor)

1999-01-01

Intelligent software is being developed for closed life support systems with biological components, for human exploration of the Moon and Mars. The intelligent software functions include planning/scheduling, reactive discrete control and sequencing, management of continuous control, and fault detection, diagnosis, and management of failures and errors. Four types of modeling information have been essential to system modeling and simulation to develop and test the software and to provide operational model-based what-if analyses: discrete component operational and failure modes; continuous dynamic performance within component modes, modeled qualitatively or quantitatively; configuration of flows and power among components in the system; and operations activities and scenarios. CONFIG, a multi-purpose discrete event simulation tool that integrates all four types of models for use throughout the engineering and operations life cycle, has been used to model components and systems involved in the production and transfer of oxygen and carbon dioxide in a plant-growth chamber and between that chamber and a habitation chamber with physicochemical systems for gas processing.

Neurolinguistically constrained simulation of sentence comprehension: integrating artificial intelligence and brain theory

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

Gigley, H.M.

1982-01-01

An artificial intelligence approach to the simulation of neurolinguistically constrained processes in sentence comprehension is developed using control strategies for simulation of cooperative computation in associative networks. The desirability of this control strategy in contrast to ATN and production system strategies is explained. A first pass implementation of HOPE, an artificial intelligence simulation model of sentence comprehension, constrained by studies of aphasic performance, psycholinguistics, neurolinguistics, and linguistic theory is described. Claims that the model could serve as a basis for sentence production simulation and for a model of language acquisition as associative learning are discussed. HOPE is a model thatmore » performs in a normal state and includes a lesion simulation facility. HOPE is also a research tool. Its modifiability and use as a tool to investigate hypothesized causes of degradation in comprehension performance by aphasic patients are described. Issues of using behavioral constraints in modelling and obtaining appropriate data for simulated process modelling are discussed. Finally, problems of validation of the simulation results are raised; and issues of how to interpret clinical results to define the evolution of the model are discussed. Conclusions with respect to the feasibility of artificial intelligence simulation process modelling are discussed based on the current state of research.« less

A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence

PubMed Central

Spain, S L; Pedroso, I; Kadeva, N; Miller, M B; Iacono, W G; McGue, M; Stergiakouli, E; Smith, G D; Putallaz, M; Lubinski, D; Meaburn, E L; Plomin, R; Simpson, M A

2016-01-01

Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case–control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence. PMID:26239293

A genome-wide analysis of putative functional and exonic variation associated with extremely high intelligence.

PubMed

Spain, S L; Pedroso, I; Kadeva, N; Miller, M B; Iacono, W G; McGue, M; Stergiakouli, E; Davey Smith, G; Putallaz, M; Lubinski, D; Meaburn, E L; Plomin, R; Simpson, M A

2016-08-01

Although individual differences in intelligence (general cognitive ability) are highly heritable, molecular genetic analyses to date have had limited success in identifying specific loci responsible for its heritability. This study is the first to investigate exome variation in individuals of extremely high intelligence. Under the quantitative genetic model, sampling from the high extreme of the distribution should provide increased power to detect associations. We therefore performed a case-control association analysis with 1409 individuals drawn from the top 0.0003 (IQ >170) of the population distribution of intelligence and 3253 unselected population-based controls. Our analysis focused on putative functional exonic variants assayed on the Illumina HumanExome BeadChip. We did not observe any individual protein-altering variants that are reproducibly associated with extremely high intelligence and within the entire distribution of intelligence. Moreover, no significant associations were found for multiple rare alleles within individual genes. However, analyses using genome-wide similarity between unrelated individuals (genome-wide complex trait analysis) indicate that the genotyped functional protein-altering variation yields a heritability estimate of 17.4% (s.e. 1.7%) based on a liability model. In addition, investigation of nominally significant associations revealed fewer rare alleles associated with extremely high intelligence than would be expected under the null hypothesis. This observation is consistent with the hypothesis that rare functional alleles are more frequently detrimental than beneficial to intelligence.

Use of artificial intelligence in supervisory control

NASA Technical Reports Server (NTRS)

Cohen, Aaron; Erickson, Jon D.

1989-01-01

Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

Outline for a theory of intelligence

NASA Technical Reports Server (NTRS)

Albus, James S.

1991-01-01

Intelligence is defined as that which produces successful behavior. Intelligence is assumed to result from natural selection. A model is proposed that integrates knowledge from research in both natural and artificial systems. The model consists of a hierarchical system architecture wherein: (1) control bandwidth decreases about an order of magnitude at each higher level, (2) perceptual resolution of spatial and temporal patterns contracts about an order-of-magnitude at each higher level, (3) goals expand in scope and planning horizons expand in space and time about an order-of-magnitude at each higher level, and (4) models of the world and memories of events expand their range in space and time by about an order-of-magnitude at each higher level. At each level, functional modules perform behavior generation (task decomposition planning and execution), world modeling, sensory processing, and value judgment. Sensory feedback control loops are closed at every level.

Theoretical Foundations of Software Technology.

DTIC Science & Technology

1983-02-14

major research interests are software testing, aritificial intelligence , pattern recogu- tion, and computer graphics. Dr. Chandranekaran is currently...produce PASCAL language code for the problems. Because of its relationship to many issues in Artificial Intelligence , we also investigated problems of...analysis to concurmt-prmcess software re- are not " intelligent " enough to discover these by themselves, ouirl more complex control flow models. The PAF

Programming model for distributed intelligent systems

NASA Technical Reports Server (NTRS)

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

1988-01-01

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

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.

A development framework for distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

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 Launch and Range Operations Virtual Test Bed (ILRO-VTB)

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Rajkumar, T.

2003-01-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

Intelligent launch and range operations virtual testbed (ILRO-VTB)

NASA Astrophysics Data System (ADS)

Bardina, Jorge; Rajkumar, Thirumalainambi

2003-09-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

A Methodolgy, Based on Analytical Modeling, for the Design of Parallel and Distributed Architectures for Relational Database Query Processors.

DTIC Science & Technology

1987-12-01

Application Programs Intelligent Disk Database Controller Manangement System Operating System Host .1’ I% Figure 2. Intelligent Disk Controller Application...8217. /- - • Database Control -% Manangement System Disk Data Controller Application Programs Operating Host I"" Figure 5. Processor-Per- Head data. Therefore, the...However. these ad- ditional properties have been proven in classical set and relation theory [75]. These additional properties are described here

Cognitive predictors of a common multitasking ability: Contributions from working memory, attention control, and fluid intelligence.

PubMed

Redick, Thomas S; Shipstead, Zach; Meier, Matthew E; Montroy, Janelle J; Hicks, Kenny L; Unsworth, Nash; Kane, Michael J; Hambrick, D Zachary; Engle, Randall W

2016-11-01

Previous research has identified several cognitive abilities that are important for multitasking, but few studies have attempted to measure a general multitasking ability using a diverse set of multitasks. In the final dataset, 534 young adult subjects completed measures of working memory (WM), attention control, fluid intelligence, and multitasking. Correlations, hierarchical regression analyses, confirmatory factor analyses, structural equation models, and relative weight analyses revealed several key findings. First, although the complex tasks used to assess multitasking differed greatly in their task characteristics and demands, a coherent construct specific to multitasking ability was identified. Second, the cognitive ability predictors accounted for substantial variance in the general multitasking construct, with WM and fluid intelligence accounting for the most multitasking variance compared to attention control. Third, the magnitude of the relationships among the cognitive abilities and multitasking varied as a function of the complexity and structure of the various multitasks assessed. Finally, structural equation models based on a multifaceted model of WM indicated that attention control and capacity fully mediated the WM and multitasking relationship. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A development framework for artificial intelligence based distributed operations support systems

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1990-01-01

Advanced automation is required to reduce costly human operations support requirements for complex space-based and ground control systems. Existing knowledge based technologies have been used successfully to automate individual operations tasks. Considerably less progress has been made in integrating and coordinating multiple operations applications for unified intelligent support systems. To fill this gap, SOCIAL, a tool set for developing Distributed Artificial Intelligence (DAI) systems is being constructed. SOCIAL consists of three primary language based components defining: models of interprocess communication across heterogeneous platforms; models for interprocess coordination, concurrency control, and fault management; and for accessing heterogeneous information resources. DAI applications subsystems, either new or existing, will access these distributed services non-intrusively, via high-level message-based protocols. SOCIAL will reduce the complexity of distributed communications, control, and integration, enabling developers to concentrate on the design and functionality of the target DAI system itself.

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

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

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

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

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.

PubMed

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.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

NASA Astrophysics Data System (ADS)

Wilson, Eric Lee

Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

High-autonomy control of space resource processing plants

NASA Technical Reports Server (NTRS)

Schooley, Larry C.; Zeigler, Bernard P.; Cellier, Francois E.; Wang, Fei-Yue

1993-01-01

A highly autonomous intelligent command/control architecture has been developed for planetary surface base industrial process plants and Space Station Freedom experimental facilities. The architecture makes use of a high-level task-oriented mode with supervisory control from one or several remote sites, and integrates advanced network communications concepts and state-of-the-art man/machine interfaces with the most advanced autonomous intelligent control. Attention is given to the full-dynamics model of a Martian oxygen-production plant, event-based/fuzzy-logic process control, and fault management practices.

Model-Unified Planning and Execution for Distributed Autonomous System Control

NASA Technical Reports Server (NTRS)

Aschwanden, Pascal; Baskaran, Vijay; Bernardini, Sara; Fry, Chuck; Moreno, Maria; Muscettola, Nicola; Plaunt, Chris; Rijsman, David; Tompkins, Paul

2006-01-01

The Intelligent Distributed Execution Architecture (IDEA) is a real-time architecture that exploits artificial intelligence planning as the core reasoning engine for interacting autonomous agents. Rather than enforcing separate deliberation and execution layers, IDEA unifies them under a single planning technology. Deliberative and reactive planners reason about and act according to a single representation of the past, present and future domain state. The domain state behaves the rules dictated by a declarative model of the subsystem to be controlled, internal processes of the IDEA controller, and interactions with other agents. We present IDEA concepts - modeling, the IDEA core architecture, the unification of deliberation and reaction under planning - and illustrate its use in a simple example. Finally, we present several real-world applications of IDEA, and compare IDEA to other high-level control approaches.

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.

Predictive Eco-Cruise Control (ECC) system : model development, modeling and potential benefits.

DOT National Transportation Integrated Search

2013-02-01

The research develops a reference model of a predictive eco-cruise control (ECC) system that intelligently modulates vehicle speed within a pre-set speed range to minimize vehicle fuel consumption levels using roadway topographic information. The stu...

Research and development of service robot platform based on artificial psychology

NASA Astrophysics Data System (ADS)

Zhang, Xueyuan; Wang, Zhiliang; Wang, Fenhua; Nagai, Masatake

2007-12-01

Some related works about the control architecture of robot system are briefly summarized. According to the discussions above, this paper proposes control architecture of service robot based on artificial psychology. In this control architecture, the robot can obtain the cognition of environment through sensors, and then be handled with intelligent model, affective model and learning model, and finally express the reaction to the outside stimulation through its behavior. For better understanding the architecture, hierarchical structure is also discussed. The control system of robot can be divided into five layers, namely physical layer, drives layer, information-processing and behavior-programming layer, application layer and system inspection and control layer. This paper shows how to achieve system integration from hardware modules, software interface and fault diagnosis. Embedded system GENE-8310 is selected as the PC platform of robot APROS-I, and its primary memory media is CF card. The arms and body of the robot are constituted by 13 motors and some connecting fittings. Besides, the robot has a robot head with emotional facial expression, and the head has 13 DOFs. The emotional and intelligent model is one of the most important parts in human-machine interaction. In order to better simulate human emotion, an emotional interaction model for robot is proposed according to the theory of need levels of Maslom and mood information of Siminov. This architecture has already been used in our intelligent service robot.

When intelligence is in control

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

Bellman, K.L.

Each time a discipline redefines itself, I look at it as a sign of growth, because often such redefinition means that there is new theory, new methods, or new {open_quotes}disciples{close_quote} from other disciplines who are stretching, enlarging, and deepening the field. Such is the case with semiotics. Deeply entwined with the concepts of {open_quotes}intelligent systems{close_quotes}, {open_quotes}intelligent control{close_quotes}, and complex systems theory, semiotics struggles to develop representations, notations (systems of representations), and models (functionally-oriented sets of related representations) to study systems that may or may not be usefully described as employing representations, notations, and models themselves. That last, of course, ismore » the main problem that semiotics faces. Semiotics, like psychology, philosophy, or any other self-referential discipline, is burdened by the eye attempting to study the eye or the mind studying the mind, or more to the point here, the modeler studying the modeling acts of others.« less

Hybrid neuro-heuristic methodology for simulation and control of dynamic systems over time interval.

PubMed

Woźniak, Marcin; Połap, Dawid

2017-09-01

Simulation and positioning are very important aspects of computer aided engineering. To process these two, we can apply traditional methods or intelligent techniques. The difference between them is in the way they process information. In the first case, to simulate an object in a particular state of action, we need to perform an entire process to read values of parameters. It is not very convenient for objects for which simulation takes a long time, i.e. when mathematical calculations are complicated. In the second case, an intelligent solution can efficiently help on devoted way of simulation, which enables us to simulate the object only in a situation that is necessary for a development process. We would like to present research results on developed intelligent simulation and control model of electric drive engine vehicle. For a dedicated simulation method based on intelligent computation, where evolutionary strategy is simulating the states of the dynamic model, an intelligent system based on devoted neural network is introduced to control co-working modules while motion is in time interval. Presented experimental results show implemented solution in situation when a vehicle transports things over area with many obstacles, what provokes sudden changes in stability that may lead to destruction of load. Therefore, applied neural network controller prevents the load from destruction by positioning characteristics like pressure, acceleration, and stiffness voltage to absorb the adverse changes of the ground. Copyright © 2017 Elsevier Ltd. All rights reserved.

Intelligent control system for continuous technological process of alkylation

NASA Astrophysics Data System (ADS)

Gebel, E. S.; Hakimov, R. A.

2018-01-01

Relevance of intelligent control for complex dynamic objects and processes are shown in this paper. The model of a virtual analyzer based on a neural network is proposed. Comparative analysis of mathematical models implemented in MathLab software showed that the most effective from the point of view of the reproducibility of the result is the model with seven neurons in the hidden layer, the training of which was performed using the method of scaled coupled gradients. Comparison of the data from the laboratory analysis and the theoretical model are showed that the root-mean-square error does not exceed 3.5, and the calculated value of the correlation coefficient corresponds to a "strong" connection between the values.

Autism-specific covariation in perceptual performances: "g" or "p" factor?

PubMed

Meilleur, Andrée-Anne S; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent

2014-01-01

Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or "g" factor). Instead, this residual covariation is accounted for by a common perceptual process (or "p" factor), which may drive perceptual abilities differently in autistic and non-autistic individuals.

Autism-Specific Covariation in Perceptual Performances: “g” or “p” Factor?

PubMed Central

Meilleur, Andrée-Anne S.; Berthiaume, Claude; Bertone, Armando; Mottron, Laurent

2014-01-01

Background Autistic perception is characterized by atypical and sometimes exceptional performance in several low- (e.g., discrimination) and mid-level (e.g., pattern matching) tasks in both visual and auditory domains. A factor that specifically affects perceptive abilities in autistic individuals should manifest as an autism-specific association between perceptual tasks. The first purpose of this study was to explore how perceptual performances are associated within or across processing levels and/or modalities. The second purpose was to determine if general intelligence, the major factor that accounts for covariation in task performances in non-autistic individuals, equally controls perceptual abilities in autistic individuals. Methods We asked 46 autistic individuals and 46 typically developing controls to perform four tasks measuring low- or mid-level visual or auditory processing. Intelligence was measured with the Wechsler's Intelligence Scale (FSIQ) and Raven Progressive Matrices (RPM). We conducted linear regression models to compare task performances between groups and patterns of covariation between tasks. The addition of either Wechsler's FSIQ or RPM in the regression models controlled for the effects of intelligence. Results In typically developing individuals, most perceptual tasks were associated with intelligence measured either by RPM or Wechsler FSIQ. The residual covariation between unimodal tasks, i.e. covariation not explained by intelligence, could be explained by a modality-specific factor. In the autistic group, residual covariation revealed the presence of a plurimodal factor specific to autism. Conclusions Autistic individuals show exceptional performance in some perceptual tasks. Here, we demonstrate the existence of specific, plurimodal covariation that does not dependent on general intelligence (or “g” factor). Instead, this residual covariation is accounted for by a common perceptual process (or “p” factor), which may drive perceptual abilities differently in autistic and non-autistic individuals. PMID:25117450

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.

Robust algebraic image enhancement for intelligent control systems

NASA Technical Reports Server (NTRS)

Lerner, Bao-Ting; Morrelli, Michael

1993-01-01

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

DFB laser array driver circuit controlled by adjustable signal

NASA Astrophysics Data System (ADS)

Du, Weikang; Du, Yinchao; Guo, Yu; Li, Wei; Wang, Hao

2018-01-01

In order to achieve the intelligent controlling of DFB laser array, this paper presents the design of an intelligence and high precision numerical controlling electric circuit. The system takes MCU and FPGA as the main control chip, with compact, high-efficiency, no impact, switching protection characteristics. The output of the DFB laser array can be determined by an external adjustable signal. The system transforms the analog control model into a digital control model, which improves the performance of the driver. The system can monitor the temperature and current of DFB laser array in real time. The output precision of the current can reach ± 0.1mA, which ensures the stable and reliable operation of the DFB laser array. Such a driver can benefit the flexible usage of the DFB laser array.

Refined carbohydrate intake in relation to non-verbal intelligence among Tehrani schoolchildren.

PubMed

Abargouei, Amin Salehi; Kalantari, Naser; Omidvar, Nasrin; Rashidkhani, Bahram; Rad, Anahita Houshiar; Ebrahimi, Azizeh Afkham; Khosravi-Boroujeni, Hossein; Esmaillzadeh, Ahmad

2012-10-01

Nutrition has long been considered one of the most important environmental factors affecting human intelligence. Although carbohydrates are the most widely studied nutrient for their possible effects on cognition, limited data are available linking usual refined carbohydrate intake and intelligence. The present study was conducted to examine the relationship between long-term refined carbohydrate intake and non-verbal intelligence among schoolchildren. Cross-sectional study. Tehran, Iran. In this cross-sectional study, 245 students aged 6-7 years were selected from 129 elementary schools in two western regions of Tehran. Anthropometric measurements were carried out. Non-verbal intelligence and refined carbohydrate consumption were determined using Raven's Standard Progressive Matrices test and a modified sixty-seven-item FFQ, respectively. Data about potential confounding variables were collected. Linear regression analysis was applied to examine the relationship between non-verbal intelligence scores and refined carbohydrate consumption. Individuals in top tertile of refined carbohydrate intake had lower mean non-verbal intelligence scores in the crude model (P < 0.038). This association remained significant after controlling for age, gender, birth date, birth order and breast-feeding pattern (P = 0.045). However, further adjustments for mother's age, mother's education, father's education, parental occupation and BMI made the association statistically non-significant. We found a significant inverse association between refined carbohydrate consumption and non-verbal intelligence scores in regression models (β = -11.359, P < 0.001). This relationship remained significant in multivariate analysis after controlling for potential confounders (β = -8.495, P = 0.038). The study provides evidence indicating an inverse relationship between refined carbohydrate consumption and non-verbal intelligence among Tehrani children aged 6-7 years. Prospective studies are needed to confirm our findings.

What No Child Left Behind Leaves Behind: The Roles of IQ and Self-Control in Predicting Standardized Achievement Test Scores and Report Card Grades

PubMed Central

Duckworth, Angela L.; Quinn, Patrick D.; Tsukayama, Eli

2013-01-01

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 particular, we suggest that intelligence helps students learn and solve problems independent of formal instruction, whereas self-control helps students study, complete homework, and behave positively in the classroom. Two longitudinal, prospective studies of middle school students support predictions from this model. In both samples, IQ predicted changes in standardized achievement test scores over time better than did self-control, whereas self-control predicted changes in report card grades over time better than did IQ. As expected, the effect of self-control on changes in report card grades was mediated in Study 2 by teacher ratings of homework completion and classroom conduct. In a third study, ratings of middle school teachers about the content and purpose of standardized achievement tests and report card grades were consistent with the proposed model. Implications for pedagogy and public policy are discussed. PMID:24072936

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

NASA Technical Reports Server (NTRS)

Mclauchlan, Robert A.

1989-01-01

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

Smart teens don't have sex (or kiss much either).

PubMed

Halpern, C T; Joyner, K; Udry, J R; Suchindran, C

2000-03-01

To examine the relationship between an intelligence measure and a wide spectrum of partnered sexual activity ranging from holding hands to sexual intercourse among adolescents. Analyses are based on two separate samples of adolescents. The core sample of the National Longitudinal Study of Adolescent Health (Add Health) includes approximately 12,000 adolescents enrolled in the 7th to 12th grades. The Biosocial Factors in Adolescent Development projects followed approximately 100 white males and 200 black and white females over 3- and 2-year periods, respectively. Both studies used the Peabody Picture Vocabulary Test (PPVT) as an intelligence measure, and confidential self-reports of sexual activity. Logistic regression models were used to examine the relationship between PPVT scores and coital status in Add Health data; proportional hazard models were used to examine the timing of initiation of noncoital and coital activities as a function of PPVT scores in the Biosocial Factors sample. Controlling for age, physical maturity, and mother's education, a significant curvilinear relationship between intelligence and coital status was demonstrated; adolescents at the upper and lower ends of the intelligence distribution were less likely to have sex. Higher intelligence was also associated with postponement of the initiation of the full range of partnered sexual activities. An expanded model incorporating a variety of control and mediator variables was tested to identify mechanisms by which the relationship operates. Higher intelligence operates as a protective factor against early sexual activity during adolescence, and lower intelligence, to a point, is a risk factor. More systematic investigation of the implications of individual differences in cognitive abilities for sexual activities and of the processes that underlie those activities is warranted.

DSB Task Force on Cyber Supply Chain

DTIC Science & Technology

2017-02-06

27 3.4 Cybersecurity for Commercial and Open Source Components...Communications and Intelligence ASD(L&MR): Assistant Secretary of Defense for Logistics and Materiel Readiness ASD(R&E): Assistant Secretary of Defense...system BSIMM: Building Security in Maturity Model C4ISR: command, control, communications, computers, intelligence , surveillance and

Intelligent robot trends and predictions for the .net future

NASA Astrophysics Data System (ADS)

Hall, Ernest L.

2001-10-01

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

Intelligence, creativity, and cognitive control: The common and differential involvement of executive functions in intelligence and creativity

PubMed Central

Benedek, Mathias; Jauk, Emanuel; Sommer, Markus; Arendasy, Martin; Neubauer, Aljoscha C.

2014-01-01

Intelligence and creativity are known to be correlated constructs suggesting that they share a common cognitive basis. The present study assessed three specific executive abilities – updating, shifting, and inhibition – and examined their common and differential relations to fluid intelligence and creativity (i.e., divergent thinking ability) within a latent variable model approach. Additionally, it was tested whether the correlation of fluid intelligence and creativity can be explained by a common executive involvement. As expected, fluid intelligence was strongly predicted by updating, but not by shifting or inhibition. Creativity was predicted by updating and inhibition, but not by shifting. Moreover, updating (and the personality factor openness) was found to explain a relevant part of the shared variance between intelligence and creativity. The findings provide direct support for the executive involvement in creative thought and shed further light on the functional relationship between intelligence and creativity. PMID:25278640

Strong Genetic Overlap Between Executive Functions and Intelligence

PubMed Central

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

Virtual personal assistance

NASA Astrophysics Data System (ADS)

Aditya, K.; Biswadeep, G.; Kedar, S.; Sundar, S.

2017-11-01

Human computer communication has growing demand recent days. The new generation of autonomous technology aspires to give computer interfaces emotional states that relate and consider user as well as system environment considerations. In the existing computational model is based an artificial intelligent and externally by multi-modal expression augmented with semi human characteristics. But the main problem with is multi-model expression is that the hardware control given to the Artificial Intelligence (AI) is very limited. So, in our project we are trying to give the Artificial Intelligence (AI) more control on the hardware. There are two main parts such as Speech to Text (STT) and Text to Speech (TTS) engines are used accomplish the requirement. In this work, we are using a raspberry pi 3, a speaker and a mic as hardware and for the programing part, we are using python scripting.

INDIRECT INTELLIGENT SLIDING MODE CONTROL OF A SHAPE MEMORY ALLOY ACTUATED FLEXIBLE BEAM USING HYSTERETIC RECURRENT NEURAL NETWORKS.

PubMed

Hannen, Jennifer C; Crews, John H; Buckner, Gregory D

2012-08-01

This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller.

Design Of An Intelligent Robotic System Organizer Via Expert System Tecniques

NASA Astrophysics Data System (ADS)

Yuan, Peter H.; Valavanis, Kimon P.

1989-02-01

Intelligent Robotic Systems are a special type of Intelligent Machines. When modeled based on Vle theory of Intelligent Controls, they are composed of three interactive levels, namely: organization, coordination, and execution, ordered according, to the ,Principle of Increasing, Intelligence with Decreasing Precl.sion. Expert System techniques, are used to design an Intelligent Robotic System Organizer with a dynamic Knowledge Base and an interactive Inference Engine. Task plans are formulated using, either or both of a Probabilistic Approach and Forward Chapling Methodology, depending on pertinent information associated with a spec;fic requested job. The Intelligent Robotic System, Organizer is implemented and tested on a prototype system operating in an uncertain environment. An evaluation of-the performance, of the prototype system is conducted based upon the probability of generating a successful task sequence versus the number of trials taken by the organizer.

Information and redundancy: key concepts in understanding the genetic control of health and intelligence.

PubMed

Morris, J A

1999-08-01

A model is proposed in which information from the environment is analysed by complex biological decision-making systems which are highly redundant. A correct response is intelligent behaviour which preserves health; incorrect responses lead to disease. Mutations in genes which code for the redundant systems will accumulate in the genome and impair decision-making. The number of mutant genes will depend upon a balance between the new mutation rate per generation and systems of elimination based on synergistic interaction in redundant systems. This leads to a polygenic pattern of inheritance for intelligence and the common diseases. The model also gives a simple explanation for some of the hitherto puzzling aspects of work on the genetic basis of intelligence including the recorded rise in IQ this century. There is a prediction that health, intelligence and socio-economic position will be correlated generating a health differential in the social hierarchy. Furthermore, highly competitive societies will place those least able to cope in the harshest environment and this will impair health overall. The model points to a need for population monitoring of somatic mutation in order to preserve the health and intelligence of future generations.

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.

Intelligence, birth order, and family size.

PubMed

Kanazawa, Satoshi

2012-09-01

The analysis of the National Child Development Study in the United Kingdom (n = 17,419) replicates some earlier findings and shows that genuine within-family data are not necessary to make the apparent birth-order effect on intelligence disappear. Birth order is not associated with intelligence in between-family data once the number of siblings is statistically controlled. The analyses support the admixture hypothesis, which avers that the apparent birth-order effect on intelligence is an artifact of family size, and cast doubt on the confluence and resource dilution models, both of which claim that birth order has a causal influence on children's cognitive development. The analyses suggest that birth order has no genuine causal effect on general intelligence.

An intelligent CNC machine control system architecture

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

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

1996-10-01

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

Intelligent Life-Extending Controls for Aircraft Engines

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei; Chen, Philip; Jaw, Link

2005-01-01

Aircraft engine controllers are designed and operated to provide desired performance and stability margins. The purpose of life-extending-control (LEC) is to study the relationship between control action and engine component life usage, and to design an intelligent control algorithm to provide proper trade-offs between performance and engine life usage. The benefit of this approach is that it is expected to maintain safety while minimizing the overall operating costs. With the advances of computer technology, engine operation models, and damage physics, it is necessary to reevaluate the control strategy fro overall operating cost consideration. This paper uses the thermo-mechanical fatigue (TMF) of a critical component to demonstrate how an intelligent engine control algorithm can drastically reduce the engine life usage with minimum sacrifice in performance. A Monte Carlo simulation is also performed to evaluate the likely engine damage accumulation under various operating conditions. The simulation results show that an optimized acceleration schedule can provide a significant life saving in selected engine components.

Fifth Conference on Artificial Intelligence for Space Applications

NASA Technical Reports Server (NTRS)

Odell, Steve L. (Compiler)

1990-01-01

The Fifth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: automation for Space Station; intelligent control, testing, and fault diagnosis; robotics and vision; planning and scheduling; simulation, modeling, and tutoring; development tools and automatic programming; knowledge representation and acquisition; and knowledge base/data base integration.

Strong genetic overlap between executive functions and intelligence.

PubMed

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 autonomous satellite architecture integrating deliberative reasoning and behavioural intelligence

NASA Technical Reports Server (NTRS)

Lindley, Craig A.

1993-01-01

This paper describes a method for the design of autonomous spacecraft, based upon behavioral approaches to intelligent robotics. First, a number of previous spacecraft automation projects are reviewed. A methodology for the design of autonomous spacecraft is then presented, drawing upon both the European Space Agency technological center (ESTEC) automation and robotics methodology and the subsumption architecture for autonomous robots. A layered competency model for autonomous orbital spacecraft is proposed. A simple example of low level competencies and their interaction is presented in order to illustrate the methodology. Finally, the general principles adopted for the control hardware design of the AUSTRALIS-1 spacecraft are described. This system will provide an orbital experimental platform for spacecraft autonomy studies, supporting the exploration of different logical control models, different computational metaphors within the behavioral control framework, and different mappings from the logical control model to its physical implementation.

A prototype knowledge-based simulation support system

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

Hill, T.R.; Roberts, S.D.

1987-04-01

As a preliminary step toward the goal of an intelligent automated system for simulation modeling support, we explore the feasibility of the overall concept by generating and testing a prototypical framework. A prototype knowledge-based computer system was developed to support a senior level course in industrial engineering so that the overall feasibility of an expert simulation support system could be studied in a controlled and observable setting. The system behavior mimics the diagnostic (intelligent) process performed by the course instructor and teaching assistants, finding logical errors in INSIGHT simulation models and recommending appropriate corrective measures. The system was programmed inmore » a non-procedural language (PROLOG) and designed to run interactively with students working on course homework and projects. The knowledge-based structure supports intelligent behavior, providing its users with access to an evolving accumulation of expert diagnostic knowledge. The non-procedural approach facilitates the maintenance of the system and helps merge the roles of expert and knowledge engineer by allowing new knowledge to be easily incorporated without regard to the existing flow of control. The background, features and design of the system are describe and preliminary results are reported. Initial success is judged to demonstrate the utility of the reported approach and support the ultimate goal of an intelligent modeling system which can support simulation modelers outside the classroom environment. Finally, future extensions are suggested.« less

A knowledge-based system for controlling automobile traffic

NASA Technical Reports Server (NTRS)

Maravas, Alexander; Stengel, Robert F.

1994-01-01

Transportation network capacity variations arising from accidents, roadway maintenance activity, and special events as well as fluctuations in commuters' travel demands complicate traffic management. Artificial intelligence concepts and expert systems can be useful in framing policies for incident detection, congestion anticipation, and optimal traffic management. This paper examines the applicability of intelligent route guidance and control as decision aids for traffic management. Basic requirements for managing traffic are reviewed, concepts for studying traffic flow are introduced, and mathematical models for modeling traffic flow are examined. Measures for quantifying transportation network performance levels are chosen, and surveillance and control strategies are evaluated. It can be concluded that automated decision support holds great promise for aiding the efficient flow of automobile traffic over limited-access roadways, bridges, and tunnels.

Working Memory and Intelligence Are Highly Related Constructs, but Why?

ERIC Educational Resources Information Center

Colom, Roberto; Abad, Francisco J.; Quiroga, M. Angeles; Shih, Pei Chun; Flores-Mendoza, Carmen

2008-01-01

Working memory and the general factor of intelligence (g) are highly related constructs. However, we still don't know why. Some models support the central role of simple short-term storage, whereas others appeal to executive functions like the control of attention. Nevertheless, the available empirical evidence does not suffice to get an answer,…

Examining the Effects of Jyoti Meditation on Stress and the Moderating Role of Emotional Intelligence

ERIC Educational Resources Information Center

Gutierrez, Daniel; Conley, Abigail H.; Young, Mark

2016-01-01

The authors examined whether Jyoti meditation (JM), a spiritually based meditation (Singh, 2012), influenced student counselors' (N = 60) level of stress and emotional intelligence (EI). Results from a randomized controlled trial and growth curve analysis provided a multilevel model in which JM reduced stress and EI moderated the effect.

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

NASA Technical Reports Server (NTRS)

Wada, Ben K. (Editor); Fanson, James L. (Editor); Miura, Koryo (Editor)

1991-01-01

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

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

NASA Astrophysics Data System (ADS)

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

1991-11-01

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

Intelligence and Disability Pension in Swedish Men and Women Followed from Childhood to Late Middle Age

PubMed Central

Lundin, Andreas; Sörberg Wallin, Alma; Falkstedt, Daniel; Allebeck, Peter; Hemmingsson, Tomas

2015-01-01

Objective To investigate the association between intelligence and disability pension due to mental, musculoskeletal, cardiovascular, and substance-use disorders among men and women, and to assess the role of childhood social factors and adulthood work characteristics. Methods Two random samples of men and women born 1948 and 1953 (n = 10 563 and 9 434), and tested for general intelligence at age 13, were followed in registers for disability pension until 2009. Physical and psychological strains in adulthood were assessed using job exposure matrices. Associations were examined using Cox proportional hazard regression models, with increases in rates reported as hazard ratios (HRs) with 95% confidence intervals (95%CI) per decrease in stanine intelligence. Results In both men and women increased risks were found for disability pension due to all causes, musculoskeletal disorder, mental disorder other than substance use, and cardiovascular disease as intelligence decreased. Increased risk was also found for substance use disorder in men. In multivariate models, HRs were attenuated after controlling for pre-school plans in adolescence, and low job control and high physical strain in adulthood. In the fully adjusted model, increased HRs remained for all causes (male HR 1.11, 95%CI 1.07–1.15, female HR 1.06, 95%CI 1.02–1.09) and musculoskeletal disorder (male HR 1.16, 95%CI 1.09–1.24, female HR 1.08, 95%CI 1.03–1.14) during 1986 to 2009. Conclusion Relatively low childhood intelligence is associated with increased risk of disability pension due to musculoskeletal disorder in both men and women, even after adjustment for risk factors for disability pension measured over the life course. PMID:26062026

Intelligence and Disability Pension in Swedish Men and Women Followed from Childhood to Late Middle Age.

PubMed

Lundin, Andreas; Sörberg Wallin, Alma; Falkstedt, Daniel; Allebeck, Peter; Hemmingsson, Tomas

2015-01-01

To investigate the association between intelligence and disability pension due to mental, musculoskeletal, cardiovascular, and substance-use disorders among men and women, and to assess the role of childhood social factors and adulthood work characteristics. Two random samples of men and women born 1948 and 1953 (n = 10 563 and 9 434), and tested for general intelligence at age 13, were followed in registers for disability pension until 2009. Physical and psychological strains in adulthood were assessed using job exposure matrices. Associations were examined using Cox proportional hazard regression models, with increases in rates reported as hazard ratios (HRs) with 95% confidence intervals (95%CI) per decrease in stanine intelligence. In both men and women increased risks were found for disability pension due to all causes, musculoskeletal disorder, mental disorder other than substance use, and cardiovascular disease as intelligence decreased. Increased risk was also found for substance use disorder in men. In multivariate models, HRs were attenuated after controlling for pre-school plans in adolescence, and low job control and high physical strain in adulthood. In the fully adjusted model, increased HRs remained for all causes (male HR 1.11, 95%CI 1.07-1.15, female HR 1.06, 95%CI 1.02-1.09) and musculoskeletal disorder (male HR 1.16, 95%CI 1.09-1.24, female HR 1.08, 95%CI 1.03-1.14) during 1986 to 2009. Relatively low childhood intelligence is associated with increased risk of disability pension due to musculoskeletal disorder in both men and women, even after adjustment for risk factors for disability pension measured over the life course.

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2016-04-13

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

A measurement model of multiple intelligence profiles of management graduates

NASA Astrophysics Data System (ADS)

Krishnan, Heamalatha; Awang, Siti Rahmah

2017-05-01

In this study, developing a fit measurement model and identifying the best fitting items to represent Howard Gardner's nine intelligences namely, musical intelligence, bodily-kinaesthetic intelligence, mathematical/logical intelligence, visual/spatial intelligence, verbal/linguistic intelligence, interpersonal intelligence, intrapersonal intelligence, naturalist intelligence and spiritual intelligence are the main interest in order to enhance the opportunities of the management graduates for employability. In order to develop a fit measurement model, Structural Equation Modeling (SEM) was applied. A psychometric test which is the Ability Test in Employment (ATIEm) was used as the instrument to measure the existence of nine types of intelligence of 137 University Teknikal Malaysia Melaka (UTeM) management graduates for job placement purposes. The initial measurement model contains nine unobserved variables and each unobserved variable is measured by ten observed variables. Finally, the modified measurement model deemed to improve the Normed chi-square (NC) = 1.331; Incremental Fit Index (IFI) = 0.940 and Root Mean Square of Approximation (RMSEA) = 0.049 was developed. The findings showed that the UTeM management graduates possessed all nine intelligences either high or low. Musical intelligence, mathematical/logical intelligence, naturalist intelligence and spiritual intelligence contributed highest loadings on certain items. However, most of the intelligences such as bodily kinaesthetic intelligence, visual/spatial intelligence, verbal/linguistic intelligence interpersonal intelligence and intrapersonal intelligence possessed by UTeM management graduates are just at the borderline.

Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals.

PubMed

Coleman, Jonathan R I; Bryois, Julien; Gaspar, Héléna A; Jansen, Philip R; Savage, Jeanne E; Skene, Nathan; Plomin, Robert; Muñoz-Manchado, Ana B; Linnarsson, Sten; Crawford, Greg; Hjerling-Leffler, Jens; Sullivan, Patrick F; Posthuma, Danielle; Breen, Gerome

2018-03-08

Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comparing 1247 individuals with mean IQ ~170 to 8185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.

Design details of Intelligent Instruments for PLC-free Cryogenic measurements, control and data acquisition

NASA Astrophysics Data System (ADS)

Antony, Joby; Mathuria, D. S.; Chaudhary, Anup; Datta, T. S.; Maity, T.

2017-02-01

Cryogenic network for linear accelerator operations demand a large number of Cryogenic sensors, associated instruments and other control-instrumentation to measure, monitor and control different cryogenic parameters remotely. Here we describe an alternate approach of six types of newly designed integrated intelligent cryogenic instruments called device-servers which has the complete circuitry for various sensor-front-end analog instrumentation and the common digital back-end http-server built together, to make crateless PLC-free model of controls and data acquisition. These identified instruments each sensor-specific viz. LHe server, LN2 Server, Control output server, Pressure server, Vacuum server and Temperature server are completely deployed over LAN for the cryogenic operations of IUAC linac (Inter University Accelerator Centre linear Accelerator), New Delhi. This indigenous design gives certain salient features like global connectivity, low cost due to crateless model, easy signal processing due to integrated design, less cabling and device-interconnectivity etc.

The NIST Real-Time Control System (RCS): A Reference Model Architecture for Computational Intelligence

NASA Technical Reports Server (NTRS)

Albus, James S.

1996-01-01

The Real-time Control System (RCS) developed at NIST and elsewhere over the past two decades defines a reference model architecture for design and analysis of complex intelligent control systems. The RCS architecture consists of a hierarchically layered set of functional processing modules connected by a network of communication pathways. The primary distinguishing feature of the layers is the bandwidth of the control loops. The characteristic bandwidth of each level is determined by the spatial and temporal integration window of filters, the temporal frequency of signals and events, the spatial frequency of patterns, and the planning horizon and granularity of the planners that operate at each level. At each level, tasks are decomposed into sequential subtasks, to be performed by cooperating sets of subordinate agents. At each level, signals from sensors are filtered and correlated with spatial and temporal features that are relevant to the control function being implemented at that level.

Personality Traits and General Intelligence as Predictors of Academic Performance: A Structural Equation Modelling Approach

ERIC Educational Resources Information Center

Rosander, Pia; Backstrom, Martin; Stenberg, Georg

2011-01-01

The aim of the present study was to investigate the extent to which personality traits, after controlling for general intelligence, predict academic performance in different school subjects. Upper secondary school students in Sweden (N=315) completed the Wonderlic IQ test (Wonderlic, 1992) and the IPIP-NEO-PI test (Goldberg, 1999). A series of…

Optimal tactics for close support operations. III - Degraded intelligence and communications

NASA Astrophysics Data System (ADS)

Hess, J.; Kalaba, R.; Kagiwada, H.; Spingarn, K.; Tsokos, C.

1980-04-01

A new generation of C3 (command, control, and communication) models for military cybernetics is developed. Recursive equations for the solution of the C3 problem are derived for an amphibious campaign with linear time-varying dynamics. Air and ground commanders are assumed to have no intelligence and no communications. Numerical results are given for the optimal decision rules.

Design of Distributed Cyber-Physical Systems for Connected and Automated Vehicles with Implementing Methodologies

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

Feng, Yixiong; Hu, Bingtao; Hao, He

With the development of communication and control technology, intelligent transportation systems have received increasing attention from both industry and academia. Intelligent transportation systems are supported by the Internet of Things, Cyber-Physical System, Artificial Intelligence, Cloud Computing and many other technologies, which supply fundamental information for connected and automated vehicles. Although plenty of studies have provided different formulations for intelligent transportation systems, many of them depend on Master Control Center. However, a centralized control mode requires a huge amount of data transmission and high level of hardware configuration and may cause communication delay and privacy leak. Some distributed architectures have beenmore » proposed to overcome the above problems but systematized technologies to collect and exchange information, process large amounts of data, model the dynamics of vehicles, and safely control the connected and automated vehicles are not explored in detail. In this paper, we proposed a novel distributed cyber-physical system for connected and automated vehicles in which every vehicle is modeled as a double-integrator using edge computing to analyze information collected from its nearest neighbors. The vehicles are supposed to travel along a desired trajectory and to maintain a rigid formation geometry. Related methodologies for the proposed system are illustrated and experiments are conducted showing that the performance of the connected and automated vehicles matches very well with analytic predictions. Some design guidelines and open questions are provided for the future study.« less

Design of Distributed Cyber-Physical Systems for Connected and Automated Vehicles with Implementing Methodologies

DOE PAGES

Feng, Yixiong; Hu, Bingtao; Hao, He; ...

2018-02-14

With the development of communication and control technology, intelligent transportation systems have received increasing attention from both industry and academia. Intelligent transportation systems are supported by the Internet of Things, Cyber-Physical System, Artificial Intelligence, Cloud Computing and many other technologies, which supply fundamental information for connected and automated vehicles. Although plenty of studies have provided different formulations for intelligent transportation systems, many of them depend on Master Control Center. However, a centralized control mode requires a huge amount of data transmission and high level of hardware configuration and may cause communication delay and privacy leak. Some distributed architectures have beenmore » proposed to overcome the above problems but systematized technologies to collect and exchange information, process large amounts of data, model the dynamics of vehicles, and safely control the connected and automated vehicles are not explored in detail. In this paper, we proposed a novel distributed cyber-physical system for connected and automated vehicles in which every vehicle is modeled as a double-integrator using edge computing to analyze information collected from its nearest neighbors. The vehicles are supposed to travel along a desired trajectory and to maintain a rigid formation geometry. Related methodologies for the proposed system are illustrated and experiments are conducted showing that the performance of the connected and automated vehicles matches very well with analytic predictions. Some design guidelines and open questions are provided for the future study.« less

Computational modeling of driver speed control with its applications in developing intelligent transportation system to prevent speeding-related accidents.

DOT National Transportation Integrated Search

2013-08-01

Speeding is the leading contributing factor in fatal accidents in NY state, according to NY State Department of Motor : Vehicle Accidents Statistical Summary (2009). Understanding and modeling speeding and speed control is one of major : challenges i...

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.

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.

A novel memristive multilayer feedforward small-world neural network with its applications in PID control.

PubMed

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.

A Novel Memristive Multilayer Feedforward Small-World Neural Network with Its Applications in PID Control

PubMed Central

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

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

PubMed

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

2015-02-25

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

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

PubMed Central

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

2015-01-01

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

Intelligent systems in the context of surrounding environment.

PubMed

Wakeling, J; Bak, P

2001-11-01

We investigate the behavioral patterns of a population of agents, each controlled by a simple biologically motivated neural network model, when they are set in competition against each other in the minority model of Challet and Zhang. We explore the effects of changing agent characteristics, demonstrating that crowding behavior takes place among agents of similar memory, and show how this allows unique "rogue" agents with higher memory values to take advantage of a majority population. We also show that agents' analytic capability is largely determined by the size of the intermediary layer of neurons. In the context of these results, we discuss the general nature of natural and artificial intelligence systems, and suggest intelligence only exists in the context of the surrounding environment (embodiment).

[An object-oriented intelligent engineering design approach for lake pollution control].

PubMed

Zou, Rui; Zhou, Jing; Liu, Yong; Zhu, Xiang; Zhao, Lei; Yang, Ping-Jian; Guo, Huai-Cheng

2013-03-01

Regarding the shortage and deficiency of traditional lake pollution control engineering techniques, a new lake pollution control engineering approach was proposed in this study, based on object-oriented intelligent design (OOID) from the perspective of intelligence. It can provide a new methodology and framework for effectively controlling lake pollution and improving water quality. The differences between the traditional engineering techniques and the OOID approach were compared. The key points for OOID were described as object perspective, cause and effect foundation, set points into surface, and temporal and spatial optimization. The blue algae control in lake was taken as an example in this study. The effect of algae control and water quality improvement were analyzed in details from the perspective of object-oriented intelligent design based on two engineering techniques (vertical hydrodynamic mixer and pumping algaecide recharge). The modeling results showed that the traditional engineering design paradigm cannot provide scientific and effective guidance for engineering design and decision-making regarding lake pollution. Intelligent design approach is based on the object perspective and quantitative causal analysis in this case. This approach identified that the efficiency of mixers was much higher than pumps in achieving the goal of low to moderate water quality improvement. However, when the objective of water quality exceeded a certain value (such as the control objective of peak Chla concentration exceeded 100 microg x L(-1) in this experimental water), the mixer cannot achieve this goal. The pump technique can achieve the goal but with higher cost. The efficiency of combining the two techniques was higher than using one of the two techniques alone. Moreover, the quantitative scale control of the two engineering techniques has a significant impact on the actual project benefits and costs.

An Intelligent Agent-Controlled and Robot-Based Disassembly Assistant

NASA Astrophysics Data System (ADS)

Jungbluth, Jan; Gerke, Wolfgang; Plapper, Peter

2017-09-01

One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate “the problem of loosening a connection and the distribution of the work” as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.

Associations between motor timing, music practice, and intelligence studied in a large sample of twins.

PubMed

Ullén, Fredrik; Mosing, Miriam A; Madison, Guy

2015-03-01

Music performance depends critically on precise processing of time. A common model behavior in studies of motor timing is isochronous serial interval production (ISIP), that is, hand/finger movements with a regular beat. ISIP accuracy is related to both music practice and intelligence. Here we present a study of these associations in a large twin cohort, demonstrating that the effects of music practice and intelligence on motor timing are additive, with no significant multiplicative (interaction) effect. Furthermore, the association between music practice and motor timing was analyzed with the use of a co-twin control design using intrapair differences. These analyses revealed that the phenotypic association disappeared when all genetic and common environmental factors were controlled. This suggests that the observed association may not reflect a causal effect of music practice on ISIP performance but rather reflect common influences (e.g., genetic effects) on both outcomes. The relevance of these findings for models of practice and expert performance is discussed. © 2014 New York Academy of Sciences.

An intelligent agent for optimal river-reservoir system management

NASA Astrophysics Data System (ADS)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

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

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.

Transition from intelligence cycle to intelligence process: the network-centric intelligence in narrow seas

NASA Astrophysics Data System (ADS)

Büker, Engin

2015-05-01

The defence technologies which have been developing and changing rapidly, today make it difficult to be able to foresee the next environment and spectrum of warfare. When said change and development is looked in specific to the naval operations, it can be said that the possible battlefield and scenarios to be developed in the near and middle terms (5-20 years) are more clarified with compare to other force components. Network Centric Naval Warfare Concept that was developed for the floating, diving and flying fleet platforms which serves away from its own mainland for miles, will keep its significance in the future. Accordingly, Network Centric Intelligence structure completely integrating with the command and control systems will have relatively more importance. This study will firstly try to figure out the transition from the traditional intelligence cycle that is still used in conventional war to Network Centric Intelligence Production Process. In the last part, the use of this new approach on the base of UAV that is alternative to satellite based command control and data transfer systems in the joint operations in narrow seas will be examined, a model suggestion for the use of operative and strategic UAVs which are assured within the scope of the NATO AGS2 for this aim will be brought.

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

NASA Technical Reports Server (NTRS)

Chen, Alexander Y.

1990-01-01

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Autonomous control systems - Architecture and fundamental issues

NASA Technical Reports Server (NTRS)

Antsaklis, P. J.; Passino, K. M.; Wang, S. J.

1988-01-01

A hierarchical functional autonomous controller architecture is introduced. In particular, the architecture for the control of future space vehicles is described in detail; it is designed to ensure the autonomous operation of the control system and it allows interaction with the pilot and crew/ground station, and the systems on board the autonomous vehicle. The fundamental issues in autonomous control system modeling and analysis are discussed. It is proposed to utilize a hybrid approach to modeling and analysis of autonomous systems. This will incorporate conventional control methods based on differential equations and techniques for the analysis of systems described with a symbolic formalism. In this way, the theory of conventional control can be fully utilized. It is stressed that autonomy is the design requirement and intelligent control methods appear at present, to offer some of the necessary tools to achieve autonomy. A conventional approach may evolve and replace some or all of the `intelligent' functions. It is shown that in addition to conventional controllers, the autonomous control system incorporates planning, learning, and FDI (fault detection and identification).

Getting to the Heart of Performance.

ERIC Educational Resources Information Center

Stock, Byron

1996-01-01

Human performance technology (HPT) models are compared. One model groups performance factors by their relation to the performer (internal or external). A second model categorizes factors by which organizational level has the most control over them (executive, managerial, or individual). A third model considers rational and emotional intelligences;…

Simulation and optimization of an experimental membrane wastewater treatment plant using computational intelligence methods.

PubMed

Ludwig, T; Kern, P; Bongards, M; Wolf, C

2011-01-01

The optimization of relaxation and filtration times of submerged microfiltration flat modules in membrane bioreactors used for municipal wastewater treatment is essential for efficient plant operation. However, the optimization and control of such plants and their filtration processes is a challenging problem due to the underlying highly nonlinear and complex processes. This paper presents the use of genetic algorithms for this optimization problem in conjunction with a fully calibrated simulation model, as computational intelligence methods are perfectly suited to the nonconvex multi-objective nature of the optimization problems posed by these complex systems. The simulation model is developed and calibrated using membrane modules from the wastewater simulation software GPS-X based on the Activated Sludge Model No.1 (ASM1). Simulation results have been validated at a technical reference plant. They clearly show that filtration process costs for cleaning and energy can be reduced significantly by intelligent process optimization.

Soundscape elaboration from anthrophonic adaptation of community noise

NASA Astrophysics Data System (ADS)

Teddy Badai Samodra, FX

2018-03-01

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

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A mathematical model of the creative control process is presented that illustrates the use for mobile robots. Examples from a variety of intelligent mobile robot applications are also presented. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to many applications.

Piezoceramic devices and artificial intelligence time varying concepts in smart structures

NASA Technical Reports Server (NTRS)

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

1990-01-01

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

Promoting Well-Being: The Contribution of Emotional Intelligence

PubMed Central

Di Fabio, Annamaria; Kenny, Maureen E.

2016-01-01

Adopting a primary prevention perspective, this study examines competencies with the potential to enhance well-being and performance among future workers. More specifically, the contributions of ability-based and trait models of emotional intelligence (EI), assessed through well-established measures, to indices of hedonic and eudaimonic well-being were examined for a sample of 157 Italian high school students. The Mayer–Salovey–Caruso Emotional Intelligence Test was used to assess ability-based EI, the Bar-On Emotional Intelligence Inventory and the Trait Emotional Intelligence Questionnaire were used to assess trait EI, the Positive and Negative Affect Scale and the Satisfaction With Life Scale were used to assess hedonic well-being, and the Meaningful Life Measure was used to assess eudaimonic well-being. The results highlight the contributions of trait EI in explaining both hedonic and eudaimonic well-being, after controlling for the effects of fluid intelligence and personality traits. Implications for further research and intervention regarding future workers are discussed. PMID:27582713

Promoting Well-Being: The Contribution of Emotional Intelligence.

PubMed

Di Fabio, Annamaria; Kenny, Maureen E

2016-01-01

Adopting a primary prevention perspective, this study examines competencies with the potential to enhance well-being and performance among future workers. More specifically, the contributions of ability-based and trait models of emotional intelligence (EI), assessed through well-established measures, to indices of hedonic and eudaimonic well-being were examined for a sample of 157 Italian high school students. The Mayer-Salovey-Caruso Emotional Intelligence Test was used to assess ability-based EI, the Bar-On Emotional Intelligence Inventory and the Trait Emotional Intelligence Questionnaire were used to assess trait EI, the Positive and Negative Affect Scale and the Satisfaction With Life Scale were used to assess hedonic well-being, and the Meaningful Life Measure was used to assess eudaimonic well-being. The results highlight the contributions of trait EI in explaining both hedonic and eudaimonic well-being, after controlling for the effects of fluid intelligence and personality traits. Implications for further research and intervention regarding future workers are discussed.

Age versus schooling effects on intelligence development.

PubMed

Cahan, S; Cohen, N

1989-10-01

The effect of formal education, as opposed to chronological age, on intelligence development has suffered from inadequate empirical investigation. Most studies of this issue have relied on natural variation in exposure to school among children of the same age, thus confounding differences in schooling with differences in other intelligence-related variables. This difficulty can be overcome by a quasi-experimental paradigm involving comparison between children who differ in both chronological age and schooling. The present study applies this paradigm to the estimation of the independent effects of age and schooling in grades 5 and 6 on raw scores obtained on a variety of general ability tests. The sample included all students in Jerusalem's Hebrew-language, state-controlled elementary schools. The results unambiguously point to schooling as the major factor underlying the increase of intelligence test scores as a function of age and to the larger effect schooling has on verbal than nonverbal tests. These results contribute to our understanding of the causal model underlying intelligence development and call for reconsideration of the conceptual basis underlying the definition of deviation-IQ scores. Some implications of these results concerning the distinction between intelligence and scholastic achievement, the causal model underlying the development of "crystallized" and "fluid" abilities, and the notion of "culture-fair" tests are discussed.

Artificial neural networks and approximate reasoning for intelligent control in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1991-01-01

A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

Do Narcissism and Emotional Intelligence Win Us Friends? Modeling Dynamics of Peer Popularity Using Inferential Network Analysis.

PubMed

Czarna, Anna Z; Leifeld, Philip; Śmieja, Magdalena; Dufner, Michael; Salovey, Peter

2016-09-27

This research investigated effects of narcissism and emotional intelligence (EI) on popularity in social networks. In a longitudinal field study, we examined the dynamics of popularity in 15 peer groups in two waves (N = 273). We measured narcissism, ability EI, and explicit and implicit self-esteem. In addition, we measured popularity at zero acquaintance and 3 months later. We analyzed the data using inferential network analysis (temporal exponential random graph modeling, TERGM) accounting for self-organizing network forces. People high in narcissism were popular, but increased less in popularity over time than people lower in narcissism. In contrast, emotionally intelligent people increased more in popularity over time than less emotionally intelligent people. The effects held when we controlled for explicit and implicit self-esteem. These results suggest that narcissism is rather disadvantageous and that EI is rather advantageous for long-term popularity. © 2016 by the Society for Personality and Social Psychology, Inc.

CATS-based Air Traffic Controller Agents

NASA Technical Reports Server (NTRS)

Callantine, Todd J.

2002-01-01

This report describes intelligent agents that function as air traffic controllers. Each agent controls traffic in a single sector in real time; agents controlling traffic in adjoining sectors can coordinate to manage an arrival flow across a given meter fix. The purpose of this research is threefold. First, it seeks to study the design of agents for controlling complex systems. In particular, it investigates agent planning and reactive control functionality in a dynamic environment in which a variety perceptual and decision making skills play a central role. It examines how heuristic rules can be applied to model planning and decision making skills, rather than attempting to apply optimization methods. Thus, the research attempts to develop intelligent agents that provide an approximation of human air traffic controller behavior that, while not based on an explicit cognitive model, does produce task performance consistent with the way human air traffic controllers operate. Second, this research sought to extend previous research on using the Crew Activity Tracking System (CATS) as the basis for intelligent agents. The agents use a high-level model of air traffic controller activities to structure the control task. To execute an activity in the CATS model, according to the current task context, the agents reference a 'skill library' and 'control rules' that in turn execute the pattern recognition, planning, and decision-making required to perform the activity. Applying the skills enables the agents to modify their representation of the current control situation (i.e., the 'flick' or 'picture'). The updated representation supports the next activity in a cycle of action that, taken as a whole, simulates air traffic controller behavior. A third, practical motivation for this research is to use intelligent agents to support evaluation of new air traffic control (ATC) methods to support new Air Traffic Management (ATM) concepts. Current approaches that use large, human-in-the-loop simulations are unquestionably valuable for this purpose, but pose considerable logistical, fiscal, and experimental control problems. First, data analysis is extremely complicated, owing simply to the large number of participants and data sources in such simulations. In addition, experienced human air traffic controllers working adjacent sectors tend to flexibly adapt to the evolving control problem - potentially shifting to other strategies than those under investigation. In addition, their performance is tightly coupled to the control interface, which in the development phase may support some concepts and supporting strategies better than others. A simple shift in strategy by one controller can change the character of a particular traffic scenario dramatically, which makes experimental comparison of ATC performance under different traffic scenarios difficult. Training a given team of controllers on operations under a new ATM concept for a sufficient period of time could avert such difficulties, but instituting an adequate training program is expensive and logistically difficult.

Smart Prosthetic Hand Technology - Phase 2

DTIC Science & Technology

2011-05-01

identification and estimation, hand motion estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The...Smart Prosthetics, Bio- Robotics , Intelligent EMG Signal Processing, Embedded Systems and Intelligent Control, Inflammatory Responses of Cells, Toxicity...estimation, intelligent embedded systems and control, robotic hand and biocompatibility and signaling. The developed identification algorithm using a new

Planning deficits in polysubstance dependent users: Differential associations with severity of drug use and intelligence.

PubMed

Valls-Serrano, C; Verdejo-García, A; Caracuel, A

2016-05-01

Polysubstance use is associated with alterations in different components of executive functioning such as working memory and response inhibition. Nevertheless, less attention has been given to executive planning skills, which are required to benefit of low structured interventions. This study examines the association between severity of use of cocaine, heroin, alcohol, fluid and crystallized intelligence and planning tasks varying on degree of structure. Data were collected from 60 polysubstance users and 30 healthy controls. Cognitive assessment consisted of three planning tasks with different structure levels: Stockings of Cambridge, Zoo Map test, and Multiple Errands Test. Polysubstance users had significant planning deficits across the three tasks compared to healthy controls. Hierarchical regression models showed that severity of drug use and fluid and crystallized intelligence significantly explained performance in all the planning tasks. However, these associations were higher for low-structured real world tasks. These low-structured tasks also showed a unique association with crystallized but not fluid intelligence. Drug abuse is negatively associated with planning abilities, and intelligence is positively associated with planning performance in real-world tasks. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2011-06-30

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

Lower verbal intelligence is associated with diabetic complications and slower walking speed in people with Type 2 diabetes: the Maastricht Study.

PubMed

Spauwen, P J J; Martens, R J H; Stehouwer, C D A; Verhey, F R J; Schram, M T; Sep, S J S; van der Kallen, C J H; Dagnelie, P C; Henry, R M A; Schaper, N C; van Boxtel, M P J

2016-12-01

To determine the association of verbal intelligence, a core constituent of health literacy, with diabetic complications and walking speed in people with Type 2 diabetes. This study was performed in 228 people with Type 2 diabetes participating in the Maastricht Study, a population-based cohort study. We examined the cross-sectional associations of score on the vocabulary test of the Groningen Intelligence Test with: 1) determinants of diabetic complications (HbA 1c , blood pressure and lipid level); 2) diabetic complications: chronic kidney disease, neuropathic pain, self-reported history of cardiovascular disease and carotid intima-media thickness; and 3) walking speed. Analyses were performed using linear regression and adjusted in separate models for potential confounders and mediators. Significant age- and sex-adjusted associations were additionally adjusted for educational level in a separate model. After full adjustment, lower verbal intelligence was associated with the presence of neuropathic pain [odds ratio (OR) 1.18, 95% CI 1.02;1.36], cardiovascular disease (OR 1.14, 95% CI 1.01;1.30), and slower walking speed (regression coefficient -0.011 m/s, 95% CI -0.021; -0.002 m/s). These associations were largely explained by education. Verbal intelligence was not associated with blood pressure, glycaemic control, lipid control, chronic kidney disease or carotid intima-media thickness. Lower verbal intelligence was associated with the presence of some diabetic complications and with a slower walking speed, a measure of physical functioning. Educational level largely explained these associations. This implies that clinicians should be aware of the educational level of people with diabetes and should provide information at a level of complexity tailored to the patient. © 2016 Diabetes UK.

AST Critical Propulsion and Noise Reduction Technologies for Future Commercial Subsonic Engines Area of Interest 1.0: Reliable and Affordable Control Systems

NASA Technical Reports Server (NTRS)

Myers, William; Winter, Steve

2006-01-01

The General Electric Reliable and Affordable Controls effort under the NASA Advanced Subsonic Technology (AST) Program has designed, fabricated, and tested advanced controls hardware and software to reduce emissions and improve engine safety and reliability. The original effort consisted of four elements: 1) a Hydraulic Multiplexer; 2) Active Combustor Control; 3) a Variable Displacement Vane Pump (VDVP); and 4) Intelligent Engine Control. The VDVP and Intelligent Engine Control elements were cancelled due to funding constraints and are reported here only to the state they progressed. The Hydraulic Multiplexing element developed and tested a prototype which improves reliability by combining the functionality of up to 16 solenoids and servo-valves into one component with a single electrically powered force motor. The Active Combustor Control element developed intelligent staging and control strategies for low emission combustors. This included development and tests of a Controlled Pressure Fuel Nozzle for fuel sequencing, a Fuel Multiplexer for individual fuel cup metering, and model-based control logic. Both the Hydraulic Multiplexer and Controlled Pressure Fuel Nozzle system were cleared for engine test. The Fuel Multiplexer was cleared for combustor rig test which must be followed by an engine test to achieve full maturation.

Virtual collaborative environments: programming and controlling robotic devices remotely

NASA Astrophysics Data System (ADS)

Davies, Brady R.; McDonald, Michael J., Jr.; Harrigan, Raymond W.

1995-12-01

This paper describes a technology for remote sharing of intelligent electro-mechanical devices. An architecture and actual system have been developed and tested, based on the proposed National Information Infrastructure (NII) or Information Highway, to facilitate programming and control of intelligent programmable machines (like robots, machine tools, etc.). Using appropriate geometric models, integrated sensors, video systems, and computing hardware; computer controlled resources owned and operated by different (in a geographic sense as well as legal sense) entities can be individually or simultaneously programmed and controlled from one or more remote locations. Remote programming and control of intelligent machines will create significant opportunities for sharing of expensive capital equipment. Using the technology described in this paper, university researchers, manufacturing entities, automation consultants, design entities, and others can directly access robotic and machining facilities located across the country. Disparate electro-mechanical resources will be shared in a manner similar to the way supercomputers are accessed by multiple users. Using this technology, it will be possible for researchers developing new robot control algorithms to validate models and algorithms right from their university labs without ever owning a robot. Manufacturers will be able to model, simulate, and measure the performance of prospective robots before selecting robot hardware optimally suited for their intended application. Designers will be able to access CNC machining centers across the country to fabricate prototypic parts during product design validation. An existing prototype architecture and system has been developed and proven. Programming and control of a large gantry robot located at Sandia National Laboratories in Albuquerque, New Mexico, was demonstrated from such remote locations as Washington D.C., Washington State, and Southern California.

Primary nocturnal enuresis is associated with lower intelligence quotient scores in boys from poorer socioeconomic status families.

PubMed

Basiri, Abbas; Bahrainian, Seyed Abdolmajid; Khoshdel, Alireza; Jalaly, Niloofar; Golshan, Shabnam; Pakmanesh, Hamid

2017-03-01

To explore intelligence quotient in boys with primary nocturnal enuresis compared with normal boys considering their socioeconomic status. A total of 152 school-aged boys (including 55 boys with primary nocturnal enuresis and 97 matched normal controls) were assessed. Boys with a history of any neurological or urological disease were excluded. Two different districts of Tehran: Khani-Abad (a poor district) and Pirouzi (a middle class district) districts were enrolled according to socioeconomic status data reported by the World Health Organization. Intelligence tests were carried out using a validated Iranian translation of the Wechsler Intelligence Scale for Children Revised. Total, as well as performance intelligence quotient and verbal intelligence quotient scores and verbal-performance discrepancy (the difference between verbal and performance intelligence quotient scores for each individual) were compared using a t-test between boys with primary nocturnal enuresis in each district and their matched controls. Considering each district separately, the total intelligence quotient score was lower in primary nocturnal enuresis cases than controls only in the lower income district (90.7 ± 23.3 vs 104.8 ± 14.7, P = 0.002). Similarly, boys with primary nocturnal enuresis ranked lower in verbal intelligence quotient (P = 0.002) and performance intelligence quotient (P = 0.004) compared with their matched normal controls only in lower income district, whereas in the higher income district, boys with primary nocturnal enuresis ranked similar in total intelligence quotient to their matched controls. Boys with primary nocturnal enuresis had a lower intelligence quotient compared with the control participants only in low-income district. It seems important to adjust the results of the intelligence quotient assessment in these children according to their socioeconomic status. © 2017 The Japanese Urological Association.

Prediction of pork loin quality using online computer vision system and artificial intelligence model.

PubMed

Sun, Xin; Young, Jennifer; Liu, Jeng-Hung; Newman, David

2018-06-01

The objective of this project was to develop a computer vision system (CVS) for objective measurement of pork loin under industry speed requirement. Color images of pork loin samples were acquired using a CVS. Subjective color and marbling scores were determined according to the National Pork Board standards by a trained evaluator. Instrument color measurement and crude fat percentage were used as control measurements. Image features (18 color features; 1 marbling feature; 88 texture features) were extracted from whole pork loin color images. Artificial intelligence prediction model (support vector machine) was established for pork color and marbling quality grades. The results showed that CVS with support vector machine modeling reached the highest prediction accuracy of 92.5% for measured pork color score and 75.0% for measured pork marbling score. This research shows that the proposed artificial intelligence prediction model with CVS can provide an effective tool for predicting color and marbling in the pork industry at online speeds. Copyright © 2018 Elsevier Ltd. All rights reserved.

An intelligent training system for space shuttle flight controllers

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Wang, Lui; Baffes, Paul; Hua, Grace

1988-01-01

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (DeplEx for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The DeplEx also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of DeplEx in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

An intelligent training system for space shuttle flight controllers

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen; Wang, Lui; Baffles, Paul; Hua, Grace

1988-01-01

An autonomous intelligent training system which integrates expert system technology with training/teaching methodologies is described. The system was designed to train Mission Control Center (MCC) Flight Dynamics Officers (FDOs) to deploy a certain type of satellite from the Space Shuttle. The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system consists of five components: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The interface provides the trainee with information of the characteristics of the current training session and with on-line help. The domain expert (Dep1Ex for Deploy Expert) contains the rules and procedural knowledge needed by the FDO to carry out the satellite deploy. The Dep1Ex also contains mal-rules which permit the identification and diagnosis of common errors made by the trainee. The training session manager (TSM) examines the actions of the trainee and compares them with the actions of Dep1Ex in order to determine appropriate responses. A trainee model is developed for each individual using the system. The model includes a history of the trainee's interactions with the training system and provides evaluative data on the trainee's current skill level. A training scenario generator (TSG) designs appropriate training exercises for each trainee based on the trainee model and the training goals. All of the expert system components of PD/ICAT communicate via a common blackboard. The PD/ICAT is currently being tested. Ultimately, this project will serve as a vehicle for developing a general architecture for intelligent training systems together with a software environment for creating such systems.

Appearing smart: the impression management of intelligence, person perception accuracy, and behavior in social interaction.

PubMed

Murphy, Nora A

2007-03-01

Intelligence is an important trait that affects everyday social interaction. The present research utilized the ecological perspective of social perception to investigate the impression management of intelligence and strangers' evaluations of targets' intelligence levels. The ability to effectively portray an impression of intelligence to outside judges as well as interaction partners was appraised and the effect of impression management on the accurate judgment of intelligence was assessed. In addition, targets' behavior was studied in relation to impression management, perceived intelligence, and actual measured intelligence. Impression-managing targets appeared more intelligent to video judges but not to their interaction partner as compared to controls. The intelligence quotient (IQ) of impression-managing targets was more accurately judged than controls' IQ. Impression-managing targets displayed distinct nonverbal behavioral patterns that differed from controls. Looking while speaking was a key behavior: It significantly correlated with IQ, was successfully manipulated by impression-managing targets, and contributed to higher perceived intelligence ratings.

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1989-01-01

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

PSECMAC intelligent insulin schedule for diabetic blood glucose management under nonmeal announcement.

PubMed

Teddy, S D; Quek, C; Lai, E M-K; Cinar, A

2010-03-01

Therapeutically, the closed-loop blood glucose-insulin regulation paradigm via a controllable insulin pump offers a potential solution to the management of diabetes. However, the development of such a closed-loop regulatory system to date has been hampered by two main issues: 1) the limited knowledge on the complex human physiological process of glucose-insulin metabolism that prevents a precise modeling of the biological blood glucose control loop; and 2) the vast metabolic biodiversity of the diabetic population due to varying exogneous and endogenous disturbances such as food intake, exercise, stress, and hormonal factors, etc. In addition, current attempts of closed-loop glucose regulatory techniques generally require some form of prior meal announcement and this constitutes a severe limitation to the applicability of such systems. In this paper, we present a novel intelligent insulin schedule based on the pseudo self-evolving cerebellar model articulation controller (PSECMAC) associative learning memory model that emulates the healthy human insulin response to food ingestion. The proposed PSECMAC intelligent insulin schedule requires no prior meal announcement and delivers the necessary insulin dosage based only on the observed blood glucose fluctuations. Using a simulated healthy subject, the proposed PSECMAC insulin schedule is demonstrated to be able to accurately capture the complex human glucose-insulin dynamics and robustly addresses the intraperson metabolic variability. Subsequently, the PSECMAC intelligent insulin schedule is employed on a group of type-1 diabetic patients to regulate their impaired blood glucose levels. Preliminary simulation results are highly encouraging. The work reported in this paper represents a major paradigm shift in the management of diabetes where patient compliance is poor and the need for prior meal announcement under current treatment regimes poses a significant challenge to an active lifestyle.

Intent inferencing with a model-based operator's associate

NASA Technical Reports Server (NTRS)

Jones, Patricia M.; Mitchell, Christine M.; Rubin, Kenneth S.

1989-01-01

A portion of the Operator Function Model Expert System (OFMspert) research project is described. OFMspert is an architecture for an intelligent operator's associate or assistant that can aid the human operator of a complex, dynamic system. Intelligent aiding requires both understanding and control. The understanding (i.e., intent inferencing) ability of the operator's associate is discussed. Understanding or intent inferencing requires a model of the human operator; the usefulness of an intelligent aid depends directly on the fidelity and completeness of its underlying model. The model chosen for this research is the operator function model (OFM). The OFM represents operator functions, subfunctions, tasks, and actions as a heterarchic-hierarchic network of finite state automata, where the arcs in the network are system triggering events. The OFM provides the structure for intent inferencing in that operator functions and subfunctions correspond to likely operator goals and plans. A blackboard system similar to that of Human Associative Processor (HASP) is proposed as the implementation of intent inferencing function. This system postulates operator intentions based on current system state and attempts to interpret observed operator actions in light of these hypothesized intentions.

The effect of cerebral palsy on arithmetic accuracy is mediated by working memory, intelligence, early numeracy, and instruction time.

PubMed

Jenks, Kathleen M; de Moor, Jan; van Lieshout, Ernest C D M; Maathuis, Karel G B; Keus, Inge; Gorter, Jan Willem

2007-01-01

The development of addition and subtraction accuracy was assessed in first graders with cerebral palsy (CP) in both mainstream (16) and special education (41) and a control group of first graders in mainstream education (16). The control group out-performed the CP groups in addition and subtraction accuracy and this difference could not be fully explained by differences in intelligence. Both CP groups showed evidence of working memory deficits. The three groups exhibited different developmental patterns in the area of early numeracy skills. Children with CP in special education were found to receive less arithmetic instruction and instruction time was positively related to arithmetic accuracy. Structural equation modeling revealed that the effect of CP on arithmetic accuracy is mediated by intelligence, working memory, early numeracy, and instruction time.

Intelligent Signal Processing for Active Control

DTIC Science & Technology

1992-06-17

FUNDING NUMSI Intelligent Signal Processing for Active Control C-NO001489-J-1633 G. AUTHOR(S) P.A. Ramamoorthy 7. P2RFORMING ORGANIZATION NAME(S) AND...unclassified .unclassified unclassified L . I mu-. W UNIVERSITY OF CINCINNATI COLLEGE OF ENGINEERING Intelligent Signal Processing For Rctiue Control...NAURI RESEARCH Conkact No: NO1489-J-1633 P.L: P.A.imoodh Intelligent Signal Processing For Active Control 1 Executive Summary The thrust of this

The implementation of intelligent home controller

NASA Astrophysics Data System (ADS)

Li, Biqing; Li, Zhao

2018-04-01

This paper mainly talks about the working way of smart home terminal controller and the design of hardware and software. Controlling the lights and by simulating the lamp and the test of the curtain, destroy the light of lamp ON-OFF and the curtain's UP-DOWN by simulating the lamp and the test of the cuetain. Through the sensor collects the ambient information and sends to the network, such as light, temperature and humidity. Besides, it can realise the control of intelligent home control by PCS. Terminal controller of intelligent home which is based on ZiBee technology has into the intelligent home system, it provides people with convenient, safe and intelligent household experience.

Design and implementation of self-balancing coaxial two wheel robot based on HSIC

NASA Astrophysics Data System (ADS)

Hu, Tianlian; Zhang, Hua; Dai, Xin; Xia, Xianfeng; Liu, Ran; Qiu, Bo

2007-12-01

This thesis has studied the control problem concerning position and orientation control of self-balancing coaxial two wheel robot based on the human simulated intelligent control (HSIC) theory. Adopting Lagrange equation, the dynamic model of self-balancing coaxial two-wheel Robot is built up, and the Sensory-motor Intelligent Schemas (SMIS) of HSIC controller for the robot is designed by analyzing its movement and simulating the human controller. In robot's motion process, by perceiving position and orientation of the robot and using multi-mode control strategy based on characteristic identification, the HSIC controller enables the robot to control posture. Utilizing Matlab/Simulink, a simulation platform is established and a motion controller is designed and realized based on RT-Linux real-time operating system, employing high speed ARM9 processor S3C2440 as kernel of the motion controller. The effectiveness of the new design is testified by the experiment.

The dynamics of Machiavellian intelligence.

PubMed

Gavrilets, Sergey; Vose, Aaron

2006-11-07

The "Machiavellian intelligence" hypothesis (or the "social brain" hypothesis) posits that large brains and distinctive cognitive abilities of humans have evolved via intense social competition in which social competitors developed increasingly sophisticated "Machiavellian" strategies as a means to achieve higher social and reproductive success. Here we build a mathematical model aiming to explore this hypothesis. In the model, genes control brains which invent and learn strategies (memes) which are used by males to gain advantage in competition for mates. We show that the dynamics of intelligence has three distinct phases. During the dormant phase only newly invented memes are present in the population. During the cognitive explosion phase the population's meme count and the learning ability, cerebral capacity (controlling the number of different memes that the brain can learn and use), and Machiavellian fitness of individuals increase in a runaway fashion. During the saturation phase natural selection resulting from the costs of having large brains checks further increases in cognitive abilities. Overall, our results suggest that the mechanisms underlying the "Machiavellian intelligence" hypothesis can indeed result in the evolution of significant cognitive abilities on the time scale of 10 to 20 thousand generations. We show that cerebral capacity evolves faster and to a larger degree than learning ability. Our model suggests that there may be a tendency toward a reduction in cognitive abilities (driven by the costs of having a large brain) as the reproductive advantage of having a large brain decreases and the exposure to memes increases in modern societies.

A Petri-net coordination model for an intelligent mobile robot

NASA Technical Reports Server (NTRS)

Wang, F.-Y.; Kyriakopoulos, K. J.; Tsolkas, A.; Saridis, G. N.

1990-01-01

The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.

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...

Information flow analysis and Petri-net-based modeling for welding flexible manufacturing cell

NASA Astrophysics Data System (ADS)

Qiu, T.; Chen, Shanben; Wang, Y. T.; Wu, Lin

2000-10-01

Due to the development of advanced manufacturing technology and the introduction of Smart-Manufacturing notion in the field of modern industrial production, welding flexible manufacturing system (WFMS) using robot technology has become the inevitable developing direction on welding automation. In WFMS process, the flexibility for different welding products and the realizing on corresponding welding parameters control are the guarantees for welding quality. Based on a new intelligent arc-welding flexible manufacturing cell (WFMC), the system structure and control policies are studied in this paper. Aiming at the different information flows among every subsystem and central monitoring computer in this WFMC, Petri net theory is introduced into the process of welding manufacturing. With its help, a discrete control model of WFMC has been constructed, in which the system status is regarded as place and the control process is regarded as transition. Moreover, grounded on automation Petri net principle, the judging and utilizing of information obtained from welding sensors are imported into net structure, which extends the traditional Petri net concepts. The control model and policies researched in this paper have established foundation for further intelligent real-time control on WFMC and WFMS.

Hypermedia and intelligent tutoring applications in a mission operations environment

NASA Technical Reports Server (NTRS)

Ames, Troy; Baker, Clifford

1990-01-01

Hypermedia, hypertext and Intelligent Tutoring System (ITS) applications to support all phases of mission operations are investigated. The application of hypermedia and ITS technology to improve system performance and safety in supervisory control is described - with an emphasis on modeling operator's intentions in the form of goals, plans, tasks, and actions. Review of hypermedia and ITS technology is presented as may be applied to the tutoring of command and control languages. Hypertext based ITS is developed to train flight operation teams and System Test and Operation Language (STOL). Specific hypermedia and ITS application areas are highlighted, including: computer aided instruction of flight operation teams (STOL ITS) and control center software development tools (CHIMES and STOL Certification Tool).

Numerical simulation of intelligent compaction technology for construction quality control.

DOT National Transportation Integrated Search

2015-02-01

For eciently updating models of large-scale structures, the response surface (RS) method based on radial basis : functions (RBFs) is proposed to model the input-output relationship of structures. The key issues for applying : the proposed method a...

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

NASA Astrophysics Data System (ADS)

Simon, Solomon H.

1992-08-01

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

OFMspert: An architecture for an operator's associate that evolves to an intelligent tutor

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1991-01-01

With the emergence of new technology for both human-computer interaction and knowledge-based systems, a range of opportunities exist which enhance the effectiveness and efficiency of controllers of high-risk engineering systems. The design of an architecture for an operator's associate is described. This associate is a stand-alone model-based system designed to interact with operators of complex dynamic systems, such as airplanes, manned space systems, and satellite ground control systems in ways comparable to that of a human assistant. The operator function model expert system (OFMspert) architecture and the design and empirical validation of OFMspert's understanding component are described. The design and validation of OFMspert's interactive and control components are also described. A description of current work in which OFMspert provides the foundation in the development of an intelligent tutor that evolves to an assistant, as operator expertise evolves from novice to expert, is provided.

Exploring rationality in schizophrenia.

PubMed

Revsbech, Rasmus; Mortensen, Erik Lykke; Owen, Gareth; Nordgaard, Julie; Jansson, Lennart; Sæbye, Ditte; Flensborg-Madsen, Trine; Parnas, Josef

2015-06-01

Empirical studies of rationality (syllogisms) in patients with schizophrenia have obtained different results. One study found that patients reason more logically if the syllogism is presented through an unusual content. To explore syllogism-based rationality in schizophrenia. Thirty-eight first-admitted patients with schizophrenia and 38 healthy controls solved 29 syllogisms that varied in presentation content (ordinary v. unusual) and validity (valid v. invalid). Statistical tests were made of unadjusted and adjusted group differences in models adjusting for intelligence and neuropsychological test performance. Controls outperformed patients on all syllogism types, but the difference between the two groups was only significant for valid syllogisms presented with unusual content. However, when adjusting for intelligence and neuropsychological test performance, all group differences became non-significant. When taking intelligence and neuropsychological performance into account, patients with schizophrenia and controls perform similarly on syllogism tests of rationality. None. © The Royal College of Psychiatrists 2015. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

PubMed

Guikema, Seth

2012-07-01

Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

F-15 Intelligent Flight Control System and Aeronautics Research at NASA Dryden

NASA Technical Reports Server (NTRS)

Brown, Nelson A.

2009-01-01

This viewgraph presentation reviews the F-15 Intelligent Flight Control System and Aeronautics including Autonomous Aerial Refueling Demonstrations, X-48B Blended Wing Body, F-15 Quiet Spike, and NF-15 Intelligent Flight Controls.

Intelligent Engine Systems: Thermal Management and Advanced Cooling

NASA Technical Reports Server (NTRS)

Bergholz, Robert

2008-01-01

The objective of the Advanced Turbine Cooling and Thermal Management program is to develop intelligent control and distribution methods for turbine cooling, while achieving a reduction in total cooling flow and assuring acceptable turbine component safety and reliability. The program also will develop embedded sensor technologies and cooling system models for real-time engine diagnostics and health management. Both active and passive control strategies will be investigated that include the capability of intelligent modulation of flow quantities, pressures, and temperatures both within the supply system and at the turbine component level. Thermal management system concepts were studied, with a goal of reducing HPT blade cooling air supply temperature. An assessment will be made of the use of this air by the active clearance control system as well. Turbine component cooling designs incorporating advanced, high-effectiveness cooling features, will be evaluated. Turbine cooling flow control concepts will be studied at the cooling system level and the component level. Specific cooling features or sub-elements of an advanced HPT blade cooling design will be downselected for core fabrication and casting demonstrations.

A conceptual framework for intelligent real-time information processing

NASA Technical Reports Server (NTRS)

Schudy, Robert

1987-01-01

By combining artificial intelligence concepts with the human information processing model of Rasmussen, a conceptual framework was developed for real time artificial intelligence systems which provides a foundation for system organization, control and validation. The approach is based on the description of system processing terms of an abstraction hierarchy of states of knowledge. The states of knowledge are organized along one dimension which corresponds to the extent to which the concepts are expressed in terms of the system inouts or in terms of the system response. Thus organized, the useful states form a generally triangular shape with the sensors and effectors forming the lower two vertices and the full evaluated set of courses of action the apex. Within the triangle boundaries are numerous processing paths which shortcut the detailed processing, by connecting incomplete levels of analysis to partially defined responses. Shortcuts at different levels of abstraction include reflexes, sensory motor control, rule based behavior, and satisficing. This approach was used in the design of a real time tactical decision aiding system, and in defining an intelligent aiding system for transport pilots.

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

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

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

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.

Demonstrating artificial intelligence for space systems - Integration and project management issues

NASA Technical Reports Server (NTRS)

Hack, Edmund C.; Difilippo, Denise M.

1990-01-01

As part of its Systems Autonomy Demonstration Project (SADP), NASA has recently demonstrated the Thermal Expert System (TEXSYS). Advanced real-time expert system and human interface technology was successfully developed and integrated with conventional controllers of prototype space hardware to provide intelligent fault detection, isolation, and recovery capability. Many specialized skills were required, and responsibility for the various phases of the project therefore spanned multiple NASA centers, internal departments and contractor organizations. The test environment required communication among many types of hardware and software as well as between many people. The integration, testing, and configuration management tools and methodologies which were applied to the TEXSYS project to assure its safe and successful completion are detailed. The project demonstrated that artificial intelligence technology, including model-based reasoning, is capable of the monitoring and control of a large, complex system in real time.

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

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor)

1990-01-01

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

Development of a Framework for Model-Based Analysis, Uncertainty Quantification, and Robust Control Design of Nonlinear Smart Composite Systems

DTIC Science & Technology

2015-06-04

control, vibration and noise control, health monitoring, and energy harvesting . However, these advantages come at the cost of rate-dependent hysteresis...configuration used for energy harvesting . Uncertainty Quantification Uncertainty quantification is pursued in two steps: (i) determination of densities...Crews and R.C. Smith, “Quantification of parameter and model uncertainty for shape mem- ory alloy bending actuators,” Journal of Intelligent material

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

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.

Emotional intelligence in patients with posttraumatic stress disorder, borderline personality disorder and healthy controls.

PubMed

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.

A Boltzmann machine for the organization of intelligent machines

NASA Technical Reports Server (NTRS)

Moed, Michael C.; Saridis, George N.

1990-01-01

A three-tier structure consisting of organization, coordination, and execution levels forms the architecture of an intelligent machine using the principle of increasing precision with decreasing intelligence from a hierarchically intelligent control. This system has been formulated as a probabilistic model, where uncertainty and imprecision can be expressed in terms of entropies. The optimal strategy for decision planning and task execution can be found by minimizing the total entropy in the system. The focus is on the design of the organization level as a Boltzmann machine. Since this level is responsible for planning the actions of the machine, the Boltzmann machine is reformulated to use entropy as the cost function to be minimized. Simulated annealing, expanding subinterval random search, and the genetic algorithm are presented as search techniques to efficiently find the desired action sequence and illustrated with numerical examples.

Experimentation of cooperative learning model Numbered Heads Together (NHT) type by concept maps and Teams Games Tournament (TGT) by concept maps in terms of students logical mathematics intellegences

NASA Astrophysics Data System (ADS)

Irawan, Adi; Mardiyana; Retno Sari Saputro, Dewi

2017-06-01

This research is aimed to find out the effect of learning model towards learning achievement in terms of students’ logical mathematics intelligences. The learning models that were compared were NHT by Concept Maps, TGT by Concept Maps, and Direct Learning model. This research was pseudo experimental by factorial design 3×3. The population of this research was all of the students of class XI Natural Sciences of Senior High School in all regency of Karanganyar in academic year 2016/2017. The conclusions of this research were: 1) the students’ achievements with NHT learning model by Concept Maps were better than students’ achievements with TGT model by Concept Maps and Direct Learning model. The students’ achievements with TGT model by Concept Maps were better than the students’ achievements with Direct Learning model. 2) The students’ achievements that exposed high logical mathematics intelligences were better than students’ medium and low logical mathematics intelligences. The students’ achievements that exposed medium logical mathematics intelligences were better than the students’ low logical mathematics intelligences. 3) Each of student logical mathematics intelligences with NHT learning model by Concept Maps has better achievement than students with TGT learning model by Concept Maps, students with NHT learning model by Concept Maps have better achievement than students with the direct learning model, and the students with TGT by Concept Maps learning model have better achievement than students with Direct Learning model. 4) Each of learning model, students who have logical mathematics intelligences have better achievement then students who have medium logical mathematics intelligences, and students who have medium logical mathematics intelligences have better achievement than students who have low logical mathematics intelligences.

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

DOE PAGES

Gonder, Jeffrey; Wood, Eric; Rajagopalan, Sai

2016-01-01

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

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

PubMed

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

2012-01-01

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

White matter tract integrity and intelligence in patients with mental retardation and healthy adults.

PubMed

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.

IMIS: An intelligence microscope imaging system

NASA Technical Reports Server (NTRS)

Caputo, Michael; Hunter, Norwood; Taylor, Gerald

1994-01-01

Until recently microscope users in space relied on traditional microscopy techniques that required manual operation of the microscope and recording of observations in the form of written notes, drawings, or photographs. This method was time consuming and required the return of film and drawings from space for analysis. No real-time data analysis was possible. Advances in digital and video technologies along with recent developments in article intelligence will allow future space microscopists to have a choice of three additional modes of microscopy: remote coaching, remote control, and automation. Remote coaching requires manual operations of the microscope with instructions given by two-way audio/video transmission during critical phases of the experiment. When using the remote mode of microscopy, the Principal Investigator controls the microscope from the ground. The automated mode employs artificial intelligence to control microscope functions and is the only mode that can be operated in the other three modes as well. The purpose of this presentation is to discuss the advantages and disadvantages of the four modes of of microscopy and how the IMIS, a proposed intelligent microscope imaging system, can be used as a model for developing and testing concepts, operating procedures, and equipment design of specifications required to provide a comprehensive microscopy/imaging capability onboard Space Station Freedom.

Autonomous vehicles: from paradigms to technology

NASA Astrophysics Data System (ADS)

Ionita, Silviu

2017-10-01

Mobility is a basic necessity of contemporary society and it is a key factor in global economic development. The basic requirements for the transport of people and goods are: safety and duration of travel, but also a number of additional criteria are very important: energy saving, pollution, passenger comfort. Due to advances in hardware and software, automation has penetrated massively in transport systems both on infrastructure and on vehicles, but man is still the key element in vehicle driving. However, the classic concept of ‘human-in-the-loop’ in terms of ‘hands on’ in driving the cars is competing aside from the self-driving startups working towards so-called ‘Level 4 autonomy’, which is defined as “a self-driving system that does not requires human intervention in most scenarios”. In this paper, a conceptual synthesis of the autonomous vehicle issue is made in connection with the artificial intelligence paradigm. It presents a classification of the tasks that take place during the driving of the vehicle and its modeling from the perspective of traditional control engineering and artificial intelligence. The issue of autonomous vehicle management is addressed on three levels: navigation, movement in traffic, respectively effective maneuver and vehicle dynamics control. Each level is then described in terms of specific tasks, such as: route selection, planning and reconfiguration, recognition of traffic signs and reaction to signaling and traffic events, as well as control of effective speed, distance and direction. The approach will lead to a better understanding of the way technology is moving when talking about autonomous cars, smart/intelligent cars or intelligent transport systems. Keywords: self-driving vehicle, artificial intelligence, deep learning, intelligent transport systems.

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

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

Analytical studies on the instabilities of heterogeneous intelligent traffic flow

NASA Astrophysics Data System (ADS)

Ngoduy, D.

2013-10-01

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

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.

User modeling for distributed virtual environment intelligent agents

NASA Astrophysics Data System (ADS)

Banks, Sheila B.; Stytz, Martin R.

1999-07-01

This paper emphasizes the requirement for user modeling by presenting the necessary information to motivate the need for and use of user modeling for intelligent agent development. The paper will present information on our current intelligent agent development program, the Symbiotic Information Reasoning and Decision Support (SIRDS) project. We then discuss the areas of intelligent agents and user modeling, which form the foundation of the SIRDS project. Included in the discussion of user modeling are its major components, which are cognitive modeling and behavioral modeling. We next motivate the need for and user of a methodology to develop user models to encompass work within cognitive task analysis. We close the paper by drawing conclusions from our current intelligent agent research project and discuss avenues of future research in the utilization of user modeling for the development of intelligent agents for virtual environments.

The NASA F-15 Intelligent Flight Control Systems: Generation II

NASA Technical Reports Server (NTRS)

Buschbacher, Mark; Bosworth, John

2006-01-01

The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

An intelligent emissions controller for fuel lean gas reburn in coal-fired power plants.

PubMed

Reifman, J; Feldman, E E; Wei, T Y; Glickert, R W

2000-02-01

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NOx) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NOx reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach. Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NOx emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.

Autonomous Mission Operations for Sensor Webs

NASA Astrophysics Data System (ADS)

Underbrink, A.; Witt, K.; Stanley, J.; Mandl, D.

2008-12-01

We present interim results of a 2005 ROSES AIST project entitled, "Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations", or SWAMO. The goal of the SWAMO project is to shift the control of spacecraft missions from a ground-based, centrally controlled architecture to a collaborative, distributed set of intelligent agents. The network of intelligent agents intends to reduce management requirements by utilizing model-based system prediction and autonomic model/agent collaboration. SWAMO agents are distributed throughout the Sensor Web environment, which may include multiple spacecraft, aircraft, ground systems, and ocean systems, as well as manned operations centers. The agents monitor and manage sensor platforms, Earth sensing systems, and Earth sensing models and processes. The SWAMO agents form a Sensor Web of agents via peer-to-peer coordination. Some of the intelligent agents are mobile and able to traverse between on-orbit and ground-based systems. Other agents in the network are responsible for encapsulating system models to perform prediction of future behavior of the modeled subsystems and components to which they are assigned. The software agents use semantic web technologies to enable improved information sharing among the operational entities of the Sensor Web. The semantics include ontological conceptualizations of the Sensor Web environment, plus conceptualizations of the SWAMO agents themselves. By conceptualizations of the agents, we mean knowledge of their state, operational capabilities, current operational capacities, Web Service search and discovery results, agent collaboration rules, etc. The need for ontological conceptualizations over the agents is to enable autonomous and autonomic operations of the Sensor Web. The SWAMO ontology enables automated decision making and responses to the dynamic Sensor Web environment and to end user science requests. The current ontology is compatible with Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) Sensor Model Language (SensorML) concepts and structures. The agents are currently deployed on the U.S. Naval Academy MidSTAR-1 satellite and are actively managing the power subsystem on-orbit without the need for human intervention.

Modernization (Selected Articles),

DTIC Science & Technology

1986-09-18

newly developed science such as control theory, artificial intelligence, model identification, computer and microelectronics technology, graphic...five "top guns" from around the country specializing in intellignece , mechanics, software and hardware as our technical advisors. In addition

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.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

A human performance modelling approach to intelligent decision support systems

NASA Technical Reports Server (NTRS)

Mccoy, Michael S.; Boys, Randy M.

1987-01-01

Manned space operations require that the many automated subsystems of a space platform be controllable by a limited number of personnel. To minimize the interaction required of these operators, artificial intelligence techniques may be applied to embed a human performance model within the automated, or semi-automated, systems, thereby allowing the derivation of operator intent. A similar application has previously been proposed in the domain of fighter piloting, where the demand for pilot intent derivation is primarily a function of limited time and high workload rather than limited operators. The derivation and propagation of pilot intent is presented as it might be applied to some programs.

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...

Acting to gain information: Real-time reasoning meets real-time perception

NASA Technical Reports Server (NTRS)

Rosenschein, Stan

1994-01-01

Recent advances in intelligent reactive systems suggest new approaches to the problem of deriving task-relevant information from perceptual systems in real time. The author will describe work in progress aimed at coupling intelligent control mechanisms to real-time perception systems, with special emphasis on frame rate visual measurement systems. A model for integrated reasoning and perception will be discussed, and recent progress in applying these ideas to problems of sensor utilization for efficient recognition and tracking will be described.

Aspects of intelligent electronic device based switchgear control training model application

NASA Astrophysics Data System (ADS)

Bogdanov, Dimitar; Popov, Ivaylo

2018-02-01

The design of the protection and control equipment for electrical power sector application was object of extensive advance in the last several decades. The modern technologies offer a wide range of multifunctional flexible applications, making the protection and control of facilities more sophisticated. In the same time, the advance of technology imposes the necessity of simulators, training models and tutorial laboratory equipment to be used for adequate training of students and field specialists

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.

Experimental Study of Flexible Plate Vibration Control by Using Two-Loop Sliding Mode Control Strategy

NASA Astrophysics Data System (ADS)

Yang, Jingyu; Lin, Jiahui; Liu, Yuejun; Yang, Kang; Zhou, Lanwei; Chen, Guoping

2017-08-01

It is well known that intelligent control theory has been used in many research fields, novel modeling method (DROMM) is used for flexible rectangular active vibration control, and then the validity of new model is confirmed by comparing finite element model with new model. In this paper, taking advantage of the dynamics of flexible rectangular plate, a two-loop sliding mode (TSM) MIMO approach is introduced for designing multiple-input multiple-output continuous vibration control system, which can overcome uncertainties, disturbances or unstable dynamics. An illustrative example is given in order to show the feasibility of the method. Numerical simulations and experiment confirm the effectiveness of the proposed TSM MIMO controller.

Intelligence rules of hysteresis in the feedforward trajectory control of piezoelectrically-driven nanostagers

NASA Astrophysics Data System (ADS)

Bashash, Saeid; Jalili, Nader

2007-02-01

Piezoelectrically-driven nanostagers have limited performance in a variety of feedforward and feedback positioning applications because of their nonlinear hysteretic response to input voltage. The hysteresis phenomenon is well known for its complex and multi-path behavior. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligence properties of hysteresis with the effects of non-local memories are discussed here. Through performing a set of experiments on a piezoelectrically-driven nanostager with a high resolution capacitive position sensor, it is shown that for the precise prediction of the hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of the hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the ever-present nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect, if memory units are sufficiently chosen for the inverse model.

Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report.

PubMed

Fu, Jicheng; Jones, Maria; Jan, Yih-Kuen

2014-01-01

Wheelchair tilt and recline functions are two of the most desirable features for relieving seating pressure to decrease the risk of pressure ulcers. The effective guidance on wheelchair tilt and recline usage is therefore critical to pressure ulcer prevention. The aim of this study was to demonstrate the feasibility of using machine learning techniques to construct an intelligent model to provide personalized guidance to individuals with spinal cord injury (SCI). The motivation stems from the clinical evidence that the requirements of individuals vary greatly and that no universal guidance on tilt and recline usage could possibly satisfy all individuals with SCI. We explored all aspects involved in constructing the intelligent model and proposed approaches tailored to suit the characteristics of this preliminary study, such as the way of modeling research participants, using machine learning techniques to construct the intelligent model, and evaluating the performance of the intelligent model. We further improved the intelligent model's prediction accuracy by developing a two-phase feature selection algorithm to identify important attributes. Experimental results demonstrated that our approaches held the promise: they could effectively construct the intelligent model, evaluate its performance, and refine the participant model so that the intelligent model's prediction accuracy was significantly improved.

Relationship between speech motor control and speech intelligibility in children with speech sound disorders.

PubMed

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.

Operator function modeling: Cognitive task analysis, modeling and intelligent aiding in supervisory control systems

NASA Technical Reports Server (NTRS)

Mitchell, Christine M.

1990-01-01

The design, implementation, and empirical evaluation of task-analytic models and intelligent aids for operators in the control of complex dynamic systems, specifically aerospace systems, are studied. Three related activities are included: (1) the models of operator decision making in complex and predominantly automated space systems were used and developed; (2) the Operator Function Model (OFM) was used to represent operator activities; and (3) Operator Function Model Expert System (OFMspert), a stand-alone knowledge-based system was developed, that interacts with a human operator in a manner similar to a human assistant in the control of aerospace systems. OFMspert is an architecture for an operator's assistant that uses the OFM as its system and operator knowledge base and a blackboard paradigm of problem solving to dynamically generate expectations about upcoming operator activities and interpreting actual operator actions. An experiment validated the OFMspert's intent inferencing capability and showed that it inferred the intentions of operators in ways comparable to both a human expert and operators themselves. OFMspert was also augmented with control capabilities. An interface allowed the operator to interact with OFMspert, delegating as much or as little control responsibility as the operator chose. With its design based on the OFM, OFMspert's control capabilities were available at multiple levels of abstraction and allowed the operator a great deal of discretion over the amount and level of delegated control. An experiment showed that overall system performance was comparable for teams consisting of two human operators versus a human operator and OFMspert team.

[Intelligence level and intelligence structure of children with primary nocturnal enuresis].

PubMed

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.

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.

Hybrid intelligent control of substrate feeding for industrial fed-batch chlortetracycline fermentation process.

PubMed

Jin, Huaiping; Chen, Xiangguang; Yang, Jianwen; Wu, Lei; Wang, Li

2014-11-01

The lack of accurate process models and reliable online sensors for substrate measurements poses significant challenges for controlling substrate feeding accurately, automatically and optimally in fed-batch fermentation industries. It is still a common practice to regulate the feeding rate based upon manual operations. To address this issue, a hybrid intelligent control method is proposed to enable automatic substrate feeding. The resulting control system consists of three modules: a presetting module for providing initial set-points; a predictive module for estimating substrate concentration online based on a new time interval-varying soft sensing algorithm; and a feedback compensator using expert rules. The effectiveness of the proposed approach is demonstrated through its successful applications to the industrial fed-batch chlortetracycline fermentation process. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Exploring rationality in schizophrenia

PubMed Central

Mortensen, Erik Lykke; Owen, Gareth; Nordgaard, Julie; Jansson, Lennart; Sæbye, Ditte; Flensborg-Madsen, Trine; Parnas, Josef

2015-01-01

Background Empirical studies of rationality (syllogisms) in patients with schizophrenia have obtained different results. One study found that patients reason more logically if the syllogism is presented through an unusual content. Aims To explore syllogism-based rationality in schizophrenia. Method Thirty-eight first-admitted patients with schizophrenia and 38 healthy controls solved 29 syllogisms that varied in presentation content (ordinary v. unusual) and validity (valid v. invalid). Statistical tests were made of unadjusted and adjusted group differences in models adjusting for intelligence and neuropsychological test performance. Results Controls outperformed patients on all syllogism types, but the difference between the two groups was only significant for valid syllogisms presented with unusual content. However, when adjusting for intelligence and neuropsychological test performance, all group differences became non-significant. Conclusions When taking intelligence and neuropsychological performance into account, patients with schizophrenia and controls perform similarly on syllogism tests of rationality. Declaration of interest None. Copyright and usage © The Royal College of Psychiatrists 2015. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence. PMID:27703730

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.

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.

Healthcare Data Gateways: Found Healthcare Intelligence on Blockchain with Novel Privacy Risk Control.

PubMed

Yue, Xiao; Wang, Huiju; Jin, Dawei; Li, Mingqiang; Jiang, Wei

2016-10-01

Healthcare data are a valuable source of healthcare intelligence. Sharing of healthcare data is one essential step to make healthcare system smarter and improve the quality of healthcare service. Healthcare data, one personal asset of patient, should be owned and controlled by patient, instead of being scattered in different healthcare systems, which prevents data sharing and puts patient privacy at risks. Blockchain is demonstrated in the financial field that trusted, auditable computing is possible using a decentralized network of peers accompanied by a public ledger. In this paper, we proposed an App (called Healthcare Data Gateway (HGD)) architecture based on blockchain to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private. Our proposed purpose-centric access model ensures patient own and control their healthcare data; simple unified Indicator-Centric Schema (ICS) makes it possible to organize all kinds of personal healthcare data practically and easily. We also point out that MPC (Secure Multi-Party Computing) is one promising solution to enable untrusted third-party to conduct computation over patient data without violating privacy.

Affordable and personalized lighting using inverse modeling and virtual sensors

NASA Astrophysics Data System (ADS)

Basu, Chandrayee; Chen, Benjamin; Richards, Jacob; Dhinakaran, Aparna; Agogino, Alice; Martin, Rodney

2014-03-01

Wireless sensor networks (WSN) have great potential to enable personalized intelligent lighting systems while reducing building energy use by 50%-70%. As a result WSN systems are being increasingly integrated in state-ofart intelligent lighting systems. In the future these systems will enable participation of lighting loads as ancillary services. However, such systems can be expensive to install and lack the plug-and-play quality necessary for user-friendly commissioning. In this paper we present an integrated system of wireless sensor platforms and modeling software to enable affordable and user-friendly intelligent lighting. It requires ⇠ 60% fewer sensor deployments compared to current commercial systems. Reduction in sensor deployments has been achieved by optimally replacing the actual photo-sensors with real-time discrete predictive inverse models. Spatially sparse and clustered sub-hourly photo-sensor data captured by the WSN platforms are used to develop and validate a piece-wise linear regression of indoor light distribution. This deterministic data-driven model accounts for sky conditions and solar position. The optimal placement of photo-sensors is performed iteratively to achieve the best predictability of the light field desired for indoor lighting control. Using two weeks of daylight and artificial light training data acquired at the Sustainability Base at NASA Ames, the model was able to predict the light level at seven monitored workstations with 80%-95% accuracy. We estimate that 10% adoption of this intelligent wireless sensor system in commercial buildings could save 0.2-0.25 quads BTU of energy nationwide.

The evolution of primate general and cultural intelligence

PubMed Central

Reader, Simon M.; Hager, Yfke; Laland, Kevin N.

2011-01-01

There are consistent individual differences in human intelligence, attributable to a single ‘general intelligence’ factor, g. The evolutionary basis of g and its links to social learning and culture remain controversial. Conflicting hypotheses regard primate cognition as divided into specialized, independently evolving modules versus a single general process. To assess how processes underlying culture relate to one another and other cognitive capacities, we compiled ecologically relevant cognitive measures from multiple domains, namely reported incidences of behavioural innovation, social learning, tool use, extractive foraging and tactical deception, in 62 primate species. All exhibited strong positive associations in principal component and factor analyses, after statistically controlling for multiple potential confounds. This highly correlated composite of cognitive traits suggests social, technical and ecological abilities have coevolved in primates, indicative of an across-species general intelligence that includes elements of cultural intelligence. Our composite species-level measure of general intelligence, ‘primate gS’, covaried with both brain volume and captive learning performance measures. Our findings question the independence of cognitive traits and do not support ‘massive modularity’ in primate cognition, nor an exclusively social model of primate intelligence. High general intelligence has independently evolved at least four times, with convergent evolution in capuchins, baboons, macaques and great apes. PMID:21357224

Student Modeling in an Intelligent Tutoring System

DTIC Science & Technology

1996-12-17

Multi-Agent Architecture." Advances in Artificial Intelligence : Proceedings of the 12 th Brazilian Symposium on Aritificial Intelligence , edited by...STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D-27 DIMTVMON* fCKAJWINT A Appr"v*d t=i...Air Force Base, Ohio AFIT/GCS/ENG/96D-27 STUDENT MODELING IN AN INTELLIGENT TUTORING SYSTEM THESIS Jeremy E. Thompson Captain, USAF AFIT/GCS/ENG/96D

Reading and spelling skills in German third graders: Examining the role of student and context characteristics.

PubMed

von Suchodoletz, Antje; Larsen, Ross A A; Gunzenhauser, Catherine; Fäsche, Anika

2015-12-01

Educational processes and outcomes are influenced by a multitude of factors, including individual and contextual characteristics. Recently, studies have demonstrated that student and context characteristics may produce unique and cumulative effects on educational outcomes. The study aimed to investigate (1) the relative contribution of student, classroom, and school characteristics to reading fluency and orthographic spelling, (2) the relative contribution of specific predictors to reading fluency and orthographic spelling within the sets of student, classroom, and school characteristics, and (3) whether the contribution of student, classroom, and school characteristics differs for reading fluency and orthographic spelling. Participants were 789 German third-grade students from 56 classrooms in 34 schools. Students completed an intelligence test and a questionnaire assessing self-control. Reading fluency and orthographic spelling performance were assessed using standardized achievement tests. Multilevel structural equation modelling was used to control for the hierarchical structure of educational data. Variances in students' reading and spelling skills were in large part explained by student characteristics (>90%). Classroom and school characteristics yielded little variance. Student-level intelligence and self-control were significantly related to reading fluency. For orthographic spelling, student-level intelligence and self-control, class-average intelligence, and, at the school level, the socio-economic status of the school's neighbourhood were significant predictors. Future research needs to investigate relevant classroom and school factors that may directly and indirectly relate to academic outcomes. © 2015 The British Psychological Society.

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...

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

NASA Astrophysics Data System (ADS)

Zarchi, Milad; Attaran, Behrooz

2017-11-01

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

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.

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.

High pressure common rail injection system modeling and control.

PubMed

Wang, H P; Zheng, D; Tian, Y

2016-07-01

In this paper modeling and common-rail pressure control of high pressure common rail injection system (HPCRIS) is presented. The proposed mathematical model of high pressure common rail injection system which contains three sub-systems: high pressure pump sub-model, common rail sub-model and injector sub-model is a relative complicated nonlinear system. The mathematical model is validated by the software Matlab and a virtual detailed simulation environment. For the considered HPCRIS, an effective model free controller which is called Extended State Observer - based intelligent Proportional Integral (ESO-based iPI) controller is designed. And this proposed method is composed mainly of the referred ESO observer, and a time delay estimation based iPI controller. Finally, to demonstrate the performances of the proposed controller, the proposed ESO-based iPI controller is compared with a conventional PID controller and ADRC. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The relationship between executive functions and fluid intelligence in Parkinson's disease

PubMed Central

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.

Use of artificial intelligence to identify cardiovascular compromise in a model of hemorrhagic shock.

PubMed

Glass, Todd F; Knapp, Jason; Amburn, Philip; Clay, Bruce A; Kabrisky, Matt; Rogers, Steven K; Garcia, Victor F

2004-02-01

To determine whether a prototype artificial intelligence system can identify volume of hemorrhage in a porcine model of controlled hemorrhagic shock. Prospective in vivo animal model of hemorrhagic shock. Research foundation animal surgical suite; computer laboratories of collaborating industry partner. Nineteen, juvenile, 25- to 35-kg, male and female swine. Anesthetized animals were instrumented for arterial and systemic venous pressure monitoring and blood sampling, and a splenectomy was performed. Following a 1-hr stabilization period, animals were hemorrhaged in aliquots to 10, 20, 30, 35, 40, 45, and 50% of total blood volume with a 10-min recovery between each aliquot. Data were downloaded directly from a commercial monitoring system into a proprietary PC-based software package for analysis. Arterial and venous blood gas values, glucose, and cardiac output were collected at specified intervals. Electrocardiogram, electroencephalogram, mixed venous oxygen saturation, temperature (core and blood), mean arterial pressure, pulmonary artery pressure, central venous pressure, pulse oximetry, and end-tidal CO(2) were continuously monitored and downloaded. Seventeen of 19 animals (89%) died as a direct result of hemorrhage. Stored data streams were analyzed by the prototype artificial intelligence system. For this project, the artificial intelligence system identified and compared three electrocardiographic features (R-R interval, QRS amplitude, and R-S interval) from each of nine unknown samples of the QRS complex. We found that the artificial intelligence system, trained on only three electrocardiographic features, identified hemorrhage volume with an average accuracy of 91% (95% confidence interval, 84-96%). These experiments demonstrate that an artificial intelligence system, based solely on the analysis of QRS amplitude, R-R interval, and R-S interval of an electrocardiogram, is able to accurately identify hemorrhage volume in a porcine model of lethal hemorrhagic shock. We suggest that this technology may represent a noninvasive means of assessing the physiologic state during and immediately following hemorrhage. Point of care application of this technology may improve outcomes with earlier diagnosis and better titration of therapy of shock.

Ortho Image and DTM Generation with Intelligent Methods

NASA Astrophysics Data System (ADS)

Bagheri, H.; Sadeghian, S.

2013-10-01

Nowadays the artificial intelligent algorithms has considered in GIS and remote sensing. Genetic algorithm and artificial neural network are two intelligent methods that are used for optimizing of image processing programs such as edge extraction and etc. these algorithms are very useful for solving of complex program. In this paper, the ability and application of genetic algorithm and artificial neural network in geospatial production process like geometric modelling of satellite images for ortho photo generation and height interpolation in raster Digital Terrain Model production process is discussed. In first, the geometric potential of Ikonos-2 and Worldview-2 with rational functions, 2D & 3D polynomials were tested. Also comprehensive experiments have been carried out to evaluate the viability of the genetic algorithm for optimization of rational function, 2D & 3D polynomials. Considering the quality of Ground Control Points, the accuracy (RMSE) with genetic algorithm and 3D polynomials method for Ikonos-2 Geo image was 0.508 pixel sizes and the accuracy (RMSE) with GA algorithm and rational function method for Worldview-2 image was 0.930 pixel sizes. For more another optimization artificial intelligent methods, neural networks were used. With the use of perceptron network in Worldview-2 image, a result of 0.84 pixel sizes with 4 neurons in middle layer was gained. The final conclusion was that with artificial intelligent algorithms it is possible to optimize the existing models and have better results than usual ones. Finally the artificial intelligence methods, like genetic algorithms as well as neural networks, were examined on sample data for optimizing interpolation and for generating Digital Terrain Models. The results then were compared with existing conventional methods and it appeared that these methods have a high capacity in heights interpolation and that using these networks for interpolating and optimizing the weighting methods based on inverse distance leads to a high accurate estimation of heights.

Organisational Intelligence

ERIC Educational Resources Information Center

Yolles, Maurice

2005-01-01

Purpose: Seeks to explore the notion of organisational intelligence as a simple extension of the notion of the idea of collective intelligence. Design/methodology/approach: Discusses organisational intelligence using previous research, which includes the Purpose, Properties and Practice model of Dealtry, and the Viable Systems model. Findings: The…

A logical model of cooperating rule-based systems

NASA Technical Reports Server (NTRS)

Bailin, Sidney C.; Moore, John M.; Hilberg, Robert H.; Murphy, Elizabeth D.; Bahder, Shari A.

1989-01-01

A model is developed to assist in the planning, specification, development, and verification of space information systems involving distributed rule-based systems. The model is based on an analysis of possible uses of rule-based systems in control centers. This analysis is summarized as a data-flow model for a hypothetical intelligent control center. From this data-flow model, the logical model of cooperating rule-based systems is extracted. This model consists of four layers of increasing capability: (1) communicating agents, (2) belief-sharing knowledge sources, (3) goal-sharing interest areas, and (4) task-sharing job roles.

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.

Self-Learning Intelligent Agents for Dynamic Traffic Routing on Transportation Networks

NASA Astrophysics Data System (ADS)

Sadek, Add; Basha, Nagi

Intelligent Transportation Systems (ITS) are designed to take advantage of recent advances in communications, electronics, and Information Technology in improving the efficiency and safety of transportation systems. Among the several ITS applications is the notion of Dynamic Traffic Routing (DTR), which involves generating "optimal" routing recommendations to drivers with the aim of maximizing network utilizing. In this paper, we demonstrate the feasibility of using a self-learning intelligent agent to solve the DTR problem to achieve traffic user equilibrium in a transportation network. The core idea is to deploy an agent to a simulation model of a highway. The agent then learns by itself by interacting with the simulation model. Once the agent reaches a satisfactory level of performance, it can then be deployed to the real-world, where it would continue to learn how to refine its control policies over time. To test this concept in this paper, the Cell Transmission Model (CTM) developed by Carlos Daganzo of the University of California at Berkeley is used to simulate a simple highway with two main alternative routes. With the model developed, a Reinforcement Learning Agent (RLA) is developed to learn how to best dynamically route traffic, so as to maximize the utilization of existing capacity. Preliminary results obtained from our experiments are promising. RL, being an adaptive online learning technique, appears to have a great potential for controlling a stochastic dynamic systems such as a transportation system. Furthermore, the approach is highly scalable and applicable to a variety of networks and roadways.

Linear quadratic servo control of a reusable rocket engine

NASA Technical Reports Server (NTRS)

Musgrave, Jeffrey L.

1991-01-01

A design method for a servo compensator is developed in the frequency domain using singular values. The method is applied to a reusable rocket engine. An intelligent control system for reusable rocket engines was proposed which includes a diagnostic system, a control system, and an intelligent coordinator which determines engine control strategies based on the identified failure modes. The method provides a means of generating various linear multivariable controllers capable of meeting performance and robustness specifications and accommodating failure modes identified by the diagnostic system. Command following with set point control is necessary for engine operation. A Kalman filter reconstructs the state while loop transfer recovery recovers the required degree of robustness while maintaining satisfactory rejection of sensor noise from the command error. The approach is applied to the design of a controller for a rocket engine satisfying performance constraints in the frequency domain. Simulation results demonstrate the performance of the linear design on a nonlinear engine model over all power levels during mainstage operation.

LG tools for asymmetric wargaming

NASA Astrophysics Data System (ADS)

Stilman, Boris; Yakhnis, Alex; Yakhnis, Vladimir

2002-07-01

Asymmetric operations represent conflict where one of the sides would apply military power to influence the political and civil environment, to facilitate diplomacy, and to interrupt specified illegal activities. This is a special type of conflict where the participants do not initiate full-scale war. Instead, the sides may be engaged in a limited open conflict or one or several sides may covertly engage another side using unconventional or less conventional methods of engagement. They may include peace operations, combating terrorism, counterdrug operations, arms control, support of insurgencies or counterinsurgencies, show of force. An asymmetric conflict can be represented as several concurrent interlinked games of various kinds: military, transportation, economic, political, etc. Thus, various actions of peace violators, terrorists, drug traffickers, etc., can be expressed via moves in different interlinked games. LG tools allow us to fully capture the specificity of asymmetric conflicts employing the major LG concept of hypergame. Hypergame allows modeling concurrent interlinked processes taking place in geographically remote locations at different levels of resolution and time scale. For example, it allows us to model an antiterrorist operation taking place simultaneously in a number of countries around the globe and involving wide range of entities from individuals to combat units to governments. Additionally, LG allows us to model all sides of the conflict at their level of sophistication. Intelligent stakeholders are represented by means of LG generated intelligent strategies. TO generate those strategies, in addition to its own mathematical intelligence, the LG algorithm may incorporate the intelligence of the top-level experts in the respective problem domains. LG models the individual differences between intelligent stakeholders. The LG tools make it possible to incorporate most of the known traits of a stakeholder, i.e., real personalities involved in the conflict with their specific individual style.

Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

PubMed

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.

Social origin, schooling and individual change in intelligence during childhood influence long-term mortality: a 68-year follow-up study

PubMed Central

Lager, Anton CJ; Modin, Bitte E; De Stavola, Bianca L; Vågerö, Denny H

2012-01-01

Background Intelligence at a single time-point has been linked to health outcomes. An individual's IQ increases with longer schooling, but the validity of such increase is unclear. In this study, we assess the hypothesis that individual change in the performance on IQ tests between ages 10 and 20 years is associated with mortality later in life. Methods The analyses are based on a cohort of Swedish boys born in 1928 (n = 610) for whom social background data were collected in 1937, IQ tests were carried out in 1938 and 1948 and own education and mortality were recorded up to 2006. Structural equation models were used to estimate the extent to which two latent intelligence scores, at ages 10 and 20 years, manifested by results on the IQ tests, are related to paternal and own education, and how all these variables are linked to all-cause mortality. Results Intelligence at the age of 20 years was associated with lower mortality in adulthood, after controlling for intelligence at the age of 10 years. The increases in intelligence partly mediated the link between longer schooling and lower mortality. Social background differences in adult intelligence (and consequently in mortality) were partly explained by the tendency for sons of more educated fathers to receive longer schooling, even when initial intelligence levels had been accounted for. Conclusions The results are consistent with a causal link from change in intelligence to mortality, and further, that schooling-induced changes in IQ scores are true and bring about lasting changes in intelligence. In addition, if both these interpretations are correct, social differences in access to longer schooling have consequences for social differences in both adult intelligence and adult health. PMID:22493324

One Dimensional Turing-Like Handshake Test for Motor Intelligence

PubMed Central

Karniel, Amir; Avraham, Guy; Peles, Bat-Chen; Levy-Tzedek, Shelly; Nisky, Ilana

2010-01-01

In the Turing test, a computer model is deemed to "think intelligently" if it can generate answers that are not distinguishable from those of a human. However, this test is limited to the linguistic aspects of machine intelligence. A salient function of the brain is the control of movement, and the movement of the human hand is a sophisticated demonstration of this function. Therefore, we propose a Turing-like handshake test, for machine motor intelligence. We administer the test through a telerobotic system in which the interrogator is engaged in a task of holding a robotic stylus and interacting with another party (human or artificial). Instead of asking the interrogator whether the other party is a person or a computer program, we employ a two-alternative forced choice method and ask which of two systems is more human-like. We extract a quantitative grade for each model according to its resemblance to the human handshake motion and name it "Model Human-Likeness Grade" (MHLG). We present three methods to estimate the MHLG. (i) By calculating the proportion of subjects' answers that the model is more human-like than the human; (ii) By comparing two weighted sums of human and model handshakes we fit a psychometric curve and extract the point of subjective equality (PSE); (iii) By comparing a given model with a weighted sum of human and random signal, we fit a psychometric curve to the answers of the interrogator and extract the PSE for the weight of the human in the weighted sum. Altogether, we provide a protocol to test computational models of the human handshake. We believe that building a model is a necessary step in understanding any phenomenon and, in this case, in understanding the neural mechanisms responsible for the generation of the human handshake. PMID:21206462

Incorporating time and spatial-temporal reasoning into situation management

NASA Astrophysics Data System (ADS)

Jakobson, Gabriel

2010-04-01

Spatio-temporal reasoning plays a significant role in situation management that is performed by intelligent agents (human or machine) by affecting how the situations are recognized, interpreted, acted upon or predicted. Many definitions and formalisms for the notion of spatio-temporal reasoning have emerged in various research fields including psychology, economics and computer science (computational linguistics, data management, control theory, artificial intelligence and others). In this paper we examine the role of spatio-temporal reasoning in situation management, particularly how to resolve situations that are described by using spatio-temporal relations among events and situations. We discuss a model for describing context sensitive temporal relations and show have the model can be extended for spatial relations.

Computer Simulated Visual and Tactile Feedback as an Aid to Manipulator and Vehicle Control,

DTIC Science & Technology

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

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.

Qualitative Reasoning methods for CELSS modeling.

PubMed

Guerrin, F; Bousson, K; Steyer JPh; Trave-Massuyes, L

1994-11-01

Qualitative Reasoning (QR) is a branch of Artificial Intelligence that arose from research on engineering problem solving. This paper describes the major QR methods and techniques, which, we believe, are capable of addressing some of the problems that are emphasized in the literature and posed by CELSS modeling, simulation, and control at the supervisory level.

Recent progress in econophysics: Chaos, leverage, and business cycles as revealed by agent-based modeling and human experiments

NASA Astrophysics Data System (ADS)

Xin, Chen; Huang, Ji-Ping

2017-12-01

Agent-based modeling and controlled human experiments serve as two fundamental research methods in the field of econophysics. Agent-based modeling has been in development for over 20 years, but how to design virtual agents with high levels of human-like "intelligence" remains a challenge. On the other hand, experimental econophysics is an emerging field; however, there is a lack of experience and paradigms related to the field. Here, we review some of the most recent research results obtained through the use of these two methods concerning financial problems such as chaos, leverage, and business cycles. We also review the principles behind assessments of agents' intelligence levels, and some relevant designs for human experiments. The main theme of this review is to show that by combining theory, agent-based modeling, and controlled human experiments, one can garner more reliable and credible results on account of a better verification of theory; accordingly, this way, a wider range of economic and financial problems and phenomena can be studied.

Galen-In-Use: using artificial intelligence terminology tools to improve the linguistic coherence of a national coding system for surgical procedures.

PubMed

Rodrigues, J M; Trombert-Paviot, B; Baud, R; Wagner, J; Meusnier-Carriot, F

1998-01-01

GALEN has developed a language independent common reference model based on a medically oriented ontology and practical tools and techniques for managing healthcare terminology including natural language processing. GALEN-IN-USE is the current phase which applied the modelling and the tools to the development or the updating of coding systems for surgical procedures in different national coding centers co-operating within the European Federation of Coding Centre (EFCC) to create a language independent knowledge repository for multicultural Europe. We used an integrated set of artificial intelligence terminology tools named CLAssification Manager workbench to process French professional medical language rubrics into intermediate dissections and to the Grail reference ontology model representation. From this language independent concept model representation we generate controlled French natural language. The French national coding centre is then able to retrieve the initial professional rubrics with different categories of concepts, to compare the professional language proposed by expert clinicians to the French generated controlled vocabulary and to finalize the linguistic labels of the coding system in relation with the meanings of the conceptual system structure.

An Analysis of Student Model Portability

ERIC Educational Resources Information Center

Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict

2016-01-01

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…

Space Station Freedom ECLSS: A step toward autonomous regenerative life support systems

NASA Technical Reports Server (NTRS)

Dewberry, Brandon S.

1990-01-01

The Environmental Control and Life Support System (ECLSS) is a Freedom Station distributed system with inherent applicability to extensive automation primarily due to its comparatively long control system latencies. These allow longer contemplation times in which to form a more intelligent control strategy and to prevent and diagnose faults. The regenerative nature of the Space Station Freedom ECLSS will contribute closed loop complexities never before encountered in life support systems. A study to determine ECLSS automation approaches has been completed. The ECLSS baseline software and system processes could be augmented with more advanced fault management and regenerative control systems for a more autonomous evolutionary system, as well as serving as a firm foundation for future regenerative life support systems. Emerging advanced software technology and tools can be successfully applied to fault management, but a fully automated life support system will require research and development of regenerative control systems and models. The baseline Environmental Control and Life Support System utilizes ground tests in development of batch chemical and microbial control processes. Long duration regenerative life support systems will require more active chemical and microbial feedback control systems which, in turn, will require advancements in regenerative life support models and tools. These models can be verified using ground and on orbit life support test and operational data, and used in the engineering analysis of proposed intelligent instrumentation feedback and flexible process control technologies for future autonomous regenerative life support systems, including the evolutionary Space Station Freedom ECLSS.

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.

A coordination theory for intelligent machines

NASA Technical Reports Server (NTRS)

Wang, Fei-Yue; Saridis, George N.

1990-01-01

A formal model for the coordination level of intelligent machines is established. The framework of the coordination level investigated consists of one dispatcher and a number of coordinators. The model called coordination structure has been used to describe analytically the information structure and information flow for the coordination activities in the coordination level. Specifically, the coordination structure offers a formalism to (1) describe the task translation of the dispatcher and coordinators; (2) represent the individual process within the dispatcher and coordinators; (3) specify the cooperation and connection among the dispatcher and coordinators; (4) perform the process analysis and evaluation; and (5) provide a control and communication mechanism for the real-time monitor or simulation of the coordination process. A simple procedure for the task scheduling in the coordination structure is presented. The task translation is achieved by a stochastic learning algorithm. The learning process is measured with entropy and its convergence is guaranteed. Finally, a case study of the coordination structure with three coordinators and one dispatcher for a simple intelligent manipulator system illustrates the proposed model and the simulation of the task processes performed on the model verifies the soundness of the theory.

Addressing Diverse Learner Preferences and Intelligences with Emerging Technologies: Matching Models to Online Opportunities

ERIC Educational Resources Information Center

Zhang, Ke; Bonk, Curtis J.

2008-01-01

This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner's multiple intelligences, Fleming and Mills' VARK model, Honey and Mumford's Learning Styles, and Kolb's Experiential Learning Model, and…

Transforming Systems Engineering through Model-Centric Engineering

DTIC Science & Technology

2018-02-28

intelligence (e.g., Artificial Intelligence , etc.), because they provide a means for representing knowledge. We see these capabilities coming to use in both...level, including:  Performance is measured by degree of success of a mission  Artificial Intelligence (AI) is applied to counterparties so that they...Modeling, Artificial Intelligence , Simulation and Modeling, 1989. [140] SAE ARP4761. Guidelines and Methods for Conducting the Safety Assessment Process

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…

American British Canadian, Australian Armies Standardization Program Catalog of War Games

DTIC Science & Technology

1991-05-21

Defense Netwrrk (ADNET), Command, Control Communication, Intelligence, Prioritization (C3IP) Links, FM2 Grid (read-in optimization) in Terrain Database...at a given echelon such as division and below. Force level models may be interactive with players performing various cnmard, control , and staff...and may require compliance with appropriate configuration control procedures. Also, release to contractors may be prohibited. FOR THE WASHINGTON

The codification of spiritual intelligence measurement model in librarianship and medical information science students of medical universities in Iran

PubMed Central

Zarrinabadi, Zarrin; Isfandyari-Moghaddam, Alireza; Erfani, Nasrolah; Tahour Soltani, Mohsen Ahmadi

2018-01-01

INTRODUCTION: According to the research mission of the librarianship and information sciences field, it is necessary to have the ability to communicate constructively between the user of the information and information in these students, and it appears more important in medical librarianship and information sciences because of the need for quick access to information for clinicians. Considering the role of spiritual intelligence in capability to establish effective and balanced communication makes it important to study this variable in librarianship and information students. One of the main factors that can affect the results of any research is conceptual model of measure variables. Accordingly, the purpose of this study was codification of spiritual intelligence measurement model. METHODS: This correlational study was conducted through structural equation model, and 270 students were opted from library and medical information students of nationwide medical universities by simple random sampling and responded to the King spiritual intelligence questionnaire (2008). Initially, based on the data, the model parameters were estimated using maximum likelihood method; then, spiritual intelligence measurement model was tested by fit indices. Data analysis was performed by Smart-Partial Least Squares software. RESULTS: Preliminary results showed that due to the positive indicators of predictive association and t-test results for spiritual intelligence parameters, the King measurement model has the acceptable fit and internal correlation of the questionnaire items was significant. Composite reliability and Cronbach's alpha of parameters indicated high reliability of spiritual intelligence model. CONCLUSIONS: The spiritual intelligence measurement model was evaluated, and results showed that the model has a good fit, so it is recommended that domestic researchers use this questionnaire to assess spiritual intelligence. PMID:29922688

The codification of spiritual intelligence measurement model in librarianship and medical information science students of medical universities in Iran.

PubMed

Zarrinabadi, Zarrin; Isfandyari-Moghaddam, Alireza; Erfani, Nasrolah; Tahour Soltani, Mohsen Ahmadi

2018-01-01

According to the research mission of the librarianship and information sciences field, it is necessary to have the ability to communicate constructively between the user of the information and information in these students, and it appears more important in medical librarianship and information sciences because of the need for quick access to information for clinicians. Considering the role of spiritual intelligence in capability to establish effective and balanced communication makes it important to study this variable in librarianship and information students. One of the main factors that can affect the results of any research is conceptual model of measure variables. Accordingly, the purpose of this study was codification of spiritual intelligence measurement model. This correlational study was conducted through structural equation model, and 270 students were opted from library and medical information students of nationwide medical universities by simple random sampling and responded to the King spiritual intelligence questionnaire (2008). Initially, based on the data, the model parameters were estimated using maximum likelihood method; then, spiritual intelligence measurement model was tested by fit indices. Data analysis was performed by Smart-Partial Least Squares software. Preliminary results showed that due to the positive indicators of predictive association and t -test results for spiritual intelligence parameters, the King measurement model has the acceptable fit and internal correlation of the questionnaire items was significant. Composite reliability and Cronbach's alpha of parameters indicated high reliability of spiritual intelligence model. The spiritual intelligence measurement model was evaluated, and results showed that the model has a good fit, so it is recommended that domestic researchers use this questionnaire to assess spiritual intelligence.

Global connectivity of prefrontal cortex predicts cognitive control and intelligence

PubMed Central

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

Intelligent sensor in control systems for objects with changing thermophysical properties

NASA Astrophysics Data System (ADS)

Belousov, O. A.; Muromtsev, D. Yu; Belyaev, M. P.

2018-04-01

The control of heat devices in a wide temperature range given thermophysical properties of an object is a topical issue. Optimal control systems of electric furnaces have to meet strict requirements in terms of accuracy of production procedures and efficiency of energy consumption. The fulfillment of these requirements is possible only if the dynamics model describing adequately the processes occurring in the furnaces is used to calculate the optimal control actions. One of the types of electric furnaces is the electric chamber furnace intended for heat treatment of various materials at temperatures from thousands of degrees Celsius and above. To solve the above-mentioned problem and to determine its place in the system of energy-efficient control of dynamic modes in the electric furnace, we propose the concept of an intelligent sensor and a method of synthesizing variables on sets of functioning states. The use of synthesis algorithms for optimal control in real time ensures the required accuracy when operating under different conditions and operating modes of the electric chamber furnace.

Emotional Intelligence Components in Alcohol Dependent and Mentally Healthy Individuals

PubMed Central

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.

PubMed

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.

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.

Power Grid Maintenance Scheduling Intelligence Arrangement Supporting System Based on Power Flow Forecasting

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.

Revisiting measurement invariance in intelligence testing in aging research: Evidence for almost complete metric invariance across age groups.

PubMed

Sprague, Briana N; Hyun, Jinshil; Molenaar, Peter C M

2017-01-01

Invariance of intelligence across age is often assumed but infrequently explicitly tested. Horn and McArdle (1992) tested measurement invariance of intelligence, providing adequate model fit but might not consider all relevant aspects such as sub-test differences. The goal of the current paper is to explore age-related invariance of the WAIS-R using an alternative model that allows direct tests of age on WAIS-R subtests. Cross-sectional data on 940 participants aged 16-75 from the WAIS-R normative values were used. Subtests examined were information, comprehension, similarities, vocabulary, picture completion, block design, picture arrangement, and object assembly. The two intelligence factors considered were fluid and crystallized intelligence. Self-reported ages were divided into young (16-22, n = 300), adult (29-39, n = 275), middle (40-60, n = 205), and older (61-75, n = 160) adult groups. Results suggested partial metric invariance holds. Although most of the subtests reflected fluid and crystalized intelligence similarly across different ages, invariance did not hold for block design on fluid intelligence and picture arrangement on crystallized intelligence for older adults. Additionally, there was evidence of a correlated residual between information and vocabulary for the young adults only. This partial metric invariance model yielded acceptable model fit compared to previously-proposed invariance models of Horn and McArdle (1992). Almost complete metric invariance holds for a two-factor model of intelligence. Most of the subtests were invariant across age groups, suggesting little evidence for age-related bias in the WAIS-R. However, we did find unique relationships between two subtests and intelligence. Future studies should examine age-related differences in subtests when testing measurement invariance in intelligence.

The Role of Intelligence Quotient and Emotional Intelligence in Cognitive Control Processes

PubMed Central

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

Emotional intelligence is a second-stratum factor of intelligence: evidence from hierarchical and bifactor models.

PubMed

MacCann, Carolyn; Joseph, Dana L; Newman, Daniel A; Roberts, Richard D

2014-04-01

This article examines the status of emotional intelligence (EI) within the structure of human cognitive abilities. To evaluate whether EI is a 2nd-stratum factor of intelligence, data were fit to a series of structural models involving 3 indicators each for fluid intelligence, crystallized intelligence, quantitative reasoning, visual processing, and broad retrieval ability, as well as 2 indicators each for emotion perception, emotion understanding, and emotion management. Unidimensional, multidimensional, hierarchical, and bifactor solutions were estimated in a sample of 688 college and community college students. Results suggest adequate fit for 2 models: (a) an oblique 8-factor model (with 5 traditional cognitive ability factors and 3 EI factors) and (b) a hierarchical solution (with cognitive g at the highest level and EI representing a 2nd-stratum factor that loads onto g at λ = .80). The acceptable relative fit of the hierarchical model confirms the notion that EI is a group factor of cognitive ability, marking the expression of intelligence in the emotion domain. The discussion proposes a possible expansion of Cattell-Horn-Carroll theory to include EI as a 2nd-stratum factor of similar standing to factors such as fluid intelligence and visual processing.

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.

Effect of childhood nutrition counselling on intelligence in adolescence: a 15-year follow-up of a cluster-randomised trial.

PubMed

Munhoz, Tiago N; Santos, Iná S; Karam, Simone de M; Martines, Jose; Pelto, Gretel; Barcelos, Raquel; Gonçalves, Helen; Valle, Neiva Cj; Anselmi, Luciana; Matijasevich, Alicia

2017-08-01

The present study aimed to assess the effects of an early childhood nutrition counselling intervention on intelligence (as measured by the intelligence quotient (IQ)) at age 15-16 years. A single-blind, cluster-randomised trial. In 1998, in Southern Brazil, mothers of children aged 18 months or younger were enrolled in a nutrition counselling intervention (n 424). Counselling included encouragement and promotion of exclusive breast-feeding until 6 months of age and continued breast-feeding supplemented by protein-, lipid- and carbohydrate-rich foods after age 6 months up to age 2 years. The control group received routine feeding advice. In 2013, the fourth round of follow-up of these individuals, at the age of 15-16 years, was undertaken. IQ was assessed using the short form of the Wechsler Adult Intelligence Scale (WAIS-III). Mental disorders (evaluated using the Development and Well-Being Assessment (DAWBA)) and self-reported school failure, smoking and alcohol use were also investigated. Adjusted analyses were conducted using a multilevel model in accordance with the sampling process. Adolescents, mean (sd) age of 15·4 (0·5) years (n 339). Mean (sd) total IQ score was lower in the intervention group than the control group (93·4 (11·4) and 95·8 (11·2), respectively) but the association did not persist after adjustment. The prevalence of any mental disorders was similar between intervention and control groups (23·1 and 23·5 %, respectively). There were no differences between groups regarding school failure, smoking and alcohol use. Nutrition counselling intervention in early childhood had no effect on intelligence measured during adolescence.

Factors Associated with Cognition in Adults: The Seattle Longitudinal Study

PubMed Central

Yu, Fang; Ryan, Lindsay H.; Schaie, K. Warner; Willis, Sherry L.; Kolanowski, Ann

2010-01-01

A better understanding of factors that affect cognition could lead to improved health and greater independence for older adults. We examined the association of four modifiable factors (leisure-time physical activity, leisure-time cognitive activity, self-directed work, and hypertension) with changes in two aspects of fluid intelligence (verbal memory and inductive reasoning). Data for 626 adults collected over 14 years (three time points) were analyzed by multi-level modeling. A component of self-directed work, higher work control, was associated with better verbal memory (p < .05) and inductive reasoning (p < .01). There were no significant interactions among these factors. The findings suggest that a strong sense of control at work may be protective for fluid intelligence in adults. PMID:19606423

Operator modeling in commerical aviation: Cognitive models, intelligent displays, and pilot's assistants

NASA Technical Reports Server (NTRS)

Govindaraj, T.; Mitchell, C. M.

1994-01-01

One of the goals of the National Aviation Safety/Automation program is to address the issue of human-centered automation in the cockpit. Human-centered automation is automation that, in the cockpit, enhances or assists the crew rather than replacing them. The Georgia Tech research program focused on this general theme, with emphasis on designing a computer-based pilot's assistant, intelligent (i.e, context-sensitive) displays, and an intelligent tutoring system for understanding and operating the autoflight system. In particular, the aids and displays were designed to enhance the crew's situational awareness of the current state of the automated flight systems and to assist the crew's situational awareness of the current state of the automated flight systems and to assist the crew in coordinating the autoflight system resources. The activities of this grant included: (1) an OFMspert to understand pilot navigation activities in a 727 class aircraft; (2) an extension of OFMspert to understand mode control in a glass cockpit, Georgia Tech Crew Activity Tracking System (GT-CATS); (3) the design of a training system to teach pilots about the vertical navigation portion of the flight management system -VNAV Tutor; and (4) a proof-of-concept display, using existing display technology, to facilitate mode awareness, particularly in situations in which controlled flight into terrain (CFIT) is a potential.

Assessing Intelligence in Children and Youth Living in the Netherlands

ERIC Educational Resources Information Center

Hurks, Petra P. M.; Bakker, Helen

2016-01-01

In this article, we briefly describe the history of intelligence test use with children and youth in the Netherlands, explain which models of intelligence guide decisions about test use, and detail how intelligence tests are currently being used in Dutch school settings. Empirically supported and theoretical models studying the structure of human…

A model of systems integration to facilitate ITS deployment : FAST-TRAC phase IV deliverable

DOT National Transportation Integrated Search

2003-04-01

The FAST-TRAC (Faster and Safer Travel through Traffic Routing and Advanced Controls) Intelligent Transportation Systems (ITS) Field Test in Oakland County, an urbanized county in metropolitan Detroit, represents a large and successful systems integr...

PERCLOS: A Valid Psychophysiological Measure of Alertness As Assessed by Psychomotor Vigilance

DOT National Transportation Integrated Search

2002-04-01

The Logical Architecture is based on a Computer Aided Systems Engineering (CASE) model of the requirements for the flow of data and control through the various functions included in Intelligent Transportation Systems (ITS). Process Specifications pro...

ASSESSMENT OF A WIND TURBINE INTELLIGENT CONTROLLER FOR ENHANCED ENERGY PRODUCTION AND POLLUTION REDUCTION

EPA Science Inventory

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...

MESA: An Interactive Modeling and Simulation Environment for Intelligent Systems Automation

NASA Technical Reports Server (NTRS)

Charest, Leonard

1994-01-01

This report describes MESA, a software environment for creating applications that automate NASA mission opterations. MESA enables intelligent automation by utilizing model-based reasoning techniques developed in the field of Artificial Intelligence. Model-based reasoning techniques are realized in Mesa through native support of causal modeling and discrete event simulation.

Time estimation predicts mathematical intelligence.

PubMed

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.

Artificial intelligence: a new approach for prescription and monitoring of hemodialysis therapy.

PubMed

Akl, A I; Sobh, M A; Enab, Y M; Tattersall, J

2001-12-01

The effect of dialysis on patients is conventionally predicted using a formal mathematical model. This approach requires many assumptions of the processes involved, and validation of these may be difficult. The validity of dialysis urea modeling using a formal mathematical model has been challenged. Artificial intelligence using neural networks (NNs) has been used to solve complex problems without needing a mathematical model or an understanding of the mechanisms involved. In this study, we applied an NN model to study and predict concentrations of urea during a hemodialysis session. We measured blood concentrations of urea, patient weight, and total urea removal by direct dialysate quantification (DDQ) at 30-minute intervals during the session (in 15 chronic hemodialysis patients). The NN model was trained to recognize the evolution of measured urea concentrations and was subsequently able to predict hemodialysis session time needed to reach a target solute removal index (SRI) in patients not previously studied by the NN model (in another 15 chronic hemodialysis patients). Comparing results of the NN model with the DDQ model, the prediction error was 10.9%, with a not significant difference between predicted total urea nitrogen (UN) removal and measured UN removal by DDQ. NN model predictions of time showed a not significant difference with actual intervals needed to reach the same SRI level at the same patient conditions, except for the prediction of SRI at the first 30-minute interval, which showed a significant difference (P = 0.001). This indicates the sensitivity of the NN model to what is called patient clearance time; the prediction error was 8.3%. From our results, we conclude that artificial intelligence applications in urea kinetics can give an idea of intradialysis profiling according to individual clinical needs. In theory, this approach can be extended easily to other solutes, making the NN model a step forward to achieving artificial-intelligent dialysis control.

An endorsement-based approach to student modeling for planner-controlled intelligent tutoring systems

NASA Technical Reports Server (NTRS)

Murray, William R.

1990-01-01

An approach is described to student modeling for intelligent tutoring systems based on an explicit representation of the tutor's beliefs about the student and the arguments for and against those beliefs (called endorsements). A lexicographic comparison of arguments, sorted according to evidence reliability, provides a principled means of determining those beliefs that are considered true, false, or uncertain. Each of these beliefs is ultimately justified by underlying assessment data. The endorsement-based approach to student modeling is particularly appropriate for tutors controlled by instructional planners. These tutors place greater demands on a student model than opportunistic tutors. Numerical calculi approaches are less well-suited because it is difficult to correctly assign numbers for evidence reliability and rule plausibility. It may also be difficult to interpret final results and provide suitable combining functions. When numeric measures of uncertainty are used, arbitrary numeric thresholds are often required for planning decisions. Such an approach is inappropriate when robust context-sensitive planning decisions must be made. A TMS-based implementation of the endorsement-based approach to student modeling is presented, this approach is compared to alternatives, and a project history is provided describing the evolution of this approach.

Optimizing acoustical conditions for speech intelligibility in classrooms

NASA Astrophysics Data System (ADS)

Yang, Wonyoung

High speech intelligibility is imperative in classrooms where verbal communication is critical. However, the optimal acoustical conditions to achieve a high degree of speech intelligibility have previously been investigated with inconsistent results, and practical room-acoustical solutions to optimize the acoustical conditions for speech intelligibility have not been developed. This experimental study validated auralization for speech-intelligibility testing, investigated the optimal reverberation for speech intelligibility for both normal and hearing-impaired listeners using more realistic room-acoustical models, and proposed an optimal sound-control design for speech intelligibility based on the findings. The auralization technique was used to perform subjective speech-intelligibility tests. The validation study, comparing auralization results with those of real classroom speech-intelligibility tests, found that if the room to be auralized is not very absorptive or noisy, speech-intelligibility tests using auralization are valid. The speech-intelligibility tests were done in two different auralized sound fields---approximately diffuse and non-diffuse---using the Modified Rhyme Test and both normal and hearing-impaired listeners. A hybrid room-acoustical prediction program was used throughout the work, and it and a 1/8 scale-model classroom were used to evaluate the effects of ceiling barriers and reflectors. For both subject groups, in approximately diffuse sound fields, when the speech source was closer to the listener than the noise source, the optimal reverberation time was zero. When the noise source was closer to the listener than the speech source, the optimal reverberation time was 0.4 s (with another peak at 0.0 s) with relative output power levels of the speech and noise sources SNS = 5 dB, and 0.8 s with SNS = 0 dB. In non-diffuse sound fields, when the noise source was between the speaker and the listener, the optimal reverberation time was 0.6 s with SNS = 4 dB and increased to 0.8 and 1.2 s with decreased SNS = 0 dB, for both normal and hearing-impaired listeners. Hearing-impaired listeners required more early energy than normal-hearing listeners. Reflective ceiling barriers and ceiling reflectors---in particular, parallel front-back rows of semi-circular reflectors---achieved the goal of decreasing reverberation with the least speech-level reduction.

Tele-autonomous systems: New methods for projecting and coordinating intelligent action at a distance

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.

Typical intellectual engagement and cognition in old age.

PubMed

Dellenbach, Myriam; Zimprich, Daniel

2008-03-01

Typical Intellectual Engagement (TIE) comprises the preference to engage in cognitively demanding activities and has been proposed as a potential explanatory variable of individual differences in cognitive abilities. Little is known, however, about the factorial structure of TIE, its relations to socio-demographic variables, and its influence on intellectual functioning in old age. In the present study, data of 364 adults (65-81 years) from the Zurich Longitudinal Study on Cognitive Aging (ZULU) were used to investigate the factorial structure of TIE and to examine the hypothesis that TIE is associated more strongly with crystallized intelligence than with fluid intelligence in old age. A measurement model of a second order factor based on a structure of four correlated first order factors (Reading, Problem Solving, Abstract Thinking, and Intellectual Curiosity) evinced an excellent fit. After controlling for age, sex, and formal education, TIE was more strongly associated with crystallized intelligence than with fluid intelligence, comparable to results in younger persons. More detailed analyses showed that this association is mostly defined via Reading and Intellectual Curiosity.

The mediating effect of emotional intelligence between emotional labour, job stress, burnout and nurses' turnover intention.

PubMed

Hong, Eunyoung; Lee, Young Sook

2016-12-01

This study was designed to construct and test the structural equation modelling on nurses' turnover intention including emotional labour, job stress, emotional intelligence and burnout in order to identify the mediating effect of emotional intelligence between those variables. Emotional labour, job stress and burnout increase turnover intention of nurses. However, emotional intelligence is negatively correlated with emotional labour and reduces job stress, burnout and turnover intention. Structural equation modelling was used to analyse the goodness of fit of the hypothetical model of nurses' turnover intention. Research data were collected via questionnaires from 4 to 22 August 2014 and analysed using SPSS version 18.0 and AMOS version 20.0. The model fit indices for the hypothetical model were suitable for recommended. Emotional intelligence has decreasing effect on turnover intention through burnout, although its direct effect on turnover intention is not significant. Emotional intelligence has mediation effect between emotional labour and burnout. This study's results suggest that increasing emotional intelligence might critically decrease nurses' turnover intention by reducing the effect of emotional labour on burnout. © 2016 John Wiley & Sons Australia, Ltd.

Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control.

PubMed

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.

Evaluating the effect of work-family conflict and emotional intelligence in workplace: review to increase employees’ performance

NASA Astrophysics Data System (ADS)

Siahaan, E.

2018-03-01

Work-family conflict appeared as a form of women emancipation that made them commit two roles simultaneously, as a house wife and as a worker. This kind of situation created an issue about the impact of the role conflict experienced by women employees towards the level of their emotional control and performance. The aim of this study was to analyze and evaluate the impact of work-family conflict and emotional intelligence towards married women employees’ job performance. This study also proposed a mediating effect of emotional intelligence. This study used a structured questionnaires to gather the required data. There were 54 married women employees in PT Telkom Regional I participated in this study. The result of this study showed that the model could explain 14,6% variance in employees’ performance. Role conflict experienced by a woman burdened her mind and affected her emotional intelligence negatively. There was no effect of work-family conflict on employees’ performance; however, the conflict significantly affected employees performance in an indirect path. The performance would lower through the decrease of employees’ emotional intelligence as the result of the conflict happened. The most important aspect increasing employees’ performance was improving their emotional intelligence while maintaining their work-family conflict.

Rethinking Intelligence: The Role of Mindset in Promoting Success for Academically High-Risk Students

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…

Comparison of Intelligibility Measures for Adults with Parkinson's Disease, Adults with Multiple Sclerosis, and Healthy Controls

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).…

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.

Adaptive Interfaces

DTIC Science & Technology

1990-11-01

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

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.

Modelling intelligent behavior

NASA Technical Reports Server (NTRS)

Green, H. S.; Triffet, T.

1993-01-01

An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

Realization of a Complex Control & Diagnosis System on Simplified Hardware

NASA Astrophysics Data System (ADS)

Stetter, R.; Swamy Prasad, M.

2015-11-01

Energy is an important factor in today's industrial environment. Pump systems account for about 20% of the total industrial electrical energy consumption. Several studies show that with proper monitoring, control and maintenance, the efficiency of pump systems can be increased. Controlling pump systems with intelligent systems can help to reduce a pump's energy consumption by up to one third of its original consumption. The research in this paper was carried out in the scope of a research project which involves modelling and simulation of pump systems. This paper focuses on the future implementation of modelling capabilities in PLCs (programmable logic controllers). The whole project aims to use a pump itself as the sensor rather than introducing external sensors into the system, which would increase the cost considerably. One promising approach for an economic and robust industrial implementation of this intelligence is the use of PLCs. PLCs can be simulated in multiple ways; in this project, Codesys was chosen for several reasons which are explained in this paper. The first part of this paper explains the modelling of a pump itself, the process load of the asynchronous motor with a control system, and the simulation possibilities of the motor in Codesys. The second part describes the simulation and testing of a system realized. The third part elaborates the Codesys system structure and interfacing of the system with external files. The final part consists of comparing the result with an earlier Matlab/SIMULINK model and original test data.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

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

Design and validation of an intelligent wheelchair towards a clinically-functional outcome.

PubMed

Boucher, Patrice; Atrash, Amin; Kelouwani, Sousso; Honoré, Wormser; Nguyen, Hai; Villemure, Julien; Routhier, François; Cohen, Paul; Demers, Louise; Forget, Robert; Pineau, Joelle

2013-06-17

Many people with mobility impairments, who require the use of powered wheelchairs, have difficulty completing basic maneuvering tasks during their activities of daily living (ADL). In order to provide assistance to this population, robotic and intelligent system technologies have been used to design an intelligent powered wheelchair (IPW). This paper provides a comprehensive overview of the design and validation of the IPW. The main contributions of this work are three-fold. First, we present a software architecture for robot navigation and control in constrained spaces. Second, we describe a decision-theoretic approach for achieving robust speech-based control of the intelligent wheelchair. Third, we present an evaluation protocol motivated by a meaningful clinical outcome, in the form of the Robotic Wheelchair Skills Test (RWST). This allows us to perform a thorough characterization of the performance and safety of the system, involving 17 test subjects (8 non-PW users, 9 regular PW users), 32 complete RWST sessions, 25 total hours of testing, and 9 kilometers of total running distance. User tests with the RWST show that the navigation architecture reduced collisions by more than 60% compared to other recent intelligent wheelchair platforms. On the tasks of the RWST, we measured an average decrease of 4% in performance score and 3% in safety score (not statistically significant), compared to the scores obtained with conventional driving model. This analysis was performed with regular users that had over 6 years of wheelchair driving experience, compared to approximately one half-hour of training with the autonomous mode. The platform tested in these experiments is among the most experimentally validated robotic wheelchairs in realistic contexts. The results establish that proficient powered wheelchair users can achieve the same level of performance with the intelligent command mode, as with the conventional command mode.

Innovative neuro-fuzzy system of smart transport infrastructure for road traffic safety

NASA Astrophysics Data System (ADS)

Beinarovica, Anna; Gorobetz, Mikhail; Levchenkov, Anatoly

2017-09-01

The proposed study describes applying of neural network and fuzzy logic in transport control for safety improvement by evaluation of accidents’ risk by intelligent infrastructure devices. Risk evaluation is made by following multiple-criteria: danger, changeability and influence of changes for risk increasing. Neuro-fuzzy algorithms are described and proposed for task solution. The novelty of the proposed system is proved by deep analysis of known studies in the field. The structure of neuro-fuzzy system for risk evaluation and mathematical model is described in the paper. The simulation model of the intelligent devices for transport infrastructure is proposed to simulate different situations, assess the risks and propose the possible actions for infrastructure or vehicles to minimize the risk of possible accidents.

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

DOEpatents

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

2003-01-01

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

Emotional intelligence and affective events in nurse education: A narrative review.

PubMed

Lewis, Gillian M; Neville, Christine; Ashkanasy, Neal M

2017-06-01

To investigate the current state of knowledge about emotional intelligence and affective events that arise during nursing students' clinical placement experiences. Narrative literature review. CINAHL, MEDLINE, PsycINFO, Scopus, Web of Science, ERIC and APAIS-Health databases published in English between 1990 and 2016. Data extraction from and constant comparative analysis of ten (10) research articles. We found four main themes: (1) emotional intelligence buffers stress; (2) emotional intelligence reduces anxiety associated with end of life care; (3) emotional intelligence promotes effective communication; and (4) emotional intelligence improves nursing performance. The articles we analysed adopted a variety of emotional intelligence models. Using the Ashkanasy and Daus "three-stream" taxonomy (Stream 1: ability models; 2: self-report; 3: mixed models), we found that Stream 2 self-report measures were the most popular followed by Stream 3 mixed model measures. None of the studies we surveyed used the Stream 1 approach. Findings nonetheless indicated that emotional intelligence was important in maintaining physical and psychological well-being. We concluded that developing emotional intelligence should be a useful adjunct to improve academic and clinical performance and to reduce the risk of emotional distress during clinical placement experiences. We call for more consistency in the use of emotional intelligence tests as a means to create an empirical evidence base in the field of nurse education. Copyright © 2017 Elsevier Ltd. All rights reserved.

A watershed model of individual differences in fluid intelligence.

PubMed

Kievit, Rogier A; Davis, Simon W; Griffiths, John; Correia, Marta M; Cam-Can; Henson, Richard N

2016-10-01

Fluid intelligence is a crucial cognitive ability that predicts key life outcomes across the lifespan. Strong empirical links exist between fluid intelligence and processing speed on the one hand, and white matter integrity and processing speed on the other. We propose a watershed model that integrates these three explanatory levels in a principled manner in a single statistical model, with processing speed and white matter figuring as intermediate endophenotypes. We fit this model in a large (N=555) adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) using multiple measures of processing speed, white matter health and fluid intelligence. The model fit the data well, outperforming competing models and providing evidence for a many-to-one mapping between white matter integrity, processing speed and fluid intelligence. The model can be naturally extended to integrate other cognitive domains, endophenotypes and genotypes. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Research Needs for Artificial Intelligence Applications in Support of C3 (Command, Control, and Communication).

DTIC Science & Technology

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

The Three Models of Emotional Intelligence and Performance in a Hot and Cool go/no-go Task in Undergraduate Students

PubMed Central

Gutiérrez-Cobo, María J.; Cabello, Rosario; Fernández-Berrocal, Pablo

2017-01-01

Emotional intelligence (EI), or the ability to perceive, use, understand and regulate emotions, appears to be helpful in the performance of “hot” (i.e., emotionally laden) cognitive tasks when using performance-based ability models, but not when using self-report EI models. The aim of this study is to analyze the relationship between EI (as measured through a performance-based ability test, a self-report mixed test and a self-report ability test) and cognitive control ability during the performance of hot and “cool” (i.e., non-emotionally laden) “go/no-go” tasks. An experimental design was used for this study in which 187 undergraduate students (25% men) with a mean age of 21.93 years (standard deviation [SD] = 3.8) completed the three EI tests of interest (Mayer-Salovey-Caruso Emotional Intelligence Test [MSCEIT], Trait Meta-Mood Scale [TMMS] and Emotional Quotient Inventory–Short Form [EQi:S]) as well as go/no-go tasks using faces and geometric figures as stimuli. The results provide evidence for negative associations between the “managing” branch of EI measured through the performance-based ability test of EI and the cognitive control index of the hot go/no-go task, although similar evidence was not found when using the cool task. Further, the present study failed to observe consistent results when using the self-report EI instruments. These findings are discussed in terms of both the validity and implications of the various EI models. PMID:28275343

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-05-01

This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-03-01

This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

Adaptive method with intercessory feedback control for an intelligent agent

DOEpatents

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.

Modeling Smart Structure of Wind Turbine Blade

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

U.S. intelligence system: model for corporate chiefs?

PubMed

Gilad, B

1991-01-01

A fully dedicated intelligence support function for senior management is no longer a luxury but a necessity. Companies can enhance their intelligence capabilities by using the government model as a rough blueprint to structure such a program.

Artificial Neural Identification and LMI Transformation for Model Reduction-Based Control of the Buck Switch-Mode Regulator

NASA Astrophysics Data System (ADS)

Al-Rabadi, Anas N.

2009-10-01

This research introduces a new method of intelligent control for the control of the Buck converter using newly developed small signal model of the pulse width modulation (PWM) switch. The new method uses supervised neural network to estimate certain parameters of the transformed system matrix [Ã]. Then, a numerical algorithm used in robust control called linear matrix inequality (LMI) optimization technique is used to determine the permutation matrix [P] so that a complete system transformation {[B˜], [C˜], [Ẽ]} is possible. The transformed model is then reduced using the method of singular perturbation, and state feedback control is applied to enhance system performance. The experimental results show that the new control methodology simplifies the model in the Buck converter and thus uses a simpler controller that produces the desired system response for performance enhancement.

Trait Emotional Intelligence and Academic Performance: Controlling for the Effects of IQ, Personality, and Self-Concept

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…

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

NASA Astrophysics Data System (ADS)

Prakash, S.; Sinha, S. K.

2015-09-01

In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.

Breastfeeding and intelligence: a systematic review and meta-analysis.

PubMed

Horta, Bernardo L; Loret de Mola, Christian; Victora, Cesar G

2015-12-01

This study was aimed at systematically reviewing evidence of the association between breastfeeding and performance in intelligence tests. Two independent searches were carried out using Medline, LILACS, SCIELO and Web of Science. Studies restricted to infants and those where estimates were not adjusted for stimulation or interaction at home were excluded. Fixed- and random-effects models were used to pool the effect estimates, and a random-effects regression was used to assess potential sources of heterogeneity. We included 17 studies with 18 estimates of the relationship between breastfeeding and performance in intelligence tests. In a random-effects model, breastfed subjects achieved a higher IQ [mean difference: 3.44 points (95% confidence interval: 2.30; 4.58)]. We found no evidence of publication bias. Studies that controlled for maternal IQ showed a smaller benefit from breastfeeding [mean difference 2.62 points (95% confidence interval: 1.25; 3.98)]. In the meta-regression, none of the study characteristics explained the heterogeneity among the studies. Breastfeeding is related to improved performance in intelligence tests. A positive effect of breastfeeding on cognition was also observed in a randomised trial. This suggests that the association is causal. ©2015 The Authors. Acta Paediatrica published by John Wiley & Sons Ltd on behalf of Foundation Acta Paediatrica.

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...

Management and control of self-replicating systems: A systems model

NASA Technical Reports Server (NTRS)

Vontiesenhausen, G.

1982-01-01

In 1980, a conceptual engineering approach to self-replicating systems was achieved. The design was based on von Newmann's kinematic version of self-replicating automata. The systems management and control and the organization of the control elements are reported. After developing the functional requirements of such a system, a hierarchy of three management and control levels is described. These are an autonomous, an external, and an intelligent management and control system. Systems recycling, systems specialization, and information replication are discussed.

Design and implementation of fuzzy-PD controller based on relation models: A cross-entropy optimization approach

NASA Astrophysics Data System (ADS)

Anisimov, D. N.; Dang, Thai Son; Banerjee, Santo; Mai, The Anh

2017-07-01

In this paper, an intelligent system use fuzzy-PD controller based on relation models is developed for a two-wheeled self-balancing robot. Scaling factors of the fuzzy-PD controller are optimized by a Cross-Entropy optimization method. A linear Quadratic Regulator is designed to bring a comparison with the fuzzy-PD controller by control quality parameters. The controllers are ported and run on STM32F4 Discovery Kit based on the real-time operating system. The experimental results indicate that the proposed fuzzy-PD controller runs exactly on embedded system and has desired performance in term of fast response, good balance and stabilize.

Model architecture of intelligent data mining oriented urban transportation information

NASA Astrophysics Data System (ADS)

Yang, Bogang; Tao, Yingchun; Sui, Jianbo; Zhang, Feizhou

2007-06-01

Aiming at solving practical problems in urban traffic, the paper presents model architecture of intelligent data mining from hierarchical view. With artificial intelligent technologies used in the framework, the intelligent data mining technology improves, which is more suitable for the change of real-time road condition. It also provides efficient technology support for the urban transport information distribution, transmission and display.

RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

EPA Science Inventory

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.

PubMed

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.

Comparing Models of Intelligence in Project TALENT: The VPR Model Fits Better than the CHC and Extended Gf-Gc Models

ERIC Educational Resources Information Center

Major, Jason T.; Johnson, Wendy; Deary, Ian J.

2012-01-01

Three prominent theories of intelligence, the Cattell-Horn-Carroll (CHC), extended fluid-crystallized (Gf-Gc) and verbal-perceptual-image rotation (VPR) theories, provide differing descriptions of the structure of intelligence (McGrew, 2009; Horn & Blankson, 2005; Johnson & Bouchard, 2005b). To compare these theories, models representing them were…

General purpose architecture for intelligent computer-aided training

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen (Inventor); Wang, Lui (Inventor); Baffes, Paul T. (Inventor); Hua, Grace C. (Inventor)

1994-01-01

An intelligent computer-aided training system having a general modular architecture is provided for use in a wide variety of training tasks and environments. It is comprised of a user interface which permits the trainee to access the same information available in the task environment and serves as a means for the trainee to assert actions to the system; a domain expert which is sufficiently intelligent to use the same information available to the trainee and carry out the task assigned to the trainee; a training session manager for examining the assertions made by the domain expert and by the trainee for evaluating such trainee assertions and providing guidance to the trainee which are appropriate to his acquired skill level; a trainee model which contains a history of the trainee interactions with the system together with summary evaluative data; an intelligent training scenario generator for designing increasingly complex training exercises based on the current skill level contained in the trainee model and on any weaknesses or deficiencies that the trainee has exhibited in previous interactions; and a blackboard that provides a common fact base for communication between the other components of the system. Preferably, the domain expert contains a list of 'mal-rules' which typifies errors that are usually made by novice trainees. Also preferably, the training session manager comprises an intelligent error detection means and an intelligent error handling means. The present invention utilizes a rule-based language having a control structure whereby a specific message passing protocol is utilized with respect to tasks which are procedural or step-by-step in structure. The rules can be activated by the trainee in any order to reach the solution by any valid or correct path.

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

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

PubMed

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

2015-01-01

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

Scope of Attention, Control of Attention, and Intelligence in Children and Adults

PubMed Central

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

PubMed Central

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

PubMed Central

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.

PubMed

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

PubMed Central

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.

PubMed

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.

Predicting Speech Intelligibility Decline in Amyotrophic Lateral Sclerosis Based on the Deterioration of Individual Speech Subsystems

PubMed Central

Yunusova, Yana; Wang, Jun; Zinman, Lorne; Pattee, Gary L.; Berry, James D.; Perry, Bridget; Green, Jordan R.

2016-01-01

Purpose To determine the mechanisms of speech intelligibility impairment due to neurologic impairments, intelligibility decline was modeled as a function of co-occurring changes in the articulatory, resonatory, phonatory, and respiratory subsystems. Method Sixty-six individuals diagnosed with amyotrophic lateral sclerosis (ALS) were studied longitudinally. The disease-related changes in articulatory, resonatory, phonatory, and respiratory subsystems were quantified using multiple instrumental measures, which were subjected to a principal component analysis and mixed effects models to derive a set of speech subsystem predictors. A stepwise approach was used to select the best set of subsystem predictors to model the overall decline in intelligibility. Results Intelligibility was modeled as a function of five predictors that corresponded to velocities of lip and jaw movements (articulatory), number of syllable repetitions in the alternating motion rate task (articulatory), nasal airflow (resonatory), maximum fundamental frequency (phonatory), and speech pauses (respiratory). The model accounted for 95.6% of the variance in intelligibility, among which the articulatory predictors showed the most substantial independent contribution (57.7%). Conclusion Articulatory impairments characterized by reduced velocities of lip and jaw movements and resonatory impairments characterized by increased nasal airflow served as the subsystem predictors of the longitudinal decline of speech intelligibility in ALS. Declines in maximum performance tasks such as the alternating motion rate preceded declines in intelligibility, thus serving as early predictors of bulbar dysfunction. Following the rapid decline in speech intelligibility, a precipitous decline in maximum performance tasks subsequently occurred. PMID:27148967

Predicting Speech Intelligibility Decline in Amyotrophic Lateral Sclerosis Based on the Deterioration of Individual Speech Subsystems.

PubMed

Rong, Panying; Yunusova, Yana; Wang, Jun; Zinman, Lorne; Pattee, Gary L; Berry, James D; Perry, Bridget; Green, Jordan R

2016-01-01

To determine the mechanisms of speech intelligibility impairment due to neurologic impairments, intelligibility decline was modeled as a function of co-occurring changes in the articulatory, resonatory, phonatory, and respiratory subsystems. Sixty-six individuals diagnosed with amyotrophic lateral sclerosis (ALS) were studied longitudinally. The disease-related changes in articulatory, resonatory, phonatory, and respiratory subsystems were quantified using multiple instrumental measures, which were subjected to a principal component analysis and mixed effects models to derive a set of speech subsystem predictors. A stepwise approach was used to select the best set of subsystem predictors to model the overall decline in intelligibility. Intelligibility was modeled as a function of five predictors that corresponded to velocities of lip and jaw movements (articulatory), number of syllable repetitions in the alternating motion rate task (articulatory), nasal airflow (resonatory), maximum fundamental frequency (phonatory), and speech pauses (respiratory). The model accounted for 95.6% of the variance in intelligibility, among which the articulatory predictors showed the most substantial independent contribution (57.7%). Articulatory impairments characterized by reduced velocities of lip and jaw movements and resonatory impairments characterized by increased nasal airflow served as the subsystem predictors of the longitudinal decline of speech intelligibility in ALS. Declines in maximum performance tasks such as the alternating motion rate preceded declines in intelligibility, thus serving as early predictors of bulbar dysfunction. Following the rapid decline in speech intelligibility, a precipitous decline in maximum performance tasks subsequently occurred.

Human-simulated intelligent control of train braking response of bridge with MRB

NASA Astrophysics Data System (ADS)

Li, Rui; Zhou, Hongli; Wu, Yueyuan; Wang, Xiaojie

2016-04-01

The urgent train braking could bring structural response menace to the bridge under passive control. Based on the analysis of breaking dynamics of a train-bridge vibration system, a magnetorheological elastomeric bearing (MRB) whose mechanical parameters are adjustable is designed, tested and modeled. A finite element method (FEM) is carried out to model and optimize a full scale vibration isolation system for railway bridge based on MRB. According to the model above, we also consider the effect of different braking stop positions on the vibration isolation system and classify the bridge longitudinal vibration characteristics into several cases. Because the train-bridge vibration isolation system has multiple vibration states and strongly coupling with nonlinear characteristics, a human-simulated intelligent control (HSIC) algorithm for isolating the bridge vibration under the impact of train braking is proposed, in which the peak shear force of pier top, the displacement of beam and the acceleration of beam are chosen as control goals. The simulation of longitudinal vibration control system under the condition of train braking is achieved by MATLAB. The results indicate that different braking stop positions significantly affect the vibration isolation system and the structural response is the most drastic when the train stops at the third cross-span. With the proposed HSIC smart isolation system, the displacement of bridge beam and peak shear force of pier top is reduced by 53.8% and 34.4%, respectively. Moreover, the acceleration of bridge beam is effectively controlled within limited range.

Cooperative learning model with high order thinking skills questions: an understanding on geometry

NASA Astrophysics Data System (ADS)

Sari, P. P.; Budiyono; Slamet, I.

2018-05-01

Geometry, a branch of mathematics, has an important role in mathematics learning. This research aims to find out the effect of learning model, emotional intelligence, and the interaction between learning model and emotional intelligence toward students’ mathematics achievement. This research is quasi-experimental research with 2 × 3 factorial design. The sample in this research included 179 Senior High School students on 11th grade in Sukoharjo Regency, Central Java, Indonesia in academic year of 2016/2017. The sample was taken by using stratified cluster random sampling. The results showed that: the student are taught by Thinking Aloud Pairs Problem-Solving using HOTs questions provides better mathematics learning achievement than Make A Match using HOTs questions. High emotional intelligence students have better mathematics learning achievement than moderate and low emotional intelligence students, and moderate emotional intelligence students have better mathematics learning achievement than low emotional intelligence students. There is an interaction between learning model and emotional intelligence, and these affect mathematics learning achievement. We conclude that appropriate learning model can support learning activities become more meaningful and facilitate students to understand material. For further research, we suggest to explore the contribution of other aspects in cooperative learning modification to mathematics achievement.

Applications for the environment : real-time information synthesis (AERIS) eco-signal operations : operational concept.

DOT National Transportation Integrated Search

2002-04-01

The Logical Architecture is based on a Computer Aided Systems Engineering (CASE) model of the requirements for the flow of data and control through the various functions included in Intelligent Transportation Systems (ITS). Data Dictionary is the com...

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

ERIC Educational Resources Information Center

Montazemi, Ali R.; Wang, Feng

1995-01-01

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

The application of artificial intelligent techniques to accelerator operations at McMaster University

NASA Astrophysics Data System (ADS)

Poehlman, W. F. S.; Garland, Wm. J.; Stark, J. W.

1993-06-01

In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an "Operator's Companion" is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging.

Methamphetamine

MedlinePlus

... 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 ...

Narcotics

MedlinePlus

... 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 ...

Hydrocodone

MedlinePlus

... 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 ...

Team Emotional Intelligence, Team Interactions, and Gender in Medical Students During a Psychiatry Clerkship.

PubMed

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.

The Development of a Virtual McKenna Military Operations in Urban Terrain (MOUT) Site for Command, Control, Communication, Computing, Intelligence, Surveillance, and Reconnaissance (C4ISR) Studies

DTIC Science & Technology

2007-06-01

4.2 Creating the Skybox and Terrain Model .........................................................................7 4.3 Creating New Textures... Skybox and Terrain Model The next step was to build a sky box. Since it already resided in Raven Shield, the creation of the sky box was limited to

The Relationship Between Emotional Intelligence and Leader Performance

DTIC Science & Technology

2002-03-01

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

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…

Integrated Reconfigurable Intelligent Systems (IRIS) for Complex Naval Systems

DTIC Science & Technology

2009-12-31

written. The new implementation supports the XML dialect called dashML. The plug-in is written in Java script using a flexible extension of the...human in the loop control was improved and documented, and the script for integration was developed; further study on theoretical framework for...reference damage controller was developed and tested; the model of human in the loop control was improved and documented, and the script for integrating

Intelligence Fusion Modeling. A Proposed Approach.

DTIC Science & Technology

1983-09-16

based techniques developed by artificial intelligence researchers. This paper describes the application of these techniques in the modeling of an... intelligence requirements, although the methods presented are applicable . We treat PIR/IR as given. -7- -- -W V"W v* 1.- . :71.,v It k*~ ~-- Movement...items from the PIR/IR/HVT decomposition are received from the CMDS. Formatted tactical intelligence reports are received from sensors of like types

Generalizing on Multiple Grounds: Performance Learning in Model-Based Troubleshooting

DTIC Science & Technology

1989-02-01

Aritificial Intelligence , 24, 1984. [Ble88] Guy E. Blelloch. Scan Primitives and Parallel Vector Models. PhD thesis, Artificial Intelligence Laboratory...Diagnostic reasoning based on strcture and behavior. Aritificial Intelligence , 24, 1984. [dK86] J. de Kleer. An assumption-based truth maintenance system...diagnosis. Aritificial Intelligence , 24. �. )3 94 BIBLIOGRAPHY [Ham87] Kristian J. Hammond. Learning to anticipate and avoid planning prob- lems

Heroin Photos

MedlinePlus

... 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 ...

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

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

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

Development and application of a real-time testbed for multiagent system interoperability: A case study on hierarchical microgrid control

DOE PAGES

Cintuglu, Mehmet Hazar; Youssef, Tarek; Mohammed, Osama A.

2016-08-10

This article presents the development and application of a real-time testbed for multiagent system interoperability. As utility independent private microgrids are installed constantly, standardized interoperability frameworks are required to define behavioral models of the individual agents for expandability and plug-and-play operation. In this paper, we propose a comprehensive hybrid agent framework combining the foundation for intelligent physical agents (FIPA), IEC 61850, and data distribution service (DDS) standards. The IEC 61850 logical node concept is extended using FIPA based agent communication language (ACL) with application specific attributes and deliberative behavior modeling capability. The DDS middleware is adopted to enable a real-timemore » publisher-subscriber interoperability mechanism between platforms. The proposed multi-agent framework was validated in a laboratory based testbed involving developed intelligent electronic device (IED) prototypes and actual microgrid setups. Experimental results were demonstrated for both decentralized and distributed control approaches. Secondary and tertiary control levels of a microgrid were demonstrated for decentralized hierarchical control case study. A consensus-based economic dispatch case study was demonstrated as a distributed control example. Finally, it was shown that the developed agent platform is industrially applicable for actual smart grid field deployment.« less

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.

A novel AIDS/HIV intelligent medical consulting system based on expert systems.

PubMed

Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

2013-01-01

The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs' ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical.

Gratitude mediates the effect of emotional intelligence on subjective well-being: A structural equation modeling analysis.

PubMed

Geng, Yuan

2016-11-01

This study investigated the relationship among emotional intelligence, gratitude, and subjective well-being in a sample of university students. A total of 365 undergraduates completed the emotional intelligence scale, the gratitude questionnaire, and the subjective well-being measures. The results of the structural equation model showed that emotional intelligence is positively associated with gratitude and subjective well-being, that gratitude is positively associated with subjective well-being, and that gratitude partially mediates the positive relationship between emotional intelligence and subjective well-being. Bootstrap test results also revealed that emotional intelligence has a significant indirect effect on subjective well-being through gratitude.

Contemporary cybernetics and its facets of cognitive informatics and computational intelligence.

PubMed

Wang, Yingxu; Kinsner, Witold; Zhang, Du

2009-08-01

This paper explores the architecture, theoretical foundations, and paradigms of contemporary cybernetics from perspectives of cognitive informatics (CI) and computational intelligence. The modern domain and the hierarchical behavioral model of cybernetics are elaborated at the imperative, autonomic, and cognitive layers. The CI facet of cybernetics is presented, which explains how the brain may be mimicked in cybernetics via CI and neural informatics. The computational intelligence facet is described with a generic intelligence model of cybernetics. The compatibility between natural and cybernetic intelligence is analyzed. A coherent framework of contemporary cybernetics is presented toward the development of transdisciplinary theories and applications in cybernetics, CI, and computational intelligence.

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.

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.

Neural Networks for Modeling and Control of Particle Accelerators

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

Edelen, A. L.; Biedron, S. G.; Chase, B. E.

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Neural Networks for Modeling and Control of Particle Accelerators

NASA Astrophysics Data System (ADS)

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; Edstrom, D.; Milton, S. V.; Stabile, P.

2016-04-01

Particle accelerators are host to myriad nonlinear and complex physical phenomena. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems, as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. The purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.

Neural Networks for Modeling and Control of Particle Accelerators

DOE PAGES

Edelen, A. L.; Biedron, S. G.; Chase, B. E.; ...

2016-04-01

Myriad nonlinear and complex physical phenomena are host to particle accelerators. They often involve a multitude of interacting systems, are subject to tight performance demands, and should be able to run for extended periods of time with minimal interruptions. Often times, traditional control techniques cannot fully meet these requirements. One promising avenue is to introduce machine learning and sophisticated control techniques inspired by artificial intelligence, particularly in light of recent theoretical and practical advances in these fields. Within machine learning and artificial intelligence, neural networks are particularly well-suited to modeling, control, and diagnostic analysis of complex, nonlinear, and time-varying systems,more » as well as systems with large parameter spaces. Consequently, the use of neural network-based modeling and control techniques could be of significant benefit to particle accelerators. For the same reasons, particle accelerators are also ideal test-beds for these techniques. Moreover, many early attempts to apply neural networks to particle accelerators yielded mixed results due to the relative immaturity of the technology for such tasks. For the purpose of this paper is to re-introduce neural networks to the particle accelerator community and report on some work in neural network control that is being conducted as part of a dedicated collaboration between Fermilab and Colorado State University (CSU). We also describe some of the challenges of particle accelerator control, highlight recent advances in neural network techniques, discuss some promising avenues for incorporating neural networks into particle accelerator control systems, and describe a neural network-based control system that is being developed for resonance control of an RF electron gun at the Fermilab Accelerator Science and Technology (FAST) facility, including initial experimental results from a benchmark controller.« less

Forensic intelligence framework--Part I: Induction of a transversal model by comparing illicit drugs and false identity documents monitoring.

PubMed

Morelato, Marie; Baechler, Simon; Ribaux, Olivier; Beavis, Alison; Tahtouh, Mark; Kirkbride, Paul; Roux, Claude; Margot, Pierre

2014-03-01

Forensic intelligence is a distinct dimension of forensic science. Forensic intelligence processes have mostly been developed to address either a specific type of trace or a specific problem. Even though these empirical developments have led to successes, they are trace-specific in nature and contribute to the generation of silos which hamper the establishment of a more general and transversal model. Forensic intelligence has shown some important perspectives but more general developments are required to address persistent challenges. This will ensure the progress of the discipline as well as its widespread implementation in the future. This paper demonstrates that the description of forensic intelligence processes, their architectures, and the methods for building them can, at a certain level, be abstracted from the type of traces considered. A comparative analysis is made between two forensic intelligence approaches developed independently in Australia and in Europe regarding the monitoring of apparently very different kind of problems: illicit drugs and false identity documents. An inductive effort is pursued to identify similarities and to outline a general model. Besides breaking barriers between apparently separate fields of study in forensic science and intelligence, this transversal model would assist in defining forensic intelligence, its role and place in policing, and in identifying its contributions and limitations. The model will facilitate the paradigm shift from the current case-by-case reactive attitude towards a proactive approach by serving as a guideline for the use of forensic case data in an intelligence-led perspective. A follow-up article will specifically address issues related to comparison processes, decision points and organisational issues regarding forensic intelligence (part II). Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Design and Implementation of C-iLearning: A Cloud-Based Intelligent Learning System

ERIC Educational Resources Information Center

Xiao, Jun; Wang, Minjuan; Wang, Lamei; Zhu, Xiaoxiao

2013-01-01

The gradual development of intelligent learning (iLearning) systems has prompted the changes of teaching and learning. This paper presents the architecture of an intelligent learning (iLearning) system built upon the recursive iLearning model and the key technologies associated with this model. Based on this model and the technical structure of a…

Emotional intelligence and psychological health in a sample of Kuwaiti college students.

PubMed

Alkhadher, Othman

2007-06-01

This summary investigated correlations between emotional intelligence and psychological health amongst 191 Kuwaiti undergraduate students in psychology, 98 men and 93 women (M age=20.6 yr., SD=2.8). There were two measures of emotional intelligence, one based on the ability model, the Arabic Test for Emotional Intelligence, and the other on the mixed model, the Emotional Intelligence Questionnaire. Participants' psychological health was assessed using scales from the Personality Assessment Inventory. A weak relationship between the two types of emotional intelligence was found. A correlation for scores on the Emotional Intelligence Questionnaire with the Personality Assessment Inventory was found but not with those of the Arabic Test for Emotional Intelligence. Regression analysis indicated scores on Managing Emotions and Self-awareness accounted for most of the variance in the association with the Personality Assessment Inventory. Significant sex differences were found only on the Arabic Test for Emotional Intelligence; women scored higher than men. On Emotional Intelligence Questionnaire measures, men had significantly higher means on Managing Emotions and Self-motivation. However, no significant differences were found between the sexes on the Total Emotional Intelligence Questionnaire scores.

Longitudinal and concurrent links between memory span, anxiety symptoms, and subsequent executive functioning in young children

PubMed Central

Visu-Petra, Laura; Stanciu, Oana; Benga, Oana; Miclea, Mircea; Cheie, Lavinia

2014-01-01

It has been conjectured that basic individual differences in attentional control influence higher-level executive functioning and subsequent academic performance in children. The current study sets out to complement the limited body of research on early precursors of executive functions (EFs). It provides both a cross-sectional, as well as a longitudinal exploration of the relationship between EF and more basic attentional control mechanisms, assessed via children's performance on memory storage tasks, and influenced by individual differences in anxiety. Multiple measures of verbal and visuospatial short-term memory (STM) were administered to children between 3 and 6 years old, alongside a non-verbal measure of intelligence, and a parental report of anxiety symptoms. After 9 months, children were re-tested on the same STM measures, at which time we also administered multiple measures of executive functioning: verbal and visuospatial working memory (WM), inhibition, and shifting. A cross-sectional view of STM development indicated that between 3 and 6 years the trajectory of visuospatial STM and EF underwent a gradual linear improvement. However, between 5 and 6 years progress in verbal STM performance stagnated. Hierarchical regression models revealed that trait anxiety was negatively associated with WM and shifting, while non-verbal intelligence was positively related to WM span. When age, gender, non-verbal intelligence, and anxiety were controlled for, STM (measured at the first assessment) was a very good predictor of overall executive performance. The models were most successful in predicting WM, followed by shifting, yet poorly predicted inhibition measures. Further longitudinal research is needed to directly address the contribution of attentional control mechanisms to emerging executive functioning and to the development of problematic behavior during early development. PMID:24904462

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 analysis and application of a new hybrid pollutants forecasting model using modified Kolmogorov-Zurbenko filter.

PubMed

Li, Peizhi; Wang, Yong; Dong, Qingli

2017-04-01

Cities in China suffer from severe smog and haze, and a forecasting system with high accuracy is of great importance to foresee the concentrations of the airborne particles. Compared with chemical transport models, the growing artificial intelligence models can simulate nonlinearities and interactive relationships and getting more accurate results. In this paper, the Kolmogorov-Zurbenko (KZ) filter is modified and firstly applied to construct the model using an artificial intelligence method. The concentration of inhalable particles and fine particulate matter in Dalian are used to analyze the filtered components and test the forecasting accuracy. Besides, an extended experiment is made by implementing a comprehensive comparison and a stability test using data in three other cities in China. Results testify the excellent performance of the developed hybrid models, which can be utilized to better understand the temporal features of pollutants and to perform a better air pollution control and management. Copyright © 2017 Elsevier B.V. All rights reserved.

PlayPhysics: An Emotional Games Learning Environment for Teaching Physics

NASA Astrophysics Data System (ADS)

Muñoz, Karla; Kevitt, Paul Mc; Lunney, Tom; Noguez, Julieta; Neri, Luis

To ensure learning, game-based learning environments must incorporate assessment mechanisms, e.g. Intelligent Tutoring Systems (ITSs). ITSs are focused on recognising and influencing the learner's emotional or motivational states. This research focuses on designing and implementing an affective student model for intelligent gaming, which reasons about the learner's emotional state from cognitive and motivational variables using observable behaviour. A Probabilistic Relational Models (PRMs) approach is employed to derive Dynamic Bayesian Networks (DBNs). The model uses the Control-Value theory of 'achievement emotions' as a basis. A preliminary test was conducted to recognise the students' prospective-outcome emotions with results presented and discussed. PlayPhysics is an emotional games learning environment for teaching Physics. Once the affective student model proves effective it will be incorporated into PlayPhysics' architecture. The design, evaluation and postevaluation of PlayPhysics are also discussed. Future work will focus on evaluating the affective student model with a larger population of students, and on providing affective feedback.

Modeling of biological intelligence for SCM system optimization.

PubMed

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

2012-01-01

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

Modeling of Biological Intelligence for SCM System Optimization

PubMed Central

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

2012-01-01

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

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

PubMed Central

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

Web-based e-learning and virtual lab of human-artificial immune system.

PubMed

Gong, Tao; Ding, Yongsheng; Xiong, Qin

2014-05-01

Human immune system is as important in keeping the body healthy as the brain in supporting the intelligence. However, the traditional models of the human immune system are built on the mathematics equations, which are not easy for students to understand. To help the students to understand the immune systems, a web-based e-learning approach with virtual lab is designed for the intelligent system control course by using new intelligent educational technology. Comparing the traditional graduate educational model within the classroom, the web-based e-learning with the virtual lab shows the higher inspiration in guiding the graduate students to think independently and innovatively, as the students said. It has been found that this web-based immune e-learning system with the online virtual lab is useful for teaching the graduate students to understand the immune systems in an easier way and design their simulations more creatively and cooperatively. The teaching practice shows that the optimum web-based e-learning system can be used to increase the learning effectiveness of the students.

Sixth NASA Glenn Research Center Propulsion Control and Diagnostics (PCD) Workshop

NASA Technical Reports Server (NTRS)

Litt, Jonathan S. (Compiler)

2018-01-01

The Intelligent Control and Autonomy Branch at NASA Glenn Research Center hosted the Sixth Propulsion Control and Diagnostics Workshop on August 22-24, 2017. The objectives of this workshop were to disseminate information about research being performed in support of NASA Aeronautics programs; get feedback from peers on the research; and identify opportunities for collaboration. There were presentations and posters by NASA researchers, Department of Defense representatives, and engine manufacturers on aspects of turbine engine modeling, control, and diagnostics.

Cooperative intelligent robotics in space III; Proceedings of the Meeting, Boston, MA, Nov. 16-18, 1992

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.

Approximate reasoning-based learning and control for proximity operations and docking in space

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.; Jani, Yashvant; Lea, Robert N.

1991-01-01

A recently proposed hybrid-neutral-network and fuzzy-logic-control architecture is applied to a fuzzy logic controller developed for attitude control of the Space Shuttle. A model using reinforcement learning and learning from past experience for fine-tuning its knowledge base is proposed. Two main components of this approximate reasoning-based intelligent control (ARIC) model - an action-state evaluation network and action selection network are described as well as the Space Shuttle attitude controller. An ARIC model for the controller is presented, and it is noted that the input layer in each network includes three nodes representing the angle error, angle error rate, and bias node. Preliminary results indicate that the controller can hold the pitch rate within its desired deadband and starts to use the jets at about 500 sec in the run.

Fronto-Parietal gray matter and white matter efficiency differentially predict intelligence in males and females.

PubMed

Ryman, Sephira G; Yeo, Ronald A; Witkiewitz, Katie; Vakhtin, Andrei A; van den Heuvel, Martijn; de Reus, Marcel; Flores, Ranee A; Wertz, Christopher R; Jung, Rex E

2016-11-01

While there are minimal sex differences in overall intelligence, males, on average, have larger total brain volume and corresponding regional brain volumes compared to females, measures that are consistently related to intelligence. Limited research has examined which other brain characteristics may differentially contribute to intelligence in females to facilitate equal performance on intelligence measures. Recent reports of sex differences in the neural characteristics of the brain further highlight the need to differentiate how the structural neural characteristics relate to intellectual ability in males and females. The current study utilized a graph network approach in conjunction with structural equation modeling to examine potential sex differences in the relationship between white matter efficiency, fronto-parietal gray matter volume, and general cognitive ability (GCA). Participants were healthy adults (n = 244) who completed a battery of cognitive testing and underwent structural neuroimaging. Results indicated that in males, a latent factor of fronto-parietal gray matter was significantly related to GCA when controlling for total gray matter volume. In females, white matter efficiency and total gray matter volume were significantly related to GCA, with no specificity of the fronto-parietal gray matter factor over and above total gray matter volume. This work highlights that different neural characteristics across males and females may contribute to performance on intelligence measures. Hum Brain Mapp 37:4006-4016, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

No association between prenatal exposure to psychotropics and intelligence at age five.

PubMed

Eriksen, Hanne-Lise Falgreen; Kesmodel, Ulrik Schiøler; Pedersen, Lars Henning; Mortensen, Erik Lykke

2015-05-01

To examine associations between prenatal exposure to selective serotonin reuptake inhibitors (SSRIs)/anxiolytics and intelligence assessed with a standard clinical intelligence test at age 5 years. Longitudinal follow-up study. Denmark, 2003-2008. A total of 1780 women and their children sampled from the Danish National Birth Cohort. Self-reported information on use of SSRI and anxiolytics was obtained from the Danish National Birth Cohort at the time of consent and from two prenatal interviews. Intelligence was assessed at age 5 years, and parental education, maternal intelligence quotient (IQ), maternal smoking and alcohol consumption in pregnancy, the child's age at testing, sex, and tester were included in the full model. The IQ of 13 medication-exposed children was compared with the IQ of 19 children whose mothers had untreated depression and 1748 control children. Wechsler Preschool and Primary Scale of Intelligence - Revised. In unadjusted analyses, children of mothers who used antidepressants or anxiolytics during pregnancy had higher verbal IQ; this association, however, was insignificant after adjustment for potentially confounding maternal and child factors. No consistent associations between IQ and fetal exposure to antidepressants and anxiolytics were observed, but the study had low statistical power, and there is an obvious need to conduct long-term follow-up studies with comprehensive cognitive assessment and sufficiently large samples of adolescent or adult offspring. © 2015 Nordic Federation of Societies of Obstetrics and Gynecology.

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

Connectionist Models for Intelligent Computation

DTIC Science & Technology

1989-07-26

Intelligent Canputation 12. PERSONAL AUTHOR(S) H.H. Chen and Y.C. Lee 13a. o R,POT Cal 13b TIME lVD/rED 14 DATE OF REPORT (Year, Month, Day) JS PAGE...fied Project Title: Connectionist Models-for Intelligent Computation Contract/Grant No.: AFOSR-87-0388 Contract/Grant Period of Performance: Sept. 1...underlying principles, architectures and appilications of artificial neural networks for intelligent computations.o, Approach: -) We use both numerical

Actors: A Model of Concurrent Computation in Distributed Systems.

DTIC Science & Technology

1985-06-01

Artificial Intelligence Labora- tory of the Massachusetts Institute of Technology. Support for the labora- tory’s aritificial intelligence research is...RD-A157 917 ACTORS: A MODEL OF CONCURRENT COMPUTATION IN 1/3- DISTRIBUTED SY𔃿TEMS(U) MASSACHUSETTS INST OF TECH CRMBRIDGE ARTIFICIAL INTELLIGENCE ...Computation In Distributed Systems Gui A. Aghai MIT Artificial Intelligence Laboratory Thsdocument ha. been cipp-oved I= pblicrelease and sale; itsI

Robust Control Analysis of Hydraulic Turbine Speed

NASA Astrophysics Data System (ADS)

Jekan, P.; Subramani, C.

2018-04-01

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

[Control of intelligent car based on electroencephalogram and neurofeedback].

PubMed

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.

Advanced, Adaptive, Modular, Distributed, Generic Universal FADEC Framework for Intelligent Propulsion Control Systems (Preprint)

DTIC Science & Technology

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

Cognitive computing and eScience in health and life science research: artificial intelligence and obesity intervention programs.

PubMed

Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna

2017-12-01

To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.

Intelligent lead: a novel HRI sensor for guide robots.

PubMed

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.

Methamphetamine Lab Incidents, 2004-2014

MedlinePlus

... 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 ...

Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Mount, Frances; Carreon, Patricia; Torney, Susan E.

2001-01-01

The Engineering and Mission Operations Directorates at NASA Johnson Space Center are combining laboratories and expertise to establish the Human Centered Autonomous and Assistant Systems Testbed for Exploration Operations. This is a testbed for human centered design, development and evaluation of intelligent autonomous and assistant systems that will be needed for human exploration and development of space. This project will improve human-centered analysis, design and evaluation methods for developing intelligent software. This software will support human-machine cognitive and collaborative activities in future interplanetary work environments where distributed computer and human agents cooperate. We are developing and evaluating prototype intelligent systems for distributed multi-agent mixed-initiative operations. The primary target domain is control of life support systems in a planetary base. Technical approaches will be evaluated for use during extended manned tests in the target domain, the Bioregenerative Advanced Life Support Systems Test Complex (BIO-Plex). A spinoff target domain is the International Space Station (ISS) Mission Control Center (MCC). Prodl}cts of this project include human-centered intelligent software technology, innovative human interface designs, and human-centered software development processes, methods and products. The testbed uses adjustable autonomy software and life support systems simulation models from the Adjustable Autonomy Testbed, to represent operations on the remote planet. Ground operations prototypes and concepts will be evaluated in the Exploration Planning and Operations Center (ExPOC) and Jupiter Facility.

Biomechanical modeling and load-carrying simulation of lower limb exoskeleton.

PubMed

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.

The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level.

PubMed

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.

The effect of long chain polyunsaturated fatty acid supplementation on intelligence in low birth weight infant during lactation: A meta-analysis

PubMed Central

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

Model predictive control of attitude maneuver of a geostationary flexible satellite based on genetic algorithm

NASA Astrophysics Data System (ADS)

TayyebTaher, M.; Esmaeilzadeh, S. Majid

2017-07-01

This article presents an application of Model Predictive Controller (MPC) to the attitude control of a geostationary flexible satellite. SIMO model has been used for the geostationary satellite, using the Lagrange equations. Flexibility is also included in the modelling equations. The state space equations are expressed in order to simplify the controller. Naturally there is no specific tuning rule to find the best parameters of an MPC controller which fits the desired controller. Being an intelligence method for optimizing problem, Genetic Algorithm has been used for optimizing the performance of MPC controller by tuning the controller parameter due to minimum rise time, settling time, overshoot of the target point of the flexible structure and its mode shape amplitudes to make large attitude maneuvers possible. The model included geosynchronous orbit environment and geostationary satellite parameters. The simulation results of the flexible satellite with attitude maneuver shows the efficiency of proposed optimization method in comparison with LQR optimal controller.

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...

Comparison of learning models based on mathematics logical intelligence in affective domain

NASA Astrophysics Data System (ADS)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

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 ...

Exploring the neural substrates of attentional control and human intelligence: Diffusion tensor imaging of prefrontal white matter tractography in healthy cognition.

PubMed

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.

An intelligent anti-jamming network system of data link

NASA Astrophysics Data System (ADS)

Fan, Xiangrui; Lin, Jingyong; Liu, Jiarun; Zhou, Chunmei

2017-10-01

Data link is the key information system for the cooperation of weapons, single physical layer anti-jamming technology has been unable to meet its requirements. High dynamic precision-guided weapon nodes like missiles, anti-jamming design of data link system need to have stronger pertinence and effectiveness: the best anti-jamming communication mode can be selected intelligently in combat environment, in real time, guarantee the continuity of communication. We discuss an anti-jamming intelligent networking technology of data link based on interference awareness, put forward a model of intelligent anti-jamming system, and introduces the cognitive node protocol stack model and intelligent anti-jamming method, in order to improve the data chain of intelligent anti-jamming ability.

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

NASA Technical Reports Server (NTRS)

Bosworth, John T.

2008-01-01

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

An intelligent multi-media human-computer dialogue system

NASA Technical Reports Server (NTRS)

Neal, J. G.; Bettinger, K. E.; Byoun, J. S.; Dobes, Z.; Thielman, C. Y.

1988-01-01

Sophisticated computer systems are being developed to assist in the human decision-making process for very complex tasks performed under stressful conditions. The human-computer interface is a critical factor in these systems. The human-computer interface should be simple and natural to use, require a minimal learning period, assist the user in accomplishing his task(s) with a minimum of distraction, present output in a form that best conveys information to the user, and reduce cognitive load for the user. In pursuit of this ideal, the Intelligent Multi-Media Interfaces project is devoted to the development of interface technology that integrates speech, natural language text, graphics, and pointing gestures for human-computer dialogues. The objective of the project is to develop interface technology that uses the media/modalities intelligently in a flexible, context-sensitive, and highly integrated manner modelled after the manner in which humans converse in simultaneous coordinated multiple modalities. As part of the project, a knowledge-based interface system, called CUBRICON (CUBRC Intelligent CONversationalist) is being developed as a research prototype. The application domain being used to drive the research is that of military tactical air control.

Smart Collision Avoidance and Hazard Routing Mechanism for Intelligent Transport Network

NASA Astrophysics Data System (ADS)

Singh, Gurpreet; Gupta, Pooja; Wahab, Mohd Helmy Abd

2017-08-01

The smart vehicular ad-hoc network is the network that consists of vehicles for smooth movement and better management of the vehicular connectivity across the given network. This research paper aims to propose a set of solution for the VANETs consisting of the automatic driven vehicles, also called as the autonomous car. Such vehicular networks are always prone to collision due to the natural or un-natural reasons which must be solved before the large-scale deployment of the autonomous transport systems. The newly designed intelligent transport movement control mechanism is based upon the intelligent data propagation along with the vehicle collision and traffic jam prevention schema [8], which may help the future designs of smart cities to become more robust and less error-prone. In the proposed model, the focus is on designing a new dynamic and robust hazard routing protocol for intelligent vehicular networks for improvement of the overall performance in various aspects. It is expected to improve the overall transmission delay as well as the number of collisions or adversaries across the vehicular network zone.

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

PubMed

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

2008-12-01

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

A novel AIDS/HIV intelligent medical consulting system based on expert systems

PubMed Central

Ebrahimi, Alireza Pour; Toloui Ashlaghi, Abbas; Mahdavy Rad, Maryam

2013-01-01

Background: The purpose of this paper is to propose a novel intelligent model for AIDS/HIV data based on expert system and using it for developing an intelligent medical consulting system for AIDS/HIV. Materials and Methods: In this descriptive research, 752 frequently asked questions (FAQs) about AIDS/HIV are gathered from numerous websites about this disease. To perform the data mining and extracting the intelligent model, the 6 stages of Crisp method has been completed for FAQs. The 6 stages include: Business understanding, data understanding, data preparation, modelling, evaluation and deployment. C5.0 Tree classification algorithm is used for modelling. Also, rational unified process (RUP) is used to develop the web-based medical consulting software. Stages of RUP are as follows: Inception, elaboration, construction and transition. The intelligent developed model has been used in the infrastructure of the software and based on client's inquiry and keywords related FAQs are displayed to the client, according to the rank. FAQs’ ranks are gradually determined considering clients reading it. Based on displayed FAQs, test and entertainment links are also displayed. Result: The accuracy of the AIDS/HIV intelligent web-based medical consulting system is estimated to be 78.76%. Conclusion: AIDS/HIV medical consulting systems have been developed using intelligent infrastructure. Being equipped with an intelligent model, providing consulting services on systematic textual data and providing side services based on client's activities causes the implemented system to be unique. The research has been approved by Iranian Ministry of Health and Medical Education for being practical. PMID:24251290

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.

System of experts for intelligent data management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1993-01-01

A proposal to conduct research and development on a system of expert systems for intelligent data management (SEIDAM) is being developed. CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. at the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

System of Experts for Intelligent Data Management (SEIDAM)

NASA Technical Reports Server (NTRS)

Goodenough, David G.; Iisaka, Joji; Fung, KO

1992-01-01

It is proposed to conduct research and development on a system of expert systems for intelligent data management (SEIDAM). CCRS has much expertise in developing systems for integrating geographic information with space and aircraft remote sensing data and in managing large archives of remotely sensed data. SEIDAM will be composed of expert systems grouped in three levels. At the lowest level, the expert systems will manage and integrate data from diverse sources, taking account of symbolic representation differences and varying accuracies. Existing software can be controlled by these expert systems, without rewriting existing software into an Artificial Intelligence (AI) language. At the second level, SEIDAM will take the interpreted data (symbolic and numerical) and combine these with data models. At the top level, SEIDAM will respond to user goals for predictive outcomes given existing data. The SEIDAM Project will address the research areas of expert systems, data management, storage and retrieval, and user access and interfaces.

Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies.

PubMed

Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; Vom Hofe, Rudolf

2013-01-01

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage  = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Applications of artificial intelligence 1993: Knowledge-based systems in aerospace and industry; Proceedings of the Meeting, Orlando, FL, Apr. 13-15, 1993

NASA Technical Reports Server (NTRS)

Fayyad, Usama M. (Editor); Uthurusamy, Ramasamy (Editor)

1993-01-01

The present volume on applications of artificial intelligence with regard to knowledge-based systems in aerospace and industry discusses machine learning and clustering, expert systems and optimization techniques, monitoring and diagnosis, and automated design and expert systems. Attention is given to the integration of AI reasoning systems and hardware description languages, care-based reasoning, knowledge, retrieval, and training systems, and scheduling and planning. Topics addressed include the preprocessing of remotely sensed data for efficient analysis and classification, autonomous agents as air combat simulation adversaries, intelligent data presentation for real-time spacecraft monitoring, and an integrated reasoner for diagnosis in satellite control. Also discussed are a knowledge-based system for the design of heat exchangers, reuse of design information for model-based diagnosis, automatic compilation of expert systems, and a case-based approach to handling aircraft malfunctions.

Hypertext Publishing and the Revitalization of Knowledge.

ERIC Educational Resources Information Center

Louie, Steven; Rubeck, Robert F.

1989-01-01

Discusses the use of hypertext for publishing and other document control activities in higher education. Topics discussed include a model of hypertext, called GUIDE, that is used at the University of Arizona Medical School; the increase in the number of scholarly publications; courseware development by faculty; and artificial intelligence. (LRW)

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.

1981-01-01

The role of the pilot and crew for future aircraft is discussed. Fifteen formal experimental studies and the development of a variety of models of human behavior based on queueing history, pattern recognition methods, control theory, fuzzy set theory, and artificial intelligence concepts are presented. L.F.M.

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

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

Design and study of water supply system for supercritical unit boiler in thermal power station

NASA Astrophysics Data System (ADS)

Du, Zenghui

2018-04-01

In order to design and optimize the boiler feed water system of supercritical unit, the establishment of a highly accurate controlled object model and its dynamic characteristics are prerequisites for developing a perfect thermal control system. In this paper, the method of mechanism modeling often leads to large systematic errors. Aiming at the information contained in the historical operation data of the boiler typical thermal system, the modern intelligent identification method to establish a high-precision quantitative model is used. This method avoids the difficulties caused by the disturbance experiment modeling for the actual system in the field, and provides a strong reference for the design and optimization of the thermal automation control system in the thermal power plant.

Multiobjective optimization and multivariable control of the beer fermentation process with the use of evolutionary algorithms.

PubMed

Andrés-Toro, B; Girón-Sierra, J M; Fernández-Blanco, P; López-Orozco, J A; Besada-Portas, E

2004-04-01

This paper describes empirical research on the model, optimization and supervisory control of beer fermentation. Conditions in the laboratory were made as similar as possible to brewery industry conditions. Since mathematical models that consider realistic industrial conditions were not available, a new mathematical model design involving industrial conditions was first developed. Batch fermentations are multiobjective dynamic processes that must be guided along optimal paths to obtain good results. The paper describes a direct way to apply a Pareto set approach with multiobjective evolutionary algorithms (MOEAs). Successful finding of optimal ways to drive these processes were reported. Once obtained, the mathematical fermentation model was used to optimize the fermentation process by using an intelligent control based on certain rules.

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

NASA Astrophysics Data System (ADS)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

Application of artificial intelligence to the management of urological cancer.

PubMed

Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

2007-10-01

Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

Bits or Shots in Combat? The Generalized Deitchman Model of Guerrilla Warfare

DTIC Science & Technology

2013-08-13

fire; absence of intelligence leads to unaimed fire, dependent on targets’ density. We propose a new Lanchester -type model that mixes aimed and unaimed...military hardware. The idea of modeling the trade-off between firepower and intelligence in a Lanchester setting was first suggested by Schreiber [4...of intelligence leads to unaimed fire, dependent on targets? density. We propose a new Lanchester -type model that mixes aimed and unaimed fire, the

Intelligent data analysis to model and understand live cell time-lapse sequences.

PubMed

Paterson, Allan; Ashtari, M; Ribé, D; Stenbeck, G; Tucker, A

2012-01-01

One important aspect of cellular function, which is at the basis of tissue homeostasis, is the delivery of proteins to their correct destinations. Significant advances in live cell microscopy have allowed tracking of these pathways by following the dynamics of fluorescently labelled proteins in living cells. This paper explores intelligent data analysis techniques to model the dynamic behavior of proteins in living cells as well as to classify different experimental conditions. We use a combination of decision tree classification and hidden Markov models. In particular, we introduce a novel approach to "align" hidden Markov models so that hidden states from different models can be cross-compared. Our models capture the dynamics of two experimental conditions accurately with a stable hidden state for control data and multiple (less stable) states for the experimental data recapitulating the behaviour of particle trajectories within live cell time-lapse data. In addition to having successfully developed an automated framework for the classification of protein transport dynamics from live cell time-lapse data our model allows us to understand the dynamics of a complex trafficking pathway in living cells in culture.

Multiple Intelligences Profiles of Children with Attention Deficit and Hyperactivity Disorder in Comparison with Nonattention Deficit and Hyperactivity Disorder.

PubMed

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.

Teaching the Teachers: Emotional Intelligence Training for Teachers

ERIC Educational Resources Information Center

Hen, Meirav; Sharabi-Nov, Adi

2014-01-01

A growing body of research in recent years has supported the value of emotional intelligence in both effective teaching and student achievement. This paper presents a pre-post, quasi-experimental design study conducted to evaluate the contributions of a 56-h "Emotional Intelligence" training model. The model has been developed and…

The relationship between emotional intelligence and task-switching in temporal lobe epilepsy.

PubMed

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.

PubMed

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.

Meta-Analysis of Fluid Intelligence Tests of Children from the Chinese Mainland with Learning Difficulties

PubMed Central

Tong, Fang; Fu, Tong

2013-01-01

Objective To evaluate the differences in fluid intelligence tests between normal children and children with learning difficulties in China. Method PubMed, MD Consult, and other Chinese Journal Database were searched from their establishment to November 2012. After finding comparative studies of Raven measurements of normal children and children with learning difficulties, full Intelligent Quotation (FIQ) values and the original values of the sub-measurement were extracted. The corresponding effect model was selected based on the results of heterogeneity and parallel sub-group analysis was performed. Results Twelve documents were included in the meta-analysis, and the studies were all performed in mainland of China. Among these, two studies were performed at child health clinics, the other ten sites were schools and control children were schoolmates or classmates. FIQ was evaluated using a random effects model. WMD was −13.18 (95% CI: −16.50–−9.85). Children with learning difficulties showed significantly lower FIQ scores than controls (P<0.00001); Type of learning difficulty and gender differences were evaluated using a fixed-effects model (I2 = 0%). The sites and purposes of the studies evaluated here were taken into account, but the reasons of heterogeneity could not be eliminated; The sum IQ of all the subgroups showed considerable heterogeneity (I2 = 76.5%). The sub-measurement score of document A showed moderate heterogeneity among all documents, and AB, B, and E showed considerable heterogeneity, which was used in a random effect model. Individuals with learning difficulties showed heterogeneity as well. There was a moderate delay in the first three items (−0.5 to −0.9), and a much more pronounced delay in the latter three items (−1.4 to −1.6). Conclusion In the Chinese mainland, the level of fluid intelligence of children with learning difficulties was lower than that of normal children. Delayed development in sub-items of C, D, and E was more obvious. PMID:24236016

[Intelligence level and structure in school age children with fetal growth restriction].

PubMed

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.

Finite element analysis of cylinder shell resonator and design of intelligent density meter

NASA Astrophysics Data System (ADS)

W, Sui X.; M, Fan Y.; X, Zhang G.; R, Qiu Z.

2005-01-01

On the basis of the mathematical model and finite element analysis of the cylinder shell resonator, a novel resonant liquid density meter is designed. The meter consists of a cylinder shell resonator fixed on both ends, a measurement circuit with automatic gain control and automatic phase control, and a signal processing system with microcomputer unit C8051F021. The density meter is insensitive to the liquid pressure, and it can intelligently compensate for the temperature. The experiment results show the meter characteristic coefficients of K0, K1, and K2 at 25 centigrade are -129.5668 kg m-3, -0.2535 × 106 kg m-3 s-1 and 0.6239 × 1010 kg m-3 s-2, respectively. The accuracy of the sensor is ±0.1% in range of 700-900 kg m-3

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

PubMed

Chang, Yeong-Chan

2009-02-01

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

Speech Prosody Across Stimulus Types for Individuals with Parkinson's Disease.

PubMed

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.

Building-to-Grid Integration through Commercial Building Portfolios Participating in Energy and Frequency Regulation Markets

NASA Astrophysics Data System (ADS)

Pavlak, Gregory S.

Building energy use is a significant contributing factor to growing worldwide energy demands. In pursuit of a sustainable energy future, commercial building operations must be intelligently integrated with the electric system to increase efficiency and enable renewable generation. Toward this end, a model-based methodology was developed to estimate the capability of commercial buildings to participate in frequency regulation ancillary service markets. This methodology was integrated into a supervisory model predictive controller to optimize building operation in consideration of energy prices, demand charges, and ancillary service revenue. The supervisory control problem was extended to building portfolios to evaluate opportunities for synergistic effect among multiple, centrally-optimized buildings. Simulation studies performed showed that the multi-market optimization was able to determine appropriate opportunities for buildings to provide frequency regulation. Total savings were increased by up to thirteen percentage points, depending on the simulation case. Furthermore, optimizing buildings as a portfolio achieved up to seven additional percentage points of savings, depending on the case. Enhanced energy and cost savings opportunities were observed by taking the novel perspective of optimizing building portfolios in multiple grid markets, motivating future pursuits of advanced control paradigms that enable a more intelligent electric grid.

MapReduce Based Parallel Bayesian Network for Manufacturing Quality Control

NASA Astrophysics Data System (ADS)

Zheng, Mao-Kuan; Ming, Xin-Guo; Zhang, Xian-Yu; Li, Guo-Ming

2017-09-01

Increasing complexity of industrial products and manufacturing processes have challenged conventional statistics based quality management approaches in the circumstances of dynamic production. A Bayesian network and big data analytics integrated approach for manufacturing process quality analysis and control is proposed. Based on Hadoop distributed architecture and MapReduce parallel computing model, big volume and variety quality related data generated during the manufacturing process could be dealt with. Artificial intelligent algorithms, including Bayesian network learning, classification and reasoning, are embedded into the Reduce process. Relying on the ability of the Bayesian network in dealing with dynamic and uncertain problem and the parallel computing power of MapReduce, Bayesian network of impact factors on quality are built based on prior probability distribution and modified with posterior probability distribution. A case study on hull segment manufacturing precision management for ship and offshore platform building shows that computing speed accelerates almost directly proportionally to the increase of computing nodes. It is also proved that the proposed model is feasible for locating and reasoning of root causes, forecasting of manufacturing outcome, and intelligent decision for precision problem solving. The integration of bigdata analytics and BN method offers a whole new perspective in manufacturing quality control.

The Effectiveness of Yoga on Spiritual Intelligence in Air Traffic Controllers of Tehran Flight Control Center

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…

Social Intelligence in a Human-Machine Collaboration System

NASA Astrophysics Data System (ADS)

Nakajima, Hiroshi; Morishima, Yasunori; Yamada, Ryota; Brave, Scott; Maldonado, Heidy; Nass, Clifford; Kawaji, Shigeyasu

In this information society of today, it is often argued that it is necessary to create a new way of human-machine interaction. In this paper, an agent with social response capabilities has been developed to achieve this goal. There are two kinds of information that is exchanged by two entities: objective and functional information (e.g., facts, requests, states of matters, etc.) and subjective information (e.g., feelings, sense of relationship, etc.). Traditional interactive systems have been designed to handle the former kind of information. In contrast, in this study social agents handling the latter type of information are presented. The current study focuses on sociality of the agent from the view point of Media Equation theory. This article discusses the definition, importance, and benefits of social intelligence as agent technology and argues that social intelligence has a potential to enhance the user's perception of the system, which in turn can lead to improvements of the system's performance. In order to implement social intelligence in the agent, a mind model has been developed to render affective expressions and personality of the agent. The mind model has been implemented in a human-machine collaborative learning system. One differentiating feature of the collaborative learning system is that it has an agent that performs as a co-learner with which the user interacts during the learning session. The mind model controls the social behaviors of the agent, thus making it possible for the user to have more social interactions with the agent. The experiment with the system suggested that a greater degree of learning was achieved when the students worked with the co-learner agent and that the co-learner agent with the mind model that expressed emotions resulted in a more positive attitude toward the system.

Patch models and their applications to multivehicle command and control.

PubMed

Rao, Venkatesh G; D'Andrea, Raffaello

2007-06-01

We introduce patch models, a computational modeling formalism for multivehicle combat domains, based on spatiotemporal abstraction methods developed in the computer science community. The framework yields models that are expressive enough to accommodate nontrivial controlled vehicle dynamics while being within the representational capabilities of common artificial intelligence techniques used in the construction of autonomous systems. The framework allows several key design requirements of next-generation network-centric command and control systems, such as maintenance of shared situation awareness, to be achieved. Major features include support for multiple situation models at each decision node and rapid mission plan adaptation. We describe the formal specification of patch models and our prototype implementation, i.e., Patchworks. The capabilities of patch models are validated through a combat mission simulation in Patchworks, which involves two defending teams protecting a camp from an enemy attacking team.

Magnetron Sputtered Pulsed Laser Deposition Scale Up

DTIC Science & Technology

2003-08-14

2:721-726 34 S. J. P. Laube and E. F. Stark, “ Artificial Intellegence in Process Control of Pulsed Laser Deposition”, Proceedings of...The model would be based on mathematical simulation of real process data, neural-networks, or other artificial intelligence methods based on in situ...Laube and E. F. Stark, Proc. Symp. Artificial Intel. Real Time Control, Valencia, Spain, 3-5 Oct. ,1994, p.159-163. International Federation of

Intelligent robots for planetary exploration and construction

NASA Technical Reports Server (NTRS)

Albus, James S.

1992-01-01

Robots capable of practical applications in planetary exploration and construction will require realtime sensory-interactive goal-directed control systems. A reference model architecture based on the NIST Real-time Control System (RCS) for real-time intelligent control systems is suggested. RCS partitions the control problem into four basic elements: behavior generation (or task decomposition), world modeling, sensory processing, and value judgment. It clusters these elements into computational nodes that have responsibility for specific subsystems, and arranges these nodes in hierarchical layers such that each layer has characteristic functionality and timing. Planetary exploration robots should have mobility systems that can safely maneuver over rough surfaces at high speeds. Walking machines and wheeled vehicles with dynamic suspensions are candidates. The technology of sensing and sensory processing has progressed to the point where real-time autonomous path planning and obstacle avoidance behavior is feasible. Map-based navigation systems will support long-range mobility goals and plans. Planetary construction robots must have high strength-to-weight ratios for lifting and positioning tools and materials in six degrees-of-freedom over large working volumes. A new generation of cable-suspended Stewart platform devices and inflatable structures are suggested for lifting and positioning materials and structures, as well as for excavation, grading, and manipulating a variety of tools and construction machinery.

Improving the All-Hazards Homeland Security Enterprise Through the Use of an Emergency Management Intelligence Model

DTIC Science & Technology

2013-09-01

Office of the Inspector General OSINT Open Source Intelligence PPD Presidential Policy Directive SIGINT Signals Intelligence SLFC State/Local Fusion...Geospatial Intelligence (GEOINT) from Geographic Information Systems (GIS), and Open Source Intelligence ( OSINT ) from Social Media. GIS is widely...and monitor make it a feasible tool to capitalize on for OSINT . A formalized EM intelligence process would help expedite the processing of such

Intelligence in youth and all-cause-mortality: systematic review with meta-analysis.

PubMed

Calvin, Catherine M; Deary, Ian J; Fenton, Candida; Roberts, Beverly A; Der, Geoff; Leckenby, Nicola; Batty, G David

2011-06-01

A number of prospective cohort studies have examined the association between intelligence in childhood or youth and life expectancy in adulthood; however, the effect size of this association is yet to be quantified and previous reviews require updating. The systematic review included an electronic search of EMBASE, MEDLINE and PSYCHINFO databases. This yielded 16 unrelated studies that met inclusion criteria, comprising 22,453 deaths among 1,107,022 participants. Heterogeneity was assessed, and fixed effects models were applied to the aggregate data. Publication bias was evaluated, and sensitivity analyses were conducted. A 1-standard deviation (SD) advantage in cognitive test scores was associated with a 24% (95% confidence interval 23-25) lower risk of death, during a 17- to 69-year follow-up. There was little evidence of publication bias (Egger's intercept = 0.10, P = 0.81), and the intelligence-mortality association was similar for men and women. Adjustment for childhood socio-economic status (SES) in the nine studies containing these data had almost no impact on this relationship, suggesting that this is not a confounder of the intelligence-mortality association. Controlling for adult SES in five studies and for education in six studies attenuated the intelligence-mortality hazard ratios by 34 and 54%, respectively. Future investigations should address the extent to which attenuation of the intelligence-mortality link by adult SES indicators is due to mediation, over-adjustment and/or confounding. The explanation(s) for association between higher early-life intelligence and lower risk of adult mortality require further elucidation.

High educational performance is a distinctive feature of bipolar disorder; a study on cognition in bipolar disorder, schizophrenia patients, relatives and controls

PubMed Central

Vreeker, Annabel; Boks, Marco P.M.; Abramovic, Lucija; Verkooijen, Sanne; van Bergen, Annet H.; Hillegers, Manon H.J.; Spijker, Annet T.; Hoencamp, Erik; Regeer, Eline J.; Riemersma-Van der Lek, Rixt F.; Stevens, Anja W.M.M.; Schulte, Peter F.J.; Vonk, Ronald; Hoekstra, Rocco; van Beveren, Nico J.M.; Kupka, Ralph W.; Brouwer, Rachel M.; Bearden, Carrie E.; MacCabe, James H.; Ophoff, Roel A.

2017-01-01

Background Schizophrenia is associated with lower intelligence and poor educational performance relative to the general population. This is, to a lesser degree, also found in first-degree relatives of schizophrenia patients. It is unclear whether bipolar disorder I (BD-I) patients and their relatives have similar lower intellectual and educational performance as that observed in schizophrenia. Methods This cross-sectional study investigated intelligence and educational performance in two outpatient samples (494 BD-I patients, 952 schizophrenia spectrum (SCZ) patients), 2,231 BD-I and SCZ relatives patients, 1,104 healthy controls and 100 control siblings. Mixed-effects- and regression models were used to compare groups on intelligence and educational performance. Results BD-I patients were more likely to have completed the highest level of education (OR=1.88 [1.66–2.70]) despite having a lower IQ compared with controls (β=−9.09, SE=1.27, p<0.001). In contrast, SCZ patients showed both a lower IQ (β= −15.31, SE=0.86, p<0.001) and lower educational levels compared with controls. Siblings of both patient groups had significantly lower IQ than control siblings, but did not differ on educational performance. IQ scores did not differ between BD-I parents and SCZ parents, but BD-I parents had completed higher educational levels. Conclusions Although BD-I patients had a lower IQ than controls, they were more likely to have completed the highest level of education. This contrasts with SCZ patients, who showed both intellectual and educational deficits compared to healthy controls. Since relatives of BD-I patients did not demonstrate superior educational performance, our data suggest that high educational performance may be a distinctive feature of bipolar disorder patients. PMID:26621616

Knowledge Based Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle.

DTIC Science & Technology

1988-04-13

Simulation: An Artificial Intelligence Approach to System Modeling and Automating the Simulation Life Cycle Mark S. Fox, Nizwer Husain, Malcolm...McRoberts and Y.V.Reddy CMU-RI-TR-88-5 Intelligent Systems Laboratory The Robotics Institute Carnegie Mellon University Pittsburgh, Pennsylvania D T T 13...years of research in the application of Artificial Intelligence to Simulation. Our focus has been in two areas: the use of Al knowledge representation

A Generalized Quantum-Inspired Decision Making Model for Intelligent Agent

PubMed Central

Loo, Chu Kiong

2014-01-01

A novel decision making for intelligent agent using quantum-inspired approach is proposed. A formal, generalized solution to the problem is given. Mathematically, the proposed model is capable of modeling higher dimensional decision problems than previous researches. Four experiments are conducted, and both empirical experiments results and proposed model's experiment results are given for each experiment. Experiments showed that the results of proposed model agree with empirical results perfectly. The proposed model provides a new direction for researcher to resolve cognitive basis in designing intelligent agent. PMID:24778580

The Cylindrical Structure of the Wechsler Intelligence Scale for Children--IV: A Retest of the Guttman Model of Intelligence

ERIC Educational Resources Information Center

Cohen, Arie; Fiorello, Catherine A.; Farley, Frank H.

2006-01-01

A previous study on the underlying structure of the Wechsler intelligence test (WISC-R; [Wechsler, D. (1974). Manual WISC-R: Wechsler intelligence scale for children-Revised. New York: Psychological Corporation]), using smallest space analysis (SSA) [Guttman, L., and Levy, S. (1991). Two structural laws for intelligence tests.…

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...

Cognitive Science: Persistent Apes Are Intelligent Apes.

PubMed

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.

Intelligent tutoring and aiding in satellite ground control. Ph.D. Thesis - Georgia Inst. of Tech., 1991

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.

The Evolution of Instructional Design Principles for Intelligent Computer-Assisted Instruction.

ERIC Educational Resources Information Center

Dede, Christopher; Swigger, Kathleen

1988-01-01

Discusses and compares the design and development of computer assisted instruction (CAI) and intelligent computer assisted instruction (ICAI). Topics discussed include instructional systems design (ISD), artificial intelligence, authoring languages, intelligent tutoring systems (ITS), qualitative models, and emerging issues in instructional…

Beyond a bigger brain: Multivariable structural brain imaging and intelligence

PubMed Central

Ritchie, Stuart J.; Booth, Tom; Valdés Hernández, Maria del C.; Corley, Janie; Maniega, Susana Muñoz; Gow, Alan J.; Royle, Natalie A.; Pattie, Alison; Karama, Sherif; Starr, John M.; Bastin, Mark E.; Wardlaw, Joanna M.; Deary, Ian J.

2015-01-01

People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in their seventies (n = 672) who were administered a comprehensive cognitive test battery. Using structural equation modelling, we related six common magnetic resonance imaging-derived brain variables that represent normal and abnormal features—brain volume, cortical thickness, white matter structure, white matter hyperintensity load, iron deposits, and microbleeds—to g and to fluid intelligence. As expected, brain volume accounted for the largest portion of variance (~ 12%, depending on modelling choices). Adding the additional variables, especially cortical thickness (+~ 5%) and white matter hyperintensity load (+~ 2%), increased the predictive value of the model. Depending on modelling choices, all neuroimaging variables together accounted for 18–21% of the variance in intelligence. These results reveal which structural brain imaging measures relate to g over and above the largest contributor, total brain volume. They raise questions regarding which other neuroimaging measures might account for even more of the variance in intelligence. PMID:26240470

A Human Factors Analysis of Proactive Support in Human-Robot Teaming

DTIC Science & Technology

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.

The Case for Intelligent Propulsion Control for Fast Engine Response

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Frederick, Dean K.; Guo, Ten-Huei

2009-01-01

Damaged aircraft have occasionally had to rely solely on thrust to maneuver as a consequence of losing hydraulic power needed to operate flight control surfaces. The lack of successful landings in these cases inspired research into more effective methods of utilizing propulsion-only control. That research demonstrated that one of the major contributors to the difficulty in landing is the slow response of the engines as compared to using traditional flight control. To address this, research is being conducted into ways of making the engine more responsive under emergency conditions. This can be achieved by relaxing controller limits, adjusting schedules, and/or redesigning the regulators to increase bandwidth. Any of these methods can enable faster response at the potential expense of engine life and increased likelihood of stall. However, an example sensitivity analysis revealed a complex interaction of the limits and the difficulty in predicting the way to achieve the fastest response. The sensitivity analysis was performed on a realistic engine model, and demonstrated that significantly faster engine response can be achieved compared to standard Bill of Material control. However, the example indicates the need for an intelligent approach to controller limit adjustment in order for the potential to be fulfilled.

The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

ERIC Educational Resources Information Center

Hali, Nur Ihsan

2017-01-01

This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

Intelligent tutoring systems for systems engineering methodologies

NASA Technical Reports Server (NTRS)

Meyer, Richard J.; Toland, Joel; Decker, Louis

1991-01-01

The general goal is to provide the technology required to build systems that can provide intelligent tutoring in IDEF (Integrated Computer Aided Manufacturing Definition Method) modeling. The following subject areas are covered: intelligent tutoring systems for systems analysis methodologies; IDEF tutor architecture and components; developing cognitive skills for IDEF modeling; experimental software; and PC based prototype.

An Analytical Model / Emotional Intelligence Quotient and QOL in Mothers with Infants in Japan.

PubMed

Ohashi, Junko; Katsura, Toshiki; Hoshino, Akiko; Usui, Kanae

2013-01-01

The purpose of this study was to examine the relationship between the emotional intelligence quotient and health-related quality of life using structural equation modeling. A self-administered questionnaire survey was conducted among 1,911 mothers who visited the Health Center for an infant medical examination. A hypothetical model was constructed using variables of the emotional intelligence quotient, social support, coping, parenting stress, and perceived health competence. There were a total of 1,104 valid responses (57.8%). Significant standardized estimates were obtained, confirming the goodness of fit issues with the model. The emotional intelligence quotient had a strong impact on physical and psychological quality of life, and showed the greatest association with coping. This study differed from previous studies in that, due to the inclusion of social support and explanatory variables in coping, an increase in coping strategies was more highly associated with emotional intelligence quotient levels than with social support. An enhanced emotional intelligence quotient should be considered a primary objective to promote the health of mothers with infant children.

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

PubMed Central

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.

PubMed

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.

Hippocampal structure and human cognition: key role of spatial processing and evidence supporting the efficiency hypothesis in females

PubMed Central

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.

The effects of an emotional intelligence program on the quality of life and well-being of patients with type 2 diabetes mellitus.

PubMed

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.

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.

Design and validation of an intelligent wheelchair towards a clinically-functional outcome

PubMed Central

2013-01-01

Background Many people with mobility impairments, who require the use of powered wheelchairs, have difficulty completing basic maneuvering tasks during their activities of daily living (ADL). In order to provide assistance to this population, robotic and intelligent system technologies have been used to design an intelligent powered wheelchair (IPW). This paper provides a comprehensive overview of the design and validation of the IPW. Methods The main contributions of this work are three-fold. First, we present a software architecture for robot navigation and control in constrained spaces. Second, we describe a decision-theoretic approach for achieving robust speech-based control of the intelligent wheelchair. Third, we present an evaluation protocol motivated by a meaningful clinical outcome, in the form of the Robotic Wheelchair Skills Test (RWST). This allows us to perform a thorough characterization of the performance and safety of the system, involving 17 test subjects (8 non-PW users, 9 regular PW users), 32 complete RWST sessions, 25 total hours of testing, and 9 kilometers of total running distance. Results User tests with the RWST show that the navigation architecture reduced collisions by more than 60% compared to other recent intelligent wheelchair platforms. On the tasks of the RWST, we measured an average decrease of 4% in performance score and 3% in safety score (not statistically significant), compared to the scores obtained with conventional driving model. This analysis was performed with regular users that had over 6 years of wheelchair driving experience, compared to approximately one half-hour of training with the autonomous mode. Conclusions The platform tested in these experiments is among the most experimentally validated robotic wheelchairs in realistic contexts. The results establish that proficient powered wheelchair users can achieve the same level of performance with the intelligent command mode, as with the conventional command mode. PMID:23773851

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.

Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing.

PubMed

Jørgensen, Søren; Dau, Torsten

2011-09-01

A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The model estimates the speech-to-noise envelope power ratio, SNR(env), at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech-shaped noise. The model was further tested in conditions with noisy speech subjected to reverberation and spectral subtraction. Good agreement between predictions and data was found in all cases. For spectral subtraction, an analysis of the model's internal representation of the stimuli revealed that the predicted decrease of intelligibility was caused by the estimated noise envelope power exceeding that of the speech. The classical concept of the speech transmission index fails in this condition. The results strongly suggest that the signal-to-noise ratio at the output of a modulation frequency selective process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

NASA Astrophysics Data System (ADS)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid-electric propulsion system. The CMAC neural network approximates the hyper-plane generated from the instantaneous optimization algorithm and produces torque commands for the internal combustion engine and electric motor. The CMAC neural network controller saves on the required memory as compared to a large look-up table by two orders of magnitude. The CMAC controller also prevents the need to compute a hyper-plane or complex logic every time step.

32 CFR 1903.1 - Definitions.

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...

32 CFR 1903.1 - Definitions.

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...

32 CFR 1903.1 - Definitions.

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...

32 CFR 1903.1 - Definitions.

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...

32 CFR 1903.1 - Definitions.

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...