MITT writer and MITT writer advanced development: Developing authoring and training systems for complex technical domains

NASA Technical Reports Server (NTRS)

Wiederholt, Bradley J.; Browning, Elica J.; Norton, Jeffrey E.; Johnson, William B.

1991-01-01

MITT Writer is a software system for developing computer based training for complex technical domains. A training system produced by MITT Writer allows a student to learn and practice troubleshooting and diagnostic skills. The MITT (Microcomputer Intelligence for Technical Training) architecture is a reasonable approach to simulation based diagnostic training. MITT delivers training on available computing equipment, delivers challenging training and simulation scenarios, and has economical development and maintenance costs. A 15 month effort was undertaken in which the MITT Writer system was developed. A workshop was also conducted to train instructors in how to use MITT Writer. Earlier versions were used to develop an Intelligent Tutoring System for troubleshooting the Minuteman Missile Message Processing System.

Command History for 1990

DTIC Science & Technology

1991-05-01

Marine Corps Tiaining Systems (CBESS) memorization training Inteligence Center, Dam Neck Threat memorization training Commander Tactical Wings, Atlantic...News Shipbuilding Technical training AEGIS Training Center, Dare Artificial Intelligence (Al) Tools Computerized firm-end analysis tools NETSCPAC...Technology Department and provides computational and electronic mail support for research in areas of artificial intelligence, computer-assisted instruction

Intelligent tutoring systems research in the training systems division: Space applications

NASA Technical Reports Server (NTRS)

Regian, J. Wesley

1988-01-01

Computer-Aided Instruction (CAI) is a mature technology used to teach students in a wide variety of domains. The introduction of Artificial Intelligence (AI) technology of the field of CAI has prompted research and development efforts in an area known as Intelligent Computer-Aided Instruction (ICAI). In some cases, ICAI has been touted as a revolutionary alternative to traditional CAI. With the advent of powerful, inexpensive school computers, ICAI is emerging as a potential rival to CAI. In contrast to this, one may conceive of Computer-Based Training (CBT) systems as lying along a continuum which runs from CAI to ICAI. Although the key difference between the two is intelligence, there is not commonly accepted definition of what constitutes an intelligent instructional system.

A general architecture for intelligent training systems

NASA Technical Reports Server (NTRS)

Loftin, R. Bowen

1987-01-01

A preliminary design of a general architecture for autonomous intelligent training systems was developed. The architecture integrates expert system technology with teaching/training methodologies to permit the production of systems suitable for use by NASA, other government agencies, industry, and academia in the training of personnel for the performance of complex, mission-critical tasks. The proposed architecture consists of five elements: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The design of this architecture was guided and its efficacy tested through the development of a system for use by Mission Control Center Flight Dynamics Officers in training to perform Payload-Assist Module Deploys from the orbiter.

Design and Effectiveness of Intelligent Tutors for Operators of Complex Dynamic Systems: A Tutor Implementation for Satellite System Operators.

ERIC Educational Resources Information Center

Mitchell, Christine M.; Govindaraj, T.

1990-01-01

Discusses the use of intelligent tutoring systems as opposed to traditional on-the-job training for training operators of complex dynamic systems and describes the computer architecture for a system for operators of a NASA (National Aeronautics and Space Administration) satellite control system. An experimental evaluation with college students is…

Intelligent Augmented Reality Training for Motherboard Assembly

ERIC Educational Resources Information Center

Westerfield, Giles; Mitrovic, Antonija; Billinghurst, Mark

2015-01-01

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

28 CFR 16.96 - Exemption of Federal Bureau of Investigation Systems-limited access.

Code of Federal Regulations, 2010 CFR

2010-07-01

...) would limit the ability of trained investigators and intelligence analysts to exercise their judgment in reporting on investigations and impede the development of criminal intelligence necessary for effective law... subsection (e)(5) would limit the ability of trained investigators and intelligence analysts to exercise...

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.

The Impact of Critical Thinking Strategies on Curriculum and Instruction for USAF Operations Intelligence

ERIC Educational Resources Information Center

Baker, Jason R.

2017-01-01

The goals of the present action research study were to understand intelligence analysts' perceptions of weapon systems visual recognition ("vis-recce") training and to determine the impact of a Critical Thinking Training (CTT) Seminar and Formative Assessments on unit-level intelligence analysts' "vis-recce" performance at a…

Intelligent Computerized Training System

NASA Technical Reports Server (NTRS)

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

1991-01-01

Intelligent computer-aided training system gives trainees same experience gained from best on-the-job training. Automated system designed to emulate behavior of experienced teacher devoting full time and attention to training novice. Proposes challenging training scenarios, monitors and evaluates trainee's actions, makes meaningful comments in response to errors, reponds to requests for information, gives hints when appropriate, and remembers strengths and weaknesses so it designs suitable exercises. Used to train flight-dynamics officers in deploying satellites from Space Shuttle. Adapted to training for variety of tasks and situations, simply by modifying one or at most two of its five modules. Helps to ensure continuous supply of trained specialists despite scarcity of experienced and skilled human trainers.

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.

Artificial Intelligence and Its Potential as an Aid to Vocational Training and Education.

ERIC Educational Resources Information Center

Aleksander, I.; And Others

This document contains a series of papers which attempt to de-mystify the subject of artificial intelligence and to show how some countries in the European Community (EC) are approaching the promotion of development and application of artificial intelligence systems that can be used as an aid in vocational training programs, as well as to…

Proceedings of the 1993 Conference on Intelligent Computer-Aided Training and Virtual Environment Technology, Volume 1

NASA Technical Reports Server (NTRS)

Hyde, Patricia R.; Loftin, R. Bowen

1993-01-01

These proceedings are organized in the same manner as the conference's contributed sessions, with the papers grouped by topic area. These areas are as follows: VE (virtual environment) training for Space Flight, Virtual Environment Hardware, Knowledge Aquisition for ICAT (Intelligent Computer-Aided Training) & VE, Multimedia in ICAT Systems, VE in Training & Education (1 & 2), Virtual Environment Software (1 & 2), Models in ICAT systems, ICAT Commercial Applications, ICAT Architectures & Authoring Systems, ICAT Education & Medical Applications, Assessing VE for Training, VE & Human Systems (1 & 2), ICAT Theory & Natural Language, ICAT Applications in the Military, VE Applications in Engineering, Knowledge Acquisition for ICAT, and ICAT Applications in Aerospace.

Applications of intelligent computer-aided training

NASA Technical Reports Server (NTRS)

Loftin, R. B.; Savely, Robert T.

1991-01-01

Intelligent computer-aided training (ICAT) systems simulate the behavior of an experienced instructor observing a trainee, responding to help requests, diagnosing and remedying trainee errors, and proposing challenging new training scenarios. This paper presents a generic ICAT architecture that supports the efficient development of ICAT systems for varied tasks. In addition, details of ICAT projects, built with this architecture, that deliver specific training for Space Shuttle crew members, ground support personnel, and flight controllers are presented. Concurrently with the creation of specific ICAT applications, a general-purpose software development environment for ICAT systems is being built. The widespread use of such systems for both ground-based and on-orbit training will serve to preserve task and training expertise, support the training of large numbers of personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences.

[Remote intelligent Brunnstrom assessment system for upper limb rehabilitation for post-stroke based on extreme learning machine].

PubMed

Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang

2014-04-01

In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.

Cognitive Task Analysis and Intelligent Computer-Based Training Systems: Lessons Learned from Coached Practice Environments in Air Force Avionics.

ERIC Educational Resources Information Center

Katz, Sandra N.; Hall, Ellen; Lesgold, Alan

This paper describes some results of a collaborative effort between the University of Pittsburgh and the Air Force to develop advanced troubleshooting training for F-15 maintenance technicians. The focus is on the cognitive task methodology used in the development of three intelligent tutoring systems to inform their instructional content and…

The development of expertise using an intelligent computer-aided training system

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele

1991-01-01

An initial examination was conducted of an Intelligent Tutoring System (ITS) developed for use in industry. The ITS, developed by NASA, simulated a satellite deployment task. More specifically, the PD (Payload Assist Module Deployment)/ICAT (Intelligent Computer Aided Training) System simulated a nominal Payload Assist Module (PAM) deployment. The development of expertise on this task was examined using three Flight Dynamics Officer (FDO) candidates who has no previous experience with this task. The results indicated that performance improved rapidly until Trial 5, followed by more gradual improvements through Trial 12. The performance dimensions measured included performance speed, actions completed, errors, help required, and display fields checked. Suggestions for further refining the software and for deciding when to expose trainees to more difficult task scenarios are discussed. Further, the results provide an initial demonstration of the effectiveness of the PD/ICAT system in training the nominal PAM deployment task and indicate the potential benefits of using ITS's for training other FDO tasks.

Toward an embedded training tool for Deep Space Network operations

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Sturdevant, Kathryn F.; Johnson, W. L.

1993-01-01

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Integrated Intelligent training and job aiding for combustion turbine engines

NASA Technical Reports Server (NTRS)

Mckeithan, Clifford M., Jr.; Quentin, George H.

1993-01-01

This paper describes an ongoing program to augment such an expert system gas turbine startup advisor, known as the EPRI SA VANT System, by including an intelligent training package. It will give a brief background on the SA VANT development and an overview of its evolution into a full-blown Gas Turbine Information System (GTIS) for rapid access of on-line documentation, diagnostics, and training. In particular, the paper will address: (1) the conversion of the knowledge base used by the SA VANT startup advisor so that it can be used for both training and job aiding; and (2) the hypertext-oriented user manuals being incorporated into the system for rapidly accessing on-line documentation at the job site.

An intelligent simulation training system

NASA Technical Reports Server (NTRS)

Biegel, John E.

1990-01-01

The Department of Industrial Engineering at the University of Central Florida, Embry-Riddle Aeronautical University and General Electric (SCSD) have been funded by the State of Florida to build an Intelligent Simulation Training System. The objective was and is to make the system generic except for the domain expertise. Researchers accomplished this objective in their prototype. The system is modularized and therefore it is easy to make any corrections, expansions or adaptations. The funding by the state of Florida has exceeded $3 million over the past three years and through the 1990 fiscal year. UCF has expended in excess of 15 work years on the project. The project effort has been broken into three major tasks. General Electric provides the simulation. Embry-Riddle Aeronautical University provides the domain expertise. The University of Central Florida has constructed the generic part of the system which is comprised of several modules that perform the tutoring, evaluation, communication, status, etc. The generic parts of the Intelligent Simulation Training Systems (ISTS) are described.

An intelligent tutoring system for space shuttle diagnosis

NASA Technical Reports Server (NTRS)

Johnson, William B.; Norton, Jeffrey E.; Duncan, Phillip C.

1988-01-01

An Intelligent Tutoring System (ITS) transcends conventional computer-based instruction. An ITS is capable of monitoring and understanding student performance thereby providing feedback, explanation, and remediation. This is accomplished by including models of the student, the instructor, and the expert technician or operator in the domain of interest. The space shuttle fuel cell is the technical domain for the project described below. One system, Microcomputer Intelligence for Technical Training (MITT), demonstrates that ITS's can be developed and delivered, with a reasonable amount of effort and in a short period of time, on a microcomputer. The MITT system capitalizes on the diagnostic training approach called Framework for Aiding the Understanding of Logical Troubleshooting (FAULT) (Johnson, 1987). The system's embedded procedural expert was developed with NASA's C-Language Integrated Production (CLIP) expert system shell (Cubert, 1987).

AI in Computer-Based Training

ERIC Educational Resources Information Center

Camstra, Bert

2008-01-01

In this paper, intelligent approaches to CBT are put into several perspectives in an attempt to elucidate the concepts and give them a more realistic (and not only glamorous) footing. The role of expert systems in training is explored and possible routes towards intelligent CBT are outlined. [This paper was first published in "Interactive Learning…

Review on the Traction System Sensor Technology of a Rail Transit Train.

PubMed

Feng, Jianghua; Xu, Junfeng; Liao, Wu; Liu, Yong

2017-06-11

The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed.

Review on the Traction System Sensor Technology of a Rail Transit Train

PubMed Central

Feng, Jianghua; Xu, Junfeng; Liao, Wu; Liu, Yong

2017-01-01

The development of high-speed intelligent rail transit has increased the number of sensors applied on trains. These play an important role in train state control and monitoring. These sensors generally work in a severe environment, so the key problem for sensor data acquisition is to ensure data accuracy and reliability. In this paper, we follow the sequence of sensor signal flow, present sensor signal sensing technology, sensor data acquisition, and processing technology, as well as sensor fault diagnosis technology based on the voltage, current, speed, and temperature sensors which are commonly used in train traction systems. Finally, intelligent sensors and future research directions of rail transit train sensors are discussed. PMID:28604615

Urban transportation : challenges to widespread deployment of intelligent transportation systems : report to Congressional committees

DOT National Transportation Integrated Search

The federal government can take programmatic and financial actions to : promote the deployment of intelligent transportation systems. The : programmatic actions include providing technical assistance and training : to state and local officials, disse...

Developing a Cognitive Model of Expert Performance for Ship Navigation Maneuvers in an Intelligent Tutoring System

DTIC Science & Technology

2010-03-01

nature of ship navigation and the requirements for the intelligent tutor presented unique challenges for development. This paper describes how the...the context of improving training. 1. Project Overview The Conning Officer Virtual Environment (COVE) is a ship-handling simulation system used...Corporation, 2009), is used to provide students with ship-handling training without the cost or risk to equipment of at-sea exercises. One downside

Characteristics of an ITS that evolves from tutor to operator's assistant. [intelligent tutoring system

NASA Technical Reports Server (NTRS)

Chu, R. W.; Mitchell, C. M.; Govindaraj, T.

1989-01-01

This paper discusses the motivation and goals of a research project which addresses the problems and issues of operator training in complex engineering sytems. The research proposes a tutor/aid paradigm for the design of an intelligent tutoring system (ITS) that evolves from a tutor to an operator's assistant for supervisory control of complex dynamic systems. Characteristics of an intelligent tutoring/aiding system are identified with respect to the representation of domain knowledge, the tutor's pedagogical structure, and the student knowledge representation. The research represents a first step in the design of an intelligent complex dynamic systems.

Intelligent systems for human resources.

PubMed

Kline, K B

1988-11-01

An intelligent system contains knowledge about some domain; it has sophisticated decision-making processes and the ability to explain its actions. The most important aspect of an intelligent system is its ability to effectively interact with humans to teach or assist complex information processing. Two intelligent systems are Intelligent Tutoring Systems (ITs) and Expert Systems. The ITSs provide instruction to a student similar to a human tutor. The ITSs capture individual performance and tutor deficiencies. These systems consist of an expert module, which contains the knowledge or material to be taught; the student module, which contains a representation of the knowledge the student knows and does not know about the domain; and the instructional or teaching module, which selects specific knowledge to teach, the instructional strategy, and provides assistance to the student to tutor deficiencies. Expert systems contain an expert's knowledge about some domain and perform specialized tasks or aid a novice in the performance of certain tasks. The most important part of an expert system is the knowledge base. This knowledge base contains all the specialized and technical knowledge an expert possesses. For an expert system to interact effectively with humans, it must have the ability to explain its actions. Use of intelligent systems can have a profound effect on human resources. The ITSs can provide better training by tutoring on an individual basis, and the expert systems can make better use of human resources through job aiding and performing complex tasks. With increasing training requirements and "doing more with less," intelligent systems can have a positive effect on human resources.

CASTE (Course Assembly System and Tutorial Environment) and CVI: (Combat Vehicle Identification) A First Application of an Intelligent Tutorial System to Combat Vehicle Identification.

DTIC Science & Technology

1984-09-01

based training systems and hence to realize an embedded trainer that is both intelligent and effective . The o(Continued) DO,; FOAM AM 71 1ឹ...Performance Effectiveness and Simulation Approved for public releate; dlitribution unlimited iii &a3laAfc*ia £&&etaL* ■’—’,£-«.■£./■.,’-f...oriented approaches to computer-based training systems and hence realise an embedded trainer that is both intelli- gent and effective . To this end

Research into the interaction between high performance and cognitive skills in an intelligent tutoring system

NASA Technical Reports Server (NTRS)

Fink, Pamela K.

1991-01-01

Two intelligent tutoring systems were developed. These tutoring systems are being used to study the effectiveness of intelligent tutoring systems in training high performance tasks and the interrelationship of high performance and cognitive tasks. The two tutoring systems, referred to as the Console Operations Tutors, were built using the same basic approach to the design of an intelligent tutoring system. This design approach allowed researchers to more rapidly implement the cognitively based tutor, the OMS Leak Detect Tutor, by using the foundation of code generated in the development of the high performance based tutor, the Manual Select Keyboard (MSK). It is believed that the approach can be further generalized to develop a generic intelligent tutoring system implementation tool.

Training effectiveness of an intelligent tutoring system for a propulsion console trainer

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele

1990-01-01

A formative evaluation was conducted on an Intelligent Tutoring System (ITS) developed for tasks performed on the Propulsion Console. The ITS, which was developed primarily as a research tool, provides training on use of the Manual Select Keyboard (MSK). Three subjects completed three phases of training using the ITS: declarative, speed, and automaticity training. Data were collected on several performance dimensions, including training time, number of trials performed in each training phase, and number of errors. Information was also collected regarding the user interface and content of training. Suggestions for refining the ITS are discussed. Further, future potential uses and limitations of the ITS are discussed. The results provide an initial demonstration of the effectiveness of the Propulsion Console ITS and indicate the potential benefits of this form of training tool for related tasks.

Computational intelligence and neuromorphic computing potential for cybersecurity applications

NASA Astrophysics Data System (ADS)

Pino, Robinson E.; Shevenell, Michael J.; Cam, Hasan; Mouallem, Pierre; Shumaker, Justin L.; Edwards, Arthur H.

2013-05-01

In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neurobiological processes and form the foundation for intelligent system architectures.

Intelligent Instructional Systems in Military Training.

ERIC Educational Resources Information Center

Fletcher, J.D.; Zdybel, Frank

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

Intelligent computer aided training systems in the real world: Making the technology accessible to the educational mainstream

NASA Technical Reports Server (NTRS)

Kovarik, Madeline

1993-01-01

Intelligent computer aided training systems hold great promise for the application of this technology to mainstream education and training. Yet, this technology, which holds such a vast potential impact for the future of education and training, has had little impact beyond the enclaves of government research labs. This is largely due to the inaccessibility of the technology to those individuals in whose hands it can have the greatest impact, teachers and educators. Simply throwing technology at an educator and expecting them to use it as an effective tool is not the answer. This paper provides a background into the use of technology as a training tool. MindLink, developed by HyperTech Systems, provides trainers with a powerful rule-based tool that can be integrated directly into a Windows application. By embedding expert systems technology it becomes more accessible and easier to master.

The development of expertise on an intelligent tutoring system

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele

1989-01-01

An initial examination was conducted of an Intelligent Tutoring System (ITS) developed for use in industry. The ITS, developed by NASA, simulated a satellite deployment task. More specifically, the PD (Payload Assist Module Deployment)/ICAT (Intelligent Computer Aided Training) System simulated a nominal Payload Assist Module (PAM) deployment. The development of expertise on this task was examined using three Flight Dynamics Officer (FDO) candidates who had no previous experience with this task. The results indicated that performance improved rapidly until Trial 5, followed by more gradual improvements through Trial 12. The performance dimensions measured included performance speed, actions completed, errors, help required, and display fields checked. Suggestions for further refining the software and for deciding when to expose trainees to more difficult task scenarios are discussed. Further, the results provide an initial demonstration of the effectiveness of the PD/ICAT system in training the nominal PAM deployment task and indicate the potential benefits of using ITS's for training other FDO tasks.

Relationship between the components of on-site training and emotional intelligence in the librarians of Isfahan University of Medical Sciences and Isfahan University with moderating role of personality characteristics

PubMed Central

Sayadi, Saeed; Safdarian, Ali; Khayeri, Behnaz

2015-01-01

Introduction: Training the man power is an inevitable necessity that the organizations need in order to survive and develop in today changing world. Aims: The aim of the present study is to identify the relationship between the components of on-site training and emotional intelligence in librarians of Isfahan University of Medical Sciences and Isfahan University with moderating role of personality characteristics. Settings and Design: Descriptive correlation method was used in the present study. The statistical population of the study was all of the 157 librarians of Isfahan University of Medical Sciences and Isfahan University from whom the appointed individuals were selected through random sampling method. Subjects and Methods: The research tools included the researcher-made questionnaire of investigating the effectiveness of on-site training system and two other standard questionnaires of Shrink emotional intelligence, and NEO personality questionnaire, which all of them had the needed reliability and validity. Statistical Analysis: The descriptive indices (distribution and mean) and also the inferential methods (Pearson correlation, regression analysis and analysis of variance) were used through applying version 20 of SPSS software to analyze the obtained data. Results: There was a significant relationship with certainty level of 95% between the components of on-site training with emotional intelligence in those who obtained low grades in the features of being extrovert and between the individual aspects of on-site training with emotional intelligence in those who got higher grades in the characteristic of being extrovert. Conclusion: The emotional intelligence is a promotable skill and considering the existence of a significant relationship between some components of emotional intelligence and on-site training, these skills can be institutionalized through conducting mentioned educational courses. PMID:27462631

Artificial Intelligence: An Analysis of the Technology for Training. Training and Development Research Center Project Number Fourteen.

ERIC Educational Resources Information Center

Sayre, Scott Alan

The ultimate goal of the science of artificial intelligence (AI) is to establish programs that will use algorithmic computer techniques to imitate the heuristic thought processes of humans. Most AI programs, especially expert systems, organize their knowledge into three specific areas: data storage, a rule set, and a control structure. Limitations…

Training + Technology: The Future Is Now.

ERIC Educational Resources Information Center

Heathman, Dena J.; Kleiner, Brian H.

1991-01-01

New applications of computer-assisted training being developed include telecommunications, artificial intelligence, soft skills training, and performance support systems. Barriers to acceptance are development time, costs, and lack of human contact. (SK)

Artificial intelligence: Learning to see and act

NASA Astrophysics Data System (ADS)

Schölkopf, Bernhard

2015-02-01

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

Training Engineers for the Ambient Intelligence Challenge

ERIC Educational Resources Information Center

Corno, Fulvio; De Russis, Luigi

2017-01-01

The increasing complexity of the new breed of distributed intelligent systems, such as the Internet of Things, which require a diversity of languages and protocols, can only be tamed with design and programming best practices. Interest is also growing for including the human factor, as advocated by the "ambient intelligence" (AmI)…

Investigation of a Neural Network Implementation of a TCP Packet Anomaly Detection System

DTIC Science & Technology

2004-05-01

reconnatre les nouvelles variantes d’attaque. Les réseaux de neurones artificiels (ANN) ont les capacités d’apprendre à partir de schémas et de...Computational Intelligence Techniques in Intrusion Detection Systems. In IASTED International Conference on Neural Networks and Computational Intelligence , pp...Neural Network Training: Overfitting May be Harder than Expected. In Proceedings of the Fourteenth National Conference on Artificial Intelligence , AAAI-97

A Common Cockpit Training System

DTIC Science & Technology

2005-01-01

a learning environment where students can practice ASW via free - play simulated tactical situations while receiving feedback and instruction customized...Mission Display and includes free play simulation capability to maximize training. This intelligent tutoring system (ITS) will observe the operator’s

Understanding the Impact of Intelligent Tutoring Agents on Real-Time Training Simulations

DTIC Science & Technology

2011-01-01

environments has increased. Intelligent Tutoring Systems (ITS) technology may include reactive or proactive simulation agents that monitor and... environments . These reactive agents monitor the trainee’s progress and provide hints or other feedback only when there is sufficient variance from... agents have a higher computational cost in that they need to sense and understand more about the trainee, environment and training context, but are

Intelligent transportation systems Professional Capacity Building Program : ITS training & education needs assessment baseline : a review and synthesis of thirteen prior studies, field interviews, and a summary assessment of ITS needs

DOT National Transportation Integrated Search

1997-12-01

Successful deployment, operation, and management of Intelligent Transportation Systems (ITS) requires a new breed of transportation professionals, according to research, extensive outreach, and information gathered to date. The U.S. DOT has responded...

Developing an Intelligent Computer-Aided Trainer

NASA Technical Reports Server (NTRS)

Hua, Grace

1990-01-01

The Payload-assist module Deploys/Intelligent Computer-Aided Training (PD/ICAT) system was developed as a prototype for intelligent tutoring systems with the intention of seeing PD/ICAT evolve and produce a general ICAT architecture and development environment that can be adapted by a wide variety of training tasks. The proposed architecture is composed of a user interface, a domain expert, a training session manager, a trainee model and a training scenario generator. The PD/ICAT prototype was developed in the LISP environment. Although it has been well received by its peers and users, it could not be delivered toe its end users for practical use because of specific hardware and software constraints. To facilitate delivery of PD/ICAT to its users and to prepare for a more widely accepted development and delivery environment for future ICAT applications, we have ported this training system to a UNIX workstation and adopted use of a conventional language, C, and a C-based rule-based language, CLIPS. A rapid conversion of the PD/ICAT expert system to CLIPS was possible because the knowledge was basically represented as a forward chaining rule base. The resulting CLIPS rule base has been tested successfully in other ICATs as well. Therefore, the porting effort has proven to be a positive step toward our ultimate goal of building a general purpose ICAT development environment.

Patient positioning using artificial intelligence neural networks, trained magnetic field sensors and magnetic implants.

PubMed

Lennernäs, B; Edgren, M; Nilsson, S

1999-01-01

The purpose of this study was to evaluate the precision of a sensor and to ascertain the maximum distance between the sensor and the magnet, in a magnetic positioning system for external beam radiotherapy using a trained artificial intelligence neural network for position determination. Magnetic positioning for radiotherapy, previously described by Lennernäs and Nilsson, is a functional technique, but it is time consuming. The sensors are large and the distance between the sensor and the magnetic implant is limited to short distances. This paper presents a new technique for positioning, using an artificial intelligence neural network, which was trained to position the magnetic implant with at least 0.5 mm resolution in X and Y dimensions. The possibility of using the system for determination in the Z dimension, that is the distance between the magnet and the sensor, was also investigated. After training, this system positioned the magnet with a mean error of maximum 0.15 mm in all dimensions and up to 13 mm from the sensor. Of 400 test positions, 8 determinations had an error larger than 0.5 mm, maximum 0.55 mm. A position was determined in approximately 0.01 s.

Increases in Emotional Intelligence After an Online Training Program Are Associated With Better Decision-Making on the Iowa Gambling Task.

PubMed

Alkozei, Anna; Smith, Ryan; Demers, Lauren A; Weber, Mareen; Berryhill, Sarah M; Killgore, William D S

2018-01-01

Higher levels of emotional intelligence have been associated with better inter and intrapersonal functioning. In the present study, 59 healthy men and women were randomized into either a three-week online training program targeted to improve emotional intelligence ( n = 29), or a placebo control training program targeted to improve awareness of nonemotional aspects of the environment ( n = 30). Compared to placebo, participants in the emotional intelligence training group showed increased performance on the total emotional intelligence score of the Mayer-Salovey-Caruso Emotional Intelligence Test, a performance measure of emotional intelligence, as well as subscales of perceiving emotions and facilitating thought. Moreover, after emotional intelligence training, but not after placebo training, individuals displayed the ability to arrive at optimal performance faster (i.e., they showed a faster learning rate) during an emotion-guided decision-making task (i.e., the Iowa Gambling Task). More specifically, although both groups showed similar performance at the start of the Iowa Gambling Task from pre- to posttraining, the participants in the emotional intelligence training group learned to choose more advantageous than disadvantageous decks than those in the placebo training group by the time they reached the "hunch" period of the task (i.e., the point in the task when implicit task learning is thought to have occurred). Greater total improvements in performance on the Iowa Gambling Task from pre- to posttraining in the emotional intelligence training group were also positively correlated with pre- to posttraining changes in Mayer-Salovey-Caruso Emotional Intelligence Test scores, in particular with changes in the ability to perceive emotions. The present study provides preliminary evidence that emotional intelligence can be trained with the help of an online training program targeted at adults; it also suggests that changes in emotional intelligence, as a result of such a program, can lead to improved emotion-guided decision-making.

Predicting Correctness of Problem Solving from Low-Level Log Data in Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Hord, Casey

2009-01-01

This paper proposes a learning based method that can automatically determine how likely a student is to give a correct answer to a problem in an intelligent tutoring system. Only log files that record students' actions with the system are used to train the model, therefore the modeling process doesn't require expert knowledge for identifying…

The relationship between intelligence and training gains is moderated by training strategy.

PubMed

Lee, Hyunkyu; Boot, Walter R; Baniqued, Pauline L; Voss, Michelle W; Prakash, Ruchika Shaurya; Basak, Chandramallika; Kramer, Arthur F

2015-01-01

We examined the relationship between training regimen and fluid intelligence in the learning of a complex video game. Fifty non-game-playing young adults were trained on a game called Space Fortress for 30 hours with one of two training regimens: (1) Hybrid Variable-Priority Training (HVT), with part-task training and a focus on improving specific skills and managing task priorities, and (2) Full Emphasis Training (FET) in which participants practiced the whole game to obtain the highest overall score. Fluid intelligence was measured with the Raven's Progressive Matrix task before training. With FET, fluid intelligence was positively associated with learning, suggesting that intellectual ability played a substantial role in determining individual differences in training success. In contrast, with HVT, fluid intelligence was not associated with learning, suggesting that individual differences in fluid intelligence do not factor into training success in a regimen that emphasizes component tasks and flexible task coordination. By analyzing training effects in terms of individual differences and training regimens, the current study offers a training approach that minimizes the potentially limiting effect of individual differences.

Intelligent hypertext manual development for the Space Shuttle hazardous gas detection system

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Hoyt, W. Andes

1989-01-01

This research is designed to utilize artificial intelligence (AI) technology to increase the efficiency of personnel involved with monitoring the space shuttle hazardous gas detection systems at the Marshall Space Flight Center. The objective is to create a computerized service manual in the form of a hypertext and expert system which stores experts' knowledge and experience. The resulting Intelligent Manual will assist the user in interpreting data timely, in identifying possible faults, in locating the applicable documentation efficiently, in training inexperienced personnel effectively, and updating the manual frequently as required.

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

ERIC Educational Resources Information Center

May, Donald M.; And Others

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

An Intelligent Simulator for Telerobotics Training

ERIC Educational Resources Information Center

Belghith, K.; Nkambou, R.; Kabanza, F.; Hartman, L.

2012-01-01

Roman Tutor is a tutoring system that uses sophisticated domain knowledge to monitor the progress of students and advise them while they are learning how to operate a space telerobotic system. It is intended to help train operators of the Space Station Remote Manipulator System (SSRMS) including astronauts, operators involved in ground-based…

Motorcycle Start-stop System based on Intelligent Biometric Voice Recognition

NASA Astrophysics Data System (ADS)

Winda, A.; E Byan, W. R.; Sofyan; Armansyah; Zariantin, D. L.; Josep, B. G.

2017-03-01

Current mechanical key in the motorcycle is prone to bulgary, being stolen or misplaced. Intelligent biometric voice recognition as means to replace this mechanism is proposed as an alternative. The proposed system will decide whether the voice is belong to the user or not and the word utter by the user is ‘On’ or ‘Off’. The decision voice will be sent to Arduino in order to start or stop the engine. The recorded voice is processed in order to get some features which later be used as input to the proposed system. The Mel-Frequency Ceptral Coefficient (MFCC) is adopted as a feature extraction technique. The extracted feature is the used as input to the SVM-based identifier. Experimental results confirm the effectiveness of the proposed intelligent voice recognition and word recognition system. It show that the proposed method produces a good training and testing accuracy, 99.31% and 99.43%, respectively. Moreover, the proposed system shows the performance of false rejection rate (FRR) and false acceptance rate (FAR) accuracy of 0.18% and 17.58%, respectively. In the intelligent word recognition shows that the training and testing accuracy are 100% and 96.3%, respectively.

Ability-Based Pairing Strategies in the Team-Based Training of a Complex Skill: Does the Intelligence of Your Training Partner Matter?

ERIC Educational Resources Information Center

Day, Eric Anthony; Arthur, Winfred Jr.; Bell, Suzanne T.; Edwards, Bryan D.; Bennett, Winston Jr.; Mendoza, Jorge L.; Tubre, Travis C.

2005-01-01

Intelligence researchers traditionally focus their attention on the individual level and overlook the role of intelligence at the interindividual level. This research investigated the interplay of the effects of intelligence at the individual and interindividual levels by manipulating the intelligence-based composition of dyadic training teams.…

Development of an intelligent surgical training system for Thoracentesis.

PubMed

Nakawala, Hirenkumar; Ferrigno, Giancarlo; De Momi, Elena

2018-01-01

Surgical training improves patient care, helps to reduce surgical risks, increases surgeon's confidence, and thus enhances overall patient safety. Current surgical training systems are more focused on developing technical skills, e.g. dexterity, of the surgeons while lacking the aspects of context-awareness and intra-operative real-time guidance. Context-aware intelligent training systems interpret the current surgical situation and help surgeons to train on surgical tasks. As a prototypical scenario, we chose Thoracentesis procedure in this work. We designed the context-aware software framework using the surgical process model encompassing ontology and production rules, based on the procedure descriptions obtained through textbooks and interviews, and ontology-based and marker-based object recognition, where the system tracked and recognised surgical instruments and materials in surgeon's hands and recognised surgical instruments on the surgical stand. The ontology was validated using annotated surgical videos, where the system identified "Anaesthesia" and "Aspiration" phase with 100% relative frequency and "Penetration" phase with 65% relative frequency. The system tracked surgical swab and 50mL syringe with approximately 88.23% and 100% accuracy in surgeon's hands and recognised surgical instruments with approximately 90% accuracy on the surgical stand. Surgical workflow training with the proposed system showed equivalent results as the traditional mentor-based training regime, thus this work is a step forward a new tool for context awareness and decision-making during surgical training. Copyright © 2017 Elsevier B.V. All rights reserved.

[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.

Failure of Working Memory Training to Enhance Cognition or Intelligence

PubMed Central

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

2013-01-01

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

An evaluation of training effectiveness of an intelligent tutoring system

NASA Technical Reports Server (NTRS)

Johnson, Debra Steele; Pieper, Kalen F.; Culbert, Chris

1992-01-01

The study evaluated the training effectiveness of an intelligent tutoring system (ITS) for the Remote Manipulator System (RMS). The study examined how well individuals learn the training content and skills from the RMS ITS and to what extent the content and skills learned using the ITS transfer to RMS task performance in the SES, a high fidelity simulator. Three astronauts completed 8 2-hour ITS sessions addressing movement in three coordinate systems, grapple, ungrapple, berth, and unberth procedures, and singularities and reach limits. Their performance was also observed in an SES training session. Performance data were collected using multiple measures: ITS task performance, transfer performance on the SES, a conceptual knowledge test, an opinion survey completed by astronauts, and comments and observations from astronauts and trainers. Results indicated the RMS ITS to be moderately effective and provided evidence of the efficacy of ITS's, in general. Comments and suggestions are provided relating to how the ITS could be improved and to enable decision makers to judge the effectiveness of the RMS ITS.

Artificial intelligence - New tools for aerospace project managers

NASA Technical Reports Server (NTRS)

Moja, D. C.

1985-01-01

Artificial Intelligence (AI) is currently being used for business-oriented, money-making applications, such as medical diagnosis, computer system configuration, and geological exploration. The present paper has the objective to assess new AI tools and techniques which will be available to assist aerospace managers in the accomplishment of their tasks. A study conducted by Brown and Cheeseman (1983) indicates that AI will be employed in all traditional management areas, taking into account goal setting, decision making, policy formulation, evaluation, planning, budgeting, auditing, personnel management, training, legal affairs, and procurement. Artificial intelligence/expert systems are discussed, giving attention to the three primary areas concerned with intelligent robots, natural language interfaces, and expert systems. Aspects of information retrieval are also considered along with the decision support system, and expert systems for project planning and scheduling.

SAFARI: An Environment for Creating Tutoring Systems in Industrial Training.

ERIC Educational Resources Information Center

Gecsei, J.; Frasson, C.

Safari is a cooperative project involving four Quebec universities, two industrial partners (Virtual Prototypes, Inc., providing the VAPS software package, and Novasys, Inc., a consulting firm specializing in artificial intelligence and training), and government. VAPS (Virtual Applications Prototyping System) is a commercial interface-building and…

Methods and means of diagnostics of oncological diseases on the basis of pattern recognition: intelligent morphological systems - problems and solutions

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.

2017-01-01

The development of methods of pattern recognition in modern intelligent systems of clinical cancer diagnosis are discussed. The histological (morphological) diagnosis - primary diagnosis for medical setting with cancer are investigated. There are proposed: interactive methods of recognition and structure of intellectual morphological complexes based on expert training-diagnostic and telemedicine systems. The proposed approach successfully implemented in clinical practice.

An integrated knowledge system for wind tunnel testing - Project Engineers' Intelligent Assistant

NASA Technical Reports Server (NTRS)

Lo, Ching F.; Shi, George Z.; Hoyt, W. A.; Steinle, Frank W., Jr.

1993-01-01

The Project Engineers' Intelligent Assistant (PEIA) is an integrated knowledge system developed using artificial intelligence technology, including hypertext, expert systems, and dynamic user interfaces. This system integrates documents, engineering codes, databases, and knowledge from domain experts into an enriched hypermedia environment and was designed to assist project engineers in planning and conducting wind tunnel tests. PEIA is a modular system which consists of an intelligent user-interface, seven modules and an integrated tool facility. Hypermedia technology is discussed and the seven PEIA modules are described. System maintenance and updating is very easy due to the modular structure and the integrated tool facility provides user access to commercial software shells for documentation, reporting, or database updating. PEIA is expected to provide project engineers with technical information, increase efficiency and productivity, and provide a realistic tool for personnel training.

Effects of cognitive training on the structure of intelligence.

PubMed

Protzko, John

2017-08-01

Targeted cognitive training, such as n-back or speed of processing training, in the hopes of raising intelligence is of great theoretical and practical importance. The most important theoretical contribution, however, is not about the malleability of intelligence. Instead, I argue the most important and novel theoretical contribution is understanding the causal structure of intelligence. The structure of intelligence, most often taken as a hierarchical factor structure, necessarily prohibits transfer from subfactors back up to intelligence. If this is the true structure, targeted cognitive training interventions will fail to increase intelligence not because intelligence is immutable, but simply because there is no causal connection between, say, working memory and intelligence. Seeing the structure of intelligence for what it is, a causal measurement model, allows us to focus testing on the presence and absence of causal links. If we can increase subfactors without transfer to other facets, we may be confirming the correct causal structure more than testing malleability. Such a blending into experimental psychometrics is a strong theoretical pursuit.

An intelligent position-specific training system for mission operations

NASA Technical Reports Server (NTRS)

Schneider, M. P.

1992-01-01

Marshall Space Flight Center's (MSFC's) payload ground controller training program provides very good generic training; however, ground controller position-specific training can be improved by including position-specific training systems in the training program. This report explains why MSFC needs to improve payload ground controller position-specific training. The report describes a generic syllabus for position-specific training systems, a range of system designs for position-specific training systems, and a generic development process for developing position-specific training systems. The report also describes a position-specific training system prototype that was developed for the crew interface coordinator payload operations control center ground controller position. The report concludes that MSFC can improve the payload ground controller training program by incorporating position-specific training systems for each ground controller position; however, MSFC should not develop position-specific training systems unless payload ground controller position experts will be available to participate in the development process.

Provision of Training for the IT Industry: The ELEVATE Project

NASA Astrophysics Data System (ADS)

Paraskakis, Iraklis; Konstantinidis, Andreas; Bouras, Thanassis; Perakis, Kostas; Pantelopoulos, Stelios; Hatziapostolou, Thanos

This paper will present ELEVATE that aims to deliver an innovative training, educational and certification environment integrating the application software to be taught with the training procedure. ELEVATE aspires to address the training needs of software development SMEs and the solution proposed is based on three basic notions: to provide competence training that is tailored to the needs of the individual trainee, to allow the trainee to carry out authentic activities as well as problem based learning that draws from real life scenarios and finally to allow for the assessment and certification of the skills and competences acquired. In order to achieve the desired results the ELEVATE architecture utilises an Interactive Interoperability Layer, an Intelligent Personalization Trainer as well as the Training, Evaluation & Certification component. As an end product, the ELEVATE project The ELEVATE pedagogical model is based on blended learning, the e-Training component (an intelligent system that provides tailored training) and Learning 2.0.

Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.

ERIC Educational Resources Information Center

Russell, Daniel M.; Pirolli, Peter

Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…

Development and Evaluation of an Adaptive Computerized Training System (ACTS). R&D Report 78-1.

ERIC Educational Resources Information Center

Knerr, Bruce W.; Nawrocki, Leon H.

This report describes the development of a computer based system designed to train electronic troubleshooting procedures. The ACTS uses artificial intelligence techniques to develop models of student and expert troubleshooting behavior as they solve a series of troubleshooting problems on the system. Comparisons of the student and expert models…

Proceedings of the Air Force Forum for Intelligent Tutoring Systems

DTIC Science & Technology

1989-04-01

interface help the students find facts? I recently developed an expert system that is used at the JFK Airport to help workers assign incoming planes to...of their errors and to make comparisons with optimal solution paths. Chapters 2, and 5 BIP, BIP II: Basic Instructional Program BIP applied knowledge...OFFICE SYMBOL 7a NAME OF MONITORING ORGANIZATION Center for Applied Artificial (If applicable) Training Systems Division Intelligence 1 6. ADDRESS (City

Genetic Fuzzy Trees for Intelligent Control of Unmanned Combat Aerial Vehicles

NASA Astrophysics Data System (ADS)

Ernest, Nicholas D.

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

The expert surgical assistant. An intelligent virtual environment with multimodal input.

PubMed

Billinghurst, M; Savage, J; Oppenheimer, P; Edmond, C

1996-01-01

Virtual Reality has made computer interfaces more intuitive but not more intelligent. This paper shows how an expert system can be coupled with multimodal input in a virtual environment to provide an intelligent simulation tool or surgical assistant. This is accomplished in three steps. First, voice and gestural input is interpreted and represented in a common semantic form. Second, a rule-based expert system is used to infer context and user actions from this semantic representation. Finally, the inferred user actions are matched against steps in a surgical procedure to monitor the user's progress and provide automatic feedback. In addition, the system can respond immediately to multimodal commands for navigational assistance and/or identification of critical anatomical structures. To show how these methods are used we present a prototype sinus surgery interface. The approach described here may easily be extended to a wide variety of medical and non-medical training applications by making simple changes to the expert system database and virtual environment models. Successful implementation of an expert system in both simulated and real surgery has enormous potential for the surgeon both in training and clinical practice.

Intelligent computer-aided training authoring environment

NASA Technical Reports Server (NTRS)

Way, Robert D.

1994-01-01

Although there has been much research into intelligent tutoring systems (ITS), there are few authoring systems available that support ITS metaphors. Instructional developers are generally obliged to use tools designed for creating on-line books. We are currently developing an authoring environment derived from NASA's research on intelligent computer-aided training (ICAT). The ICAT metaphor, currently in use at NASA has proven effective in disciplines from satellite deployment to high school physics. This technique provides a personal trainer (PT) who instructs the student using a simulated work environment (SWE). The PT acts as a tutor, providing individualized instruction and assistance to each student. Teaching in an SWE allows the student to learn tasks by doing them, rather than by reading about them. This authoring environment will expedite ICAT development by providing a tool set that guides the trainer modeling process. Additionally, this environment provides a vehicle for distributing NASA's ICAT technology to the private sector.

Training and Personnel Systems Technology R and D Program Description FY 93

DTIC Science & Technology

1992-07-24

instructional strategies provide the best training in ICAT applications, and (c) demonstration of microcomputer authoring techniques for rapid development...learning strategies for language training, (b) develop a behavioral taxonomy to evaluate Military Intelligence (MI) performance and to characterize the...training requirements for collective tasks. In FY93, plans are to: (a) develop training strategies for sustaining command and control skills, and (b

A Potential Spatial Working Memory Training Task to Improve Both Episodic Memory and Fluid Intelligence

PubMed Central

Rudebeck, Sarah R.; Bor, Daniel; Ormond, Angharad; O’Reilly, Jill X.; Lee, Andy C. H.

2012-01-01

One current challenge in cognitive training is to create a training regime that benefits multiple cognitive domains, including episodic memory, without relying on a large battery of tasks, which can be time-consuming and difficult to learn. By giving careful consideration to the neural correlates underlying episodic and working memory, we devised a computerized working memory training task in which neurologically healthy participants were required to monitor and detect repetitions in two streams of spatial information (spatial location and scene identity) presented simultaneously (i.e. a dual n-back paradigm). Participants’ episodic memory abilities were assessed before and after training using two object and scene recognition memory tasks incorporating memory confidence judgments. Furthermore, to determine the generalizability of the effects of training, we also assessed fluid intelligence using a matrix reasoning task. By examining the difference between pre- and post-training performance (i.e. gain scores), we found that the trainers, compared to non-trainers, exhibited a significant improvement in fluid intelligence after 20 days. Interestingly, pre-training fluid intelligence performance, but not training task improvement, was a significant predictor of post-training fluid intelligence improvement, with lower pre-training fluid intelligence associated with greater post-training gain. Crucially, trainers who improved the most on the training task also showed an improvement in recognition memory as captured by d-prime scores and estimates of recollection and familiarity memory. Training task improvement was a significant predictor of gains in recognition and familiarity memory performance, with greater training improvement leading to more marked gains. In contrast, lower pre-training recollection memory scores, and not training task improvement, led to greater recollection memory performance after training. Our findings demonstrate that practice on a single working memory task can potentially improve aspects of both episodic memory and fluid intelligence, and that an extensive training regime with multiple tasks may not be necessary. PMID:23209740

A potential spatial working memory training task to improve both episodic memory and fluid intelligence.

PubMed

Rudebeck, Sarah R; Bor, Daniel; Ormond, Angharad; O'Reilly, Jill X; Lee, Andy C H

2012-01-01

One current challenge in cognitive training is to create a training regime that benefits multiple cognitive domains, including episodic memory, without relying on a large battery of tasks, which can be time-consuming and difficult to learn. By giving careful consideration to the neural correlates underlying episodic and working memory, we devised a computerized working memory training task in which neurologically healthy participants were required to monitor and detect repetitions in two streams of spatial information (spatial location and scene identity) presented simultaneously (i.e. a dual n-back paradigm). Participants' episodic memory abilities were assessed before and after training using two object and scene recognition memory tasks incorporating memory confidence judgments. Furthermore, to determine the generalizability of the effects of training, we also assessed fluid intelligence using a matrix reasoning task. By examining the difference between pre- and post-training performance (i.e. gain scores), we found that the trainers, compared to non-trainers, exhibited a significant improvement in fluid intelligence after 20 days. Interestingly, pre-training fluid intelligence performance, but not training task improvement, was a significant predictor of post-training fluid intelligence improvement, with lower pre-training fluid intelligence associated with greater post-training gain. Crucially, trainers who improved the most on the training task also showed an improvement in recognition memory as captured by d-prime scores and estimates of recollection and familiarity memory. Training task improvement was a significant predictor of gains in recognition and familiarity memory performance, with greater training improvement leading to more marked gains. In contrast, lower pre-training recollection memory scores, and not training task improvement, led to greater recollection memory performance after training. Our findings demonstrate that practice on a single working memory task can potentially improve aspects of both episodic memory and fluid intelligence, and that an extensive training regime with multiple tasks may not be necessary.

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.

Training the Body: The Potential of AIED to Support Personalized Motor Skills Learning

ERIC Educational Resources Information Center

Santos, Olga C.

2016-01-01

This paper argues that the research field of Artificial Intelligence in Education (AIED) can benefit from integrating recent technological advances (e.g., wearable devices, big data processing, 3D modelling, 3D printing, ambient intelligence) and design methodologies, such as TORMES, when developing systems that address the psychomotor learning…

The ZOG Technology Demonstration Project: A System Evaluation of USS CARL VINSON (CVN 70)

DTIC Science & Technology

1984-12-01

part of a larger project involving development of a wide range of computer technologies, including artifcial intelligence and a long-range computer...shipboard manage- ment, aircraft management, expert systems, menu selection, man- machine interface, artificial intelligence , automation; shipboard It AWM...functions, planning, evaluation, training, hierarchical data bases The objective of this project was to conduct an evaluation of ZOG, a general purpose

Effects of intelligibility on working memory demand for speech perception.

PubMed

Francis, Alexander L; Nusbaum, Howard C

2009-08-01

Understanding low-intelligibility speech is effortful. In three experiments, we examined the effects of intelligibility on working memory (WM) demands imposed by perception of synthetic speech. In all three experiments, a primary speeded word recognition task was paired with a secondary WM-load task designed to vary the availability of WM capacity during speech perception. Speech intelligibility was varied either by training listeners to use available acoustic cues in a more diagnostic manner (as in Experiment 1) or by providing listeners with more informative acoustic cues (i.e., better speech quality, as in Experiments 2 and 3). In the first experiment, training significantly improved intelligibility and recognition speed; increasing WM load significantly slowed recognition. A significant interaction between training and load indicated that the benefit of training on recognition speed was observed only under low memory load. In subsequent experiments, listeners received no training; intelligibility was manipulated by changing synthesizers. Improving intelligibility without training improved recognition accuracy, and increasing memory load still decreased it, but more intelligible speech did not produce more efficient use of available WM capacity. This suggests that perceptual learning modifies the way available capacity is used, perhaps by increasing the use of more phonetically informative features and/or by decreasing use of less informative ones.

Metacognitive Prompt Overdose: Positive and Negative Effects of Prompts in iSTART

ERIC Educational Resources Information Center

McCarthy, Kathryn S.; Johnson, Amy M.; Likens, Aaron D.; Martin, Zachary; McNamara, Danielle S.

2017-01-01

Interactive Strategy Training for Active Reading and Thinking (iSTART) is an intelligent tutoring system that supports reading comprehension through self-explanation (SE) training. This study tested how two metacognitive features, presented in a 2 x 2 design, affected students' SE scores during training. The "performance notification"…

Artificial Intelligence Applications to High-Technology Training.

ERIC Educational Resources Information Center

Dede, Christopher

1987-01-01

Discusses the use of artificial intelligence to improve occupational instruction in complex subjects with high performance goals, such as those required for high-technology jobs. Highlights include intelligent computer assisted instruction, examples in space technology training, intelligent simulation environments, and the need for adult training…

Innovative applications of artificial intelligence

NASA Astrophysics Data System (ADS)

Schorr, Herbert; Rappaport, Alain

Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

Building professional capacity in ITS : guidelines for designing an individualized training and education plan

DOT National Transportation Integrated Search

1999-04-01

This document presents a guide for educating and training transportation professionals on skills for Intelligent Transportation Systems (ITS). It identifies twenty ideal roles that professionals play in ITS and ITS competencies A curriculum is then p...

Building professional capacity in ITS : an assessment of ITS training and education needs : the CVO perspective

DOT National Transportation Integrated Search

1999-08-01

This report focuses on assessing the training and education needs of transportation professionals involved in Intelligent Transportation Systems/Commercial Vehicle Operations (ITS/CVO). After an introduction to the program, the author defines the pro...

MACH 3: Past and future approaches to intelligent tutoring

NASA Technical Reports Server (NTRS)

Acchione-Noel, Sylvia; Psotka, Joseph

1993-01-01

In 1986, the U.S. Army Research Institute created an intelligent tutoring system as a proof-of-concept for artificial intelligence applications in Army training. The Maintenance Aid Computer HAWK Intelligent Institutional Instructor (MACH 3) taught student mechanics to maintain and troubleshoot the AN/MPQ-57 High Power Illuminator Radar (HPIR) of the HAWK Air Defense Missile System. In 1989, TRADOC Analysis Command compared the effectiveness of MACH 3 to traditional paper-based troubleshooting drills. For the study, all students received lecture and hands-on training as usual. However, during troubleshooting drills, students traced faults using either MACH 3 or the traditional paper-based method. Class records showed that the MACH 3 group completed significantly more troubleshooting tasks and progressed through tasks of greater difficulty than the paper-based group. Upon completion of training, students took written, practical, and oral essay tests. Mean test scores showed that students performed similarly regardless of the drill method used. However, significantly different standard deviations showed that the MACH 3 group performed more consistently than the paper-based group. Furthermore, significantly different time measures showed that the MACH 3 group reached faster troubleshooting solutions on the actual radar transmitter than the paper-based group. We will present the study results and discuss how updating the design of the MACH 3 can include desktop computing in a virtual environment.

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

ERIC Educational Resources Information Center

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

2018-01-01

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

An Intelligent Tutoring System (ITS) for Operating Training of ROCSAT TT&C Groung Station

NASA Astrophysics Data System (ADS)

Shr, Arthur M. D.; Miau, Jiun Jih

2000-07-01

ROCS AT-1 is the first small satellite developed by the Republic of China and is a lowearth orbit experimental satellite. The goal of ROCSAT-1 is to carry out scientific research missions. To successfully accomplish ROCSAT missions, the ROCSAT Mission Operations Team (RMOT) is formed to handle the daily operation and maintenance activities. These activities are onerous and complex. Hence, RMOT is concerned with future personnel training. In this paper, we propose an Intelligent Tutoring System (ITS) which is capable of integrating the training courses into a software program. ITS uses a great amount of information to present a subject for a user to learn. In the process of teaching, an ITS is capable of presenting the course materials in a structured format to the user and to judge if the user has mastered the subject or not. ITS is the tool to integrate the RMOT training courses and to develop a multi-function computer-assisted instruction (CAI) system. It can not only provide a practical method for users recurrently, but also make self-teaching easily.

The 2009 DOD Cost Research Workshop: Acquisition Reform

DTIC Science & Technology

2010-02-01

2 ACEIT Enhancement, Help-Desk/Training, Consulting DASA-CE–3 Command, Control, Communications, Computers, Intelligence, Surveillance, and...Management Information System (OSMIS) online interactive relational database DASA-CE–2 Title: ACEIT Enhancement, Help-Desk/Training, Consulting Summary...support and training for the Automated Cost estimator Integrated Tools ( ACEIT ) software suite. ACEIT is the Army standard suite of analytical tools for

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.

Building professional capacity in ITS : documentation and analysis of training and education needs in support of ITS deployment

DOT National Transportation Integrated Search

1999-04-01

This report summarizes a comprehensive effort conducted in the summer of 1998 to more systematically investigate the intelligent transportation systems (ITS) training and education needs of transportation professionals. A team of analysts conducted a...

Working Memory Training Does Not Improve Intelligence in Healthy Young Adults

ERIC Educational Resources Information Center

Chooi, Weng-Tink; Thompson, Lee A.

2012-01-01

Jaeggi and her colleagues claimed that they were able to improve fluid intelligence by training working memory. Subjects who trained their working memory on a dual n-back task for a period of time showed significant improvements in working memory span tasks and fluid intelligence tests such as the Raven's Progressive Matrices and the Bochumer…

An Intelligent Catheter System Robotic Controlled Catheter System

PubMed Central

Negoro, M.; Tanimoto, M.; Arai, F.; Fukuda, T.; Fukasaku, K.; Takahashi, I.; Miyachi, S.

2001-01-01

Summary We have developed a novel catheter system, an intelligent catheter system, which is able to control a catheter by an externally-placed controller. This system has made from master-slave mechanism and has following three components; 1) a joy stick as a master (for operators) 2)a catheter controller as a slave (for a patient),3)a micro force sensor as a sensing device. This catheter tele-guiding system has abilities to perform intravascular procedures from the distant places. It may help to reduce the radiation exposures to the operators and also to help train young doctors. PMID:20663387

iBEST: intelligent Balance assessment and Stability Training system using smartphone.

PubMed

Wai, Aung Aung Phyo; Duc, Pham Duy; Syin, Chan; Zhang, Haihong

2014-01-01

Patients with postural instability could lead to falls and injuries while walking due to balance disorders. So those patients need regular balance training and evaluation to improve and examine balance deficiencies. But many do not notice such balance issues; resulting lack of timely preventive measures. This shows the needs of affordable and accessible solution for balance training and assessment. So iBEST (intelligent Balance assessment and Stability Training) is proposed enabling to train and assess balance conveniently anywhere anytime. Moreover, therapists can remotely evaluate and manage their recovery progress. These benefits can be realized leveraging sensors from smartphone, cloud-based data analytics and web applications. iBEST employs sensorised automated balance assessment in digitizing Berg Balance Scale (BBS) clinical risk assessment tool. The initial feasibility study showed average accuracy of 90.22% using smartphone in classifying the specified BBS test items.

Digital intelligent booster for DCC miniature train networks

NASA Astrophysics Data System (ADS)

Ursu, M. P.; Condruz, D. A.

2017-08-01

Modern miniature trains are now driven by means of the DCC (Digital Command and Control) system, which allows the human operator or a personal computer to launch commands to each individual train or even to control different features of the same train. The digital command station encodes these commands and sends them to the trains by means of electrical pulses via the rails of the railway network. Due to the development of the miniature railway network, it may happen that the power requirement of the increasing number of digital locomotives, carriages and accessories exceeds the nominal output power of the digital command station. This digital intelligent booster relieves the digital command station from powering the entire railway network all by itself, and it automatically handles the multiple powered sections of the network. This electronic device is also able to detect and process short-circuits and overload conditions, without the intervention of the digital command station.

Arthur C. Graesser: Award for Distinguished Contributions of Applications of Psychology to Education and Training.

PubMed

2011-11-01

Presents Arthur C. Graesser as the 2011 winner of the American Psychological Association Award for Distinguished Contributions of Applications of Psychology to Education and Training. "As a multifaceted psychologist, cognitive engineer of useful education and training technologies, and mentor of new talent for the world of applied and translational cognitive science, Arthur C. Graesser is the perfect role model, showing how a strong scholar and intellect can shape both research and practice. His work is a mix of top-tier scholarship in psychology, education, intelligent systems, and computational linguistics. He combines cognitive science excellence with bold use of psychological knowledge and intelligent systems to design new generations of learning opportunities and to help lay the foundation for a translational science of learning." (PsycINFO Database Record (c) 2011 APA, all rights reserved). 2011 APA, all rights reserved

The Effect of Spiritual Intelligence Training on Job Satisfaction of Psychiatric Nurses.

PubMed

Heydari, Abbas; Meshkinyazd, Ali; Soudmand, Parvaneh

2017-04-01

Objective: Nurses are the most important staff in the health care system, thus, their job satisfaction is important in nursing management. The present study aimed at determining the impact of teaching spiritual intelligence on the job satisfaction of psychiatric nurses. Method: The participants were divided into 2 groups by random allocation. Data were collected in 3 stages of before intervention, 4 weeks, and 8 weeks post intervention using Brayfield & Rother Job Satisfaction Questionnaire. Results: The results of this study revealed that the mean score of job satisfaction in the experimental group was 65.5±9.9 in the pre intervention stage, which increased to 69.8±6.3 one month after the intervention and to 72.5±8.9 in 2 months after the intervention, and it was significantly more than that of the control group. Conclusion: The job satisfaction rate of the control group decreased admirably in both 1 month and 2 months after the intervention stage. Thus, spiritual intelligence training is an effective method to increase job satisfaction, and it is suggested that managers consider spiritual intelligence training to increase job satisfaction in nurses.

Tutoring electronic troubleshooting in a simulated maintenance work environment

NASA Technical Reports Server (NTRS)

Gott, Sherrie P.

1987-01-01

A series of intelligent tutoring systems, or intelligent maintenance simulators, is being developed based on expert and novice problem solving data. A graded series of authentic troubleshooting problems provides the curriculum, and adaptive instructional treatments foster active learning in trainees who engage in extensive fault isolation practice and thus in conditionalizing what they know. A proof of concept training study involving human tutoring was conducted as a precursor to the computer tutors to assess this integrated, problem based approach to task analysis and instruction. Statistically significant improvements in apprentice technicians' troubleshooting efficiency were achieved after approximately six hours of training.

The Research on Application of Information Technology in sports Stadiums

NASA Astrophysics Data System (ADS)

Can, Han; Lu, Ma; Gan, Luying

With the Olympic glory in the national fitness program planning and the smooth development of China, the public's concern for the sport continues to grow, while their physical health is also increasingly fervent desired, the country launched a modern technological construction of sports facilities. Information technology applications in the sports venues in the increasingly wide range of modern venues and facilities, including not only the intelligent application of office automation systems, intelligent systems and sports facilities, communication systems for event management, ticket access control system, contest information systems, television systems, Command and Control System, but also in action including the use of computer technology, image analysis, computer-aided training athletes, sports training system and related data entry systems, decision support systems.Using documentary data method, this paper focuses on the research on application of information technology in Sports Stadiums, and try to explore its future trends.With a view to promote the growth of China's national economyand,so as to improve the students'quality and promote the cause of Chinese sports.

First CLIPS Conference Proceedings, volume 1

NASA Technical Reports Server (NTRS)

1990-01-01

The first Conference of C Language Production Systems (CLIPS) hosted by the NASA-Lyndon B. Johnson Space Center in August 1990 is presented. Articles included engineering applications, intelligent tutors and training, intelligent software engineering, automated knowledge acquisition, network applications, verification and validation, enhancements to CLIPS, space shuttle quality control/diagnosis applications, space shuttle and real-time applications, and medical, biological, and agricultural applications.

Virtual reality for intelligent and interactive operating, training, and visualization systems

NASA Astrophysics Data System (ADS)

Freund, Eckhard; Rossmann, Juergen; Schluse, Michael

2000-10-01

Virtual Reality Methods allow a new and intuitive way of communication between man and machine. The basic idea of Virtual Reality (VR) is the generation of artificial computer simulated worlds, which the user not only can look at but also can interact with actively using data glove and data helmet. The main emphasis for the use of such techniques at the IRF is the development of a new generation of operator interfaces for the control of robots and other automation components and for intelligent training systems for complex tasks. The basic idea of the methods developed at the IRF for the realization of Projective Virtual Reality is to let the user work in the virtual world as he would act in reality. The user actions are recognized by the Virtual reality System and by means of new and intelligent control software projected onto the automation components like robots which afterwards perform the necessary actions in reality to execute the users task. In this operation mode the user no longer has to be a robot expert to generate tasks for robots or to program them, because intelligent control software recognizes the users intention and generated automatically the commands for nearly every automation component. Now, Virtual Reality Methods are ideally suited for universal man-machine-interfaces for the control and supervision of a big class of automation components, interactive training and visualization systems. The Virtual Reality System of the IRF-COSIMIR/VR- forms the basis for different projects starting with the control of space automation systems in the projects CIROS, VITAL and GETEX, the realization of a comprehensive development tool for the International Space Station and last but not least with the realistic simulation fire extinguishing, forest machines and excavators which will be presented in the final paper in addition to the key ideas of this Virtual Reality System.

World of intelligence defense object detection-machine learning (artificial intelligence)

NASA Astrophysics Data System (ADS)

Gupta, Anitya; Kumar, Akhilesh; Bhushan, Vinayak

2018-04-01

This paper proposes a Quick Locale based Convolutional System strategy (Quick R-CNN) for question recognition. Quick R-CNN expands on past work to effectively characterize ob-ject recommendations utilizing profound convolutional systems. Com-pared to past work, Quick R-CNN utilizes a few in-novations to enhance preparing and testing speed while likewise expanding identification precision. Quick R-CNN trains the profound VGG16 arrange 9 quicker than R-CNN, is 213 speedier at test-time, and accomplishes a higher Guide on PASCAL VOC 2012. Contrasted with SPPnet, Quick R-CNN trains VGG16 3 quicker, tests 10 speedier, and is more exact. Quick R-CNN is actualized in Python and C++ (utilizing Caffe) and is accessible under the open-source MIT Permit.

[Artificial intelligence--the knowledge base applied to nephrology].

PubMed

Sancipriano, G P

2005-01-01

The idea that efficacy efficiency, and quality in medicine could not be reached without sorting the huge knowledge of medical and nursing science is very common. Engineers and computer scientists have developed medical software with great prospects for success, but currently these software applications are not so useful in clinical practice. The medical doctor and the trained nurse live the 'information age' in many daily activities, but the main benefits are not so widespread in working activities. Artificial intelligence and, particularly, export systems charm health staff because of their potential. The first part of this paper summarizes the characteristics of 'weak artificial intelligence' and of expert systems important in clinical practice. The second part discusses medical doctors' requirements and the current nephrologic knowledge bases available for artificial intelligence development.

An Experimental Design of a Foundational Framework for the Application of Affective Computing to Soaring Flight Simulation and Training

ERIC Educational Resources Information Center

Moon, Shannon

2017-01-01

In the absence of tools for intelligent tutoring systems for soaring flight simulation training, this study evaluated a framework foundation to measure pilot performance, affect, and physiological response to training in real-time. Volunteers were asked to perform a series of flight tasks selected from Federal Aviation Administration Practical…

Hybrid intelligent monironing systems for thermal power plant trips

NASA Astrophysics Data System (ADS)

Barsoum, Nader; Ismail, Firas Basim

2012-11-01

Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

A fuzzy logic intelligent diagnostic system for spacecraft integrated vehicle health management

NASA Technical Reports Server (NTRS)

Wu, G. Gordon

1995-01-01

Due to the complexity of future space missions and the large amount of data involved, greater autonomy in data processing is demanded for mission operations, training, and vehicle health management. In this paper, we develop a fuzzy logic intelligent diagnostic system to perform data reduction, data analysis, and fault diagnosis for spacecraft vehicle health management applications. The diagnostic system contains a data filter and an inference engine. The data filter is designed to intelligently select only the necessary data for analysis, while the inference engine is designed for failure detection, warning, and decision on corrective actions using fuzzy logic synthesis. Due to its adaptive nature and on-line learning ability, the diagnostic system is capable of dealing with environmental noise, uncertainties, conflict information, and sensor faults.

StairStepper: An Adaptive Remedial iSTART Module

ERIC Educational Resources Information Center

Perret, Cecile A.; Johnson, Amy M.; McCarthy, Kathryn S.; Guerrero, Tricia A.; Dai, Jianmin; McNamara, Danielle S.

2017-01-01

This paper introduces StairStepper, a new addition to Interactive Strategy Training for Active Reading and Thinking (iSTART), an intelligent tutoring system (ITS) that provides adaptive self-explanation training and practice. Whereas iSTART focuses on improving comprehension at levels geared toward answering challenging questions associated with…

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.

The potential for intelligent decision support systems to improve the quality and consistency of medication reviews.

PubMed

Bindoff, I; Stafford, A; Peterson, G; Kang, B H; Tenni, P

2012-08-01

Drug-related problems (DRPs) are of serious concern worldwide, particularly for the elderly who often take many medications simultaneously. Medication reviews have been demonstrated to improve medication usage, leading to reductions in DRPs and potential savings in healthcare costs. However, medication reviews are not always of a consistently high standard, and there is often room for improvement in the quality of their findings. Our aim was to produce computerized intelligent decision support software that can improve the consistency and quality of medication review reports, by helping to ensure that DRPs relevant to a patient are overlooked less frequently. A system that largely achieved this goal was previously published, but refinements have been made. This paper examines the results of both the earlier and newer systems. Two prototype multiple-classification ripple-down rules medication review systems were built, the second being a refinement of the first. Each of the systems was trained incrementally using a human medication review expert. The resultant knowledge bases were analysed and compared, showing factors such as accuracy, time taken to train, and potential errors avoided. The two systems performed well, achieving accuracies of approximately 80% and 90%, after being trained on only a small number of cases (126 and 244 cases, respectively). Through analysis of the available data, it was estimated that without the system intervening, the expert training the first prototype would have missed approximately 36% of potentially relevant DRPs, and the second 43%. However, the system appeared to prevent the majority of these potential expert errors by correctly identifying the DRPs for them, leaving only an estimated 8% error rate for the first expert and 4% for the second. These intelligent decision support systems have shown a clear potential to substantially improve the quality and consistency of medication reviews, which should in turn translate into improved medication usage if they were implemented into routine use. © 2011 Blackwell Publishing Ltd.

An Ensemble of Neural Networks for Stock Trading Decision Making

NASA Astrophysics Data System (ADS)

Chang, Pei-Chann; Liu, Chen-Hao; Fan, Chin-Yuan; Lin, Jun-Lin; Lai, Chih-Ming

Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from historic data for training. These turning signals represent short-term and long-term trading signals for selling or buying stocks from the market which are applied to forecast the future turning points from the set of test data. Experimental results demonstrate that the hybrid system can make a significant and constant amount of profit when compared with other approaches using stock data available in the market.

ORGANIZING, TRAINING, AND RETAINING INTELLIGENCE PROFESSIONALS FOR CYBER OPERATIONS

DTIC Science & Technology

2016-02-13

in Education,” Preventing School Failure 57(3), (2013): 162-170. Wall , Andru, “Demystifying the Title 10-Title 50 Debate,” Harvard Law School...AIR WAR COLLEGE AIR UNIVERSITY ORGANIZING, TRAINING, AND RETAINING INTELLIGENCE PROFESSIONALS FOR CYBER OPERATIONS by Melissa A...to adequately organize, train and retain cyber expertise. This is especially true within Air Force intelligence, a critical component of the

Artificial Intelligence Applications to Learning and Training. Occasional Paper--InTER/2/88.

ERIC Educational Resources Information Center

Cumming, Geoff

This report summarizes and interprets the discussions at a seminar on artificial intelligence (AI) training domains and knowledge representations which was sponsored by the United Kingdom Training Commission. The following broad areas are addressed: (1) the context, process, and diversity of requirements of training and training needs; (2)…

Exploiting Artificial Intelligence To Enhance Training: A Short- and Medium-Term Perspective.

ERIC Educational Resources Information Center

Cumming, Geoff

This paper is an introductory discussion of industrial training, artificial intelligence (AI), and AI applications in training, prepared in the context of the United Kingdom Training Commission (TC) program. Following an outline of the activities and aims of the program, individual sections describe perspectives on: (1) training needs, including…

Case Study of the U.S. Army’s Should-Cost Management Implementation

DTIC Science & Technology

2013-12-03

and Pelvic Protection Systems (PPS). After graduating from the Naval Postgraduate School, Major Choi will be assigned to the U.S. Army...Systems PMO Product/Project/Program Management Office PMT Program Management Training POA&M Plan of Action and Milestones POE Program Office...Intelligence, Electronic Warfare and Sensors  PEO Simulation, Training , and Instrumentation  JPEO Chemical and Biological Defense The researcher

Advanced Satellite Workstation - An integrated workstation environment for operational support of satellite system planning and analysis

NASA Astrophysics Data System (ADS)

Hamilton, Marvin J.; Sutton, Stewart A.

A prototype integrated environment, the Advanced Satellite Workstation (ASW), which was developed and delivered for evaluation and operator feedback in an operational satellite control center, is described. The current ASW hardware consists of a Sun Workstation and Macintosh II Workstation connected via an ethernet Network Hardware and Software, Laser Disk System, Optical Storage System, and Telemetry Data File Interface. The central objective of ASW is to provide an intelligent decision support and training environment for operator/analysis of complex systems such as satellites. Compared to the many recent workstation implementations that incorporate graphical telemetry displays and expert systems, ASW provides a considerably broader look at intelligent, integrated environments for decision support, based on the premise that the central features of such an environment are intelligent data access and integrated toolsets.

Statistical Hypothesis Testing using CNN Features for Synthesis of Adversarial Counterexamples to Human and Object Detection Vision Systems

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

Raj, Sunny; Jha, Sumit Kumar; Pullum, Laura L.

Validating the correctness of human detection vision systems is crucial for safety applications such as pedestrian collision avoidance in autonomous vehicles. The enormous space of possible inputs to such an intelligent system makes it difficult to design test cases for such systems. In this report, we present our tool MAYA that uses an error model derived from a convolutional neural network (CNN) to explore the space of images similar to a given input image, and then tests the correctness of a given human or object detection system on such perturbed images. We demonstrate the capability of our tool on themore » pre-trained Histogram-of-Oriented-Gradients (HOG) human detection algorithm implemented in the popular OpenCV toolset and the Caffe object detection system pre-trained on the ImageNet benchmark. Our tool may serve as a testing resource for the designers of intelligent human and object detection systems.« less

Natural Language Processing for Joint Fire Observer Training

DTIC Science & Technology

2010-11-01

training system. However, many of the tasks an operator performs are routine and can be automated. The Intelligent Operator Training Assistant ( IOTA ) is...whole JFETS training session might be handled by the IOTA . In other cases, where the soldier departs from pre-defined parameters, the human operator...is able to take over control of the session from the IOTA until the soldier is back within the established parameters. We enable this flexibility

CBT Pilot Program Instructional Guide. Basic Drafting Skills Curriculum Delivered through CAD Workstations and Artificial Intelligence Software.

ERIC Educational Resources Information Center

Smith, Richard J.; Sauer, Mardelle A.

This guide is intended to assist teachers in using computer-aided design (CAD) workstations and artificial intelligence software to teach basic drafting skills. The guide outlines a 7-unit shell program that may also be used as a generic authoring system capable of supporting computer-based training (CBT) in other subject areas. The first section…

Lessons learned in the development of the STOL intelligent tutoring system

NASA Technical Reports Server (NTRS)

Seamster, Thomas; Baker, Clifford; Ames, Troy

1991-01-01

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

Facial Recognition Training: Improving Intelligence Collection by Soldiers

DTIC Science & Technology

2008-01-01

Facial Recognition Training: Improving Intelligence Collection by Soldiers By: 2LT Michael Mitchell, MI, ALARNG “In combat, you don’t rise to...technology, but on patrol a Soldier cannot use a device as quickly as simply looking at the subject. Why is Facial Recognition Difficult? Soldiers...00-2008 to 00-00-2008 4. TITLE AND SUBTITLE Facial Recognition Training: Improving Intelligence Collection by Soldiers 5a. CONTRACT NUMBER 5b

Multidimensional Aptitude Battery-Second Edition Intelligence Testing of Remotely Piloted Aircraft Training Candidates Compared with Manned Airframe Training Candidates

DTIC Science & Technology

2015-03-01

assessing the general intelligence and neuropsychological aptitudes of USAF RPA pilot training candidates. Chappelle et al. obtained comprehensive...computer-based intelligence testing (Multidimensional Aptitude Battery-Second Edition [MAB-II]) and neuropsychological screening (MicroCog) on USAF MQ-1... schizophrenia , attention deficit hyperactivity disorder, and autism spectrum disorders) and not on very high functioning populations such as aviators

POINTER: Portable Intelligent Trainer for External Robotics

NASA Technical Reports Server (NTRS)

Kuiper, Hilbert; Rikken, Patrick J.

1994-01-01

Intelligent tutoring systems (ITS's) play an increasing role in training and education of people with different levels of skill and knowledge. As compared to conventional computer based training (CBT) an ITS provides more tailored instruction by trying to mimic the teaching behavior of a human instructor as much as possible and is therefore much more flexible. This paper starts with an introduction to ITS's, followed by the description of an ITS for training of an (astronaut) operator in monitoring and controlling robotic arm procedures. The robotic arm will be used for exchange of equipment between a space station and a space plane involving critical and accurate movements of the robotic arm. The ITS for this application, called Pointer, is developed by TNO Physics and Electronics Laboratory and is based upon an existing ITS that includes procedural training. Pointer has been developed on a workstation whereas the target platform was a portable computer. Therefore, a lot of attention had to be paid to scaling effects and keeping up with user friendliness of the much smaller user interface. Although the learning domain was the control of a robotic arm, it is clear that use of intelligent training technologies on a portable computer has many other applications (payload operations, operation control rooms, etc.). Training can occur at any time and place in an attractive and cost effective way.

Automated Intelligibility Assessment of Pathological Speech Using Phonological Features

NASA Astrophysics Data System (ADS)

Middag, Catherine; Martens, Jean-Pierre; Van Nuffelen, Gwen; De Bodt, Marc

2009-12-01

It is commonly acknowledged that word or phoneme intelligibility is an important criterion in the assessment of the communication efficiency of a pathological speaker. People have therefore put a lot of effort in the design of perceptual intelligibility rating tests. These tests usually have the drawback that they employ unnatural speech material (e.g., nonsense words) and that they cannot fully exclude errors due to listener bias. Therefore, there is a growing interest in the application of objective automatic speech recognition technology to automate the intelligibility assessment. Current research is headed towards the design of automated methods which can be shown to produce ratings that correspond well with those emerging from a well-designed and well-performed perceptual test. In this paper, a novel methodology that is built on previous work (Middag et al., 2008) is presented. It utilizes phonological features, automatic speech alignment based on acoustic models that were trained on normal speech, context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples. The experimental evaluation of the new system reveals that the root mean squared error of the discrepancies between perceived and computed intelligibilities can be as low as 8 on a scale of 0 to 100.

The effect of life skills training on emotional intelligence of the medical sciences students in iran.

PubMed

Lolaty, Hamideh A; Ghahari, Sharbanoo; Tirgari, Abdolhakim; Fard, Jabbar Heydari

2012-10-01

Emotional intelligence has a major role in mental health and life skills training, and could be viewed as a bridge relating to emotional intelligence and mental health. The present study is aimed at determining the effect of life skills training on the emotional intelligence among the first year students of Mazandaran University of Medical Sciences. MATERIALS AND METHODS: IN THIS EXPERIMENTAL STUDY, THE SUBJECTS WERE SELECTED BY RANDOM SAMPLING AND ALLOCATED INTO TWO GROUPS: Case group (n=20) and control group (n=19); they matched for gender, experience of stressful life events in the past six months, level of interest in the field of study, and level of emotional intelligence. The two groups responded to Bar-on Emotional Quotient Inventory before starting the experiment. Subsequently, the case group underwent life skills training. After the training, Bar-on Emotional Quotient Inventory was responded by the case and control groups again. The data was analyzed using descriptive statistics including Chi-square test, paired and independent t-tests, using SPSS software version 15. In the case group, the scores of emotional intelligence after life skills training were significantly improved (t=11.703 df=19 P=0.001), while no significant difference was observed in the control group (t=0.683 df =18 P=0.503). By performing programs such as life skills training, the levels of emotional intelligence of the students could be increased, which itself could lead to academic success, reduced substance abuse, and increased stress tolerance in the students.

Neural Networks for the Beginner.

ERIC Educational Resources Information Center

Snyder, Robin M.

Motivated by the brain, neural networks are a right-brained approach to artificial intelligence that is used to recognize patterns based on previous training. In practice, one would not program an expert system to recognize a pattern and one would not train a neural network to make decisions from rules; but one could combine the best features of…

A Pan-European Survey Leading to the Development of WITS.

ERIC Educational Resources Information Center

Mullins, Roisin; Duan, Yanqing; Hamblin, David

2001-01-01

Describes a study of the training needs of small- and medium-sized enterprises in relation to the Internet, electronic commerce, and electronic data interchange in the United Kingdom, Poland, Slovak Republic, Germany, and Portugal. Discusses the development of a Web-based intelligent training system (WITS) as a result of the study. (Author/LRW)

Representing System Behaviors and Expert Behaviors for Intelligent Tutoring

DTIC Science & Technology

1987-02-09

Learned .................................. 44 . Future Directions ................................... 47 Sum m ary...and training environments to assist the instructor in meeting the students’ learning needs. The first application of the IMTS will be in training...identifies and resolves learning deficiencies and minimizes unproductive practice time. Another decision made early in the planning phase was to place

Government-Sponsored Research and Development Efforts in the Area of Intelligent Tutoring Systems. Summary Report.

DTIC Science & Technology

1995-02-01

modeling a personal trainer MASA training through development and .-chnology ICAT applications, VR-training applications, and technology transfer to...Scholas- tic Aptitude Tests, the average score of ITS-tutored students was 410, compared with an average of 380 for non-ITS users [Anderson et al. 1994

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Effects of Lexical and Somatosensory Feedback on Long-Term Improvements in Intelligibility of Dysarthric Speech

ERIC Educational Resources Information Center

Borrie, Stephanie A.; Schäfer, Martina C. M.

2017-01-01

Purpose: Intelligibility improvements immediately following perceptual training with dysarthric speech using lexical feedback are comparable to those observed when training uses somatosensory feedback (Borrie & Schäfer, 2015). In this study, we investigated if these lexical and somatosensory guided improvements in listener intelligibility of…

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…

Video-Games: Do They Require General Intelligence?

ERIC Educational Resources Information Center

Quiroga, M. A.; Herranz, M.; Gomez-Abad, M.; Kebir, M.; Ruiz, J.; Colom, Roberto

2009-01-01

Here we test if playing video-games require intelligence. Twenty-seven university undergraduate students were trained on three games from Big Brain Academy (Wii): Calculus, Backward Memory and Train. Participants did not have any previous experience with these games. General intelligence was measured by five ability tests before the training…

Enlisted Personnel Allocation System

DTIC Science & Technology

1989-03-01

hierarchy is further subdivided into two characteristic groupings: intelligence qualifications and physical qualifications. 41 I I 7 -, S- ie p if- i - LL...weighted as 30% of the applicant’s Intelligence Qualifications score). As shown in Figure 6, a step function generates a score based on the...34 There is no aritificial time window imposed on any MOS. Any open training date within the full DEP horizon may be recommended by the optimization

The effect of relational training on intelligence quotient: a case study.

PubMed

Vizcaíno-Torres, Rosa M; Ruiz, Francisco J; Luciano, Carmen; López-López, Juan C; Barbero-Rubio, Adrián; Gil, Enriquel

2015-01-01

Relational training protocols based on Relational Frame Theory (RFT) are showing promising results in increasing intelligence quotient. This case study aimed at analyzing the effect of a training protocol in fluency and flexibility in relational responding on intelligence quotient with a 4-year-old child. The child’s cognitive and psychomotor development was evaluated before and after the implementation of the training protocol using the McCarthy’s Aptitudes and Psychomotricity Scale (MSCA). The training protocol consisted of a multiple-exemplar-training (MET) in relational framing in accordance with COORDINATION (Phases 1 and 2), OPPOSITION (Phase 3 and 4), and COMPARISON (Phases 5 and 6). The MET protocol was implemented in approximately 12 hours throughout five and one half months. The training was effective in establishing relational responding in OPPOSITION and COMPARISON frames as well as in promoting fluency and flexibility in all the three types of trained relations. After this training, the child showed an increase above 1.5 SD in the General Cognitive Index of the MSCA (from 106 to 131). This case study adds further empirical evidence of the potential of RFT training to improve cognitive abilities and intelligence.

An Intelligent Decision System for Intraoperative Somatosensory Evoked Potential Monitoring.

PubMed

Fan, Bi; Li, Han-Xiong; Hu, Yong

2016-02-01

Somatosensory evoked potential (SEP) is a useful, noninvasive technique widely used for spinal cord monitoring during surgery. One of the main indicators of a spinal cord injury is the drop in amplitude of the SEP signal in comparison to the nominal baseline that is assumed to be constant during the surgery. However, in practice, the real-time baseline is not constant and may vary during the operation due to nonsurgical factors, such as blood pressure, anaesthesia, etc. Thus, a false warning is often generated if the nominal baseline is used for SEP monitoring. In current practice, human experts must be used to prevent this false warning. However, these well-trained human experts are expensive and may not be reliable and consistent due to various reasons like fatigue and emotion. In this paper, an intelligent decision system is proposed to improve SEP monitoring. First, the least squares support vector regression and multi-support vector regression models are trained to construct the dynamic baseline from historical data. Then a control chart is applied to detect abnormalities during surgery. The effectiveness of the intelligent decision system is evaluated by comparing its performance against the nominal baseline model by using the real experimental datasets derived from clinical conditions.

Sparse Forward-Backward for Fast Training of Conditional Random Fields

DTIC Science & Technology

2006-01-01

knowledge- based systems. Proceedings of the 6th Conference on Uncertainty in Artifcial Intelligence , 1990. Appears to be unavailable. [4] Michael I...response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and...task, the NetTalk text-to-speech data set [5], we can now train a conditional random field (CRF) in about 6 hours for which training previously

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 ...

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

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

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

The Effects of Taekwondo Training on Brain Connectivity and Body Intelligence.

PubMed

Kim, Young Jae; Cha, Eun Joo; Kim, Sun Mi; Kang, Kyung Doo; Han, Doug Hyun

2015-07-01

Many studies have reported that Taekwondo training could improve body perception, control and brain activity, as assessed with an electroencephalogram. This study aimed to assess body intelligence and brain connectivity in children with Taekwondo training as compared to children without Taekwondo training. Fifteen children with Taekwondo training (TKD) and 13 age- and sex-matched children who had no previous experience of Taekwondo training (controls) were recruited. Body intelligence, clinical characteristics and brain connectivity in all children were assessed with the Body Intelligence Scale (BIS), self-report, and resting state functional magnetic resonance imaging. The mean BIS score in the TKD group was higher than that in the control group. The TKD group showed increased low-frequency fluctuations in the right frontal precentral gyrus and the right parietal precuneus, compared to the control group. The TKD group showed positive cerebellum vermis (lobe VII) seed to the right frontal, left frontal, and left parietal lobe. The control group showed positive cerebellum seed to the left frontal, parietal, and occipital cortex. Relative to the control group, the TKD group showed increased functional connectivity from cerebellum seed to the right inferior frontal gyrus. To the best of our knowledge, this is the first study to assess the effect of Taekwondo training on brain connectivity in children. Taekwondo training improved body intelligence and brain connectivity from the cerebellum to the parietal and frontal cortex.

Natural Language Processing and Game-Based Practice in iSTART

ERIC Educational Resources Information Center

Jackson, Tanner; Boonthum-Denecke, Chutima; McNamara, Danielle

2015-01-01

Intelligent Tutoring Systems (ITSs) are situated in a potential struggle between effective pedagogy and system enjoyment and engagement. iSTART (Interactive Strategy Training for Active Reading and Thinking), a reading strategy tutoring system in which students practice generating self-explanations and using reading strategies, employs two devices…

Battle Command Staff Training

DTIC Science & Technology

1992-12-01

warfare ? • How does one develop training exercises to exploit this medium? • What are some of the implications for institutional training? The DARPA...IDT Inactive Duty Training JEW IIntelligencel•ectronic Warfare I FOR Intelligent Forces IPB Intelligence Preparation of the Battlefield JAAT Joint Air... Chemical xiI NFA No Fire Area NGB Nationhl Guard Bureau NTC National Training Center OAC Officers Advanced Cours- OC Observer/Controllcr OCI Observer

Heroin Photos

MedlinePlus

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The effectiveness of staff training focused on increasing emotional intelligence and improving interaction between support staff and clients.

PubMed

Zijlmans, L J M; Embregts, P J C M; Gerits, L; Bosman, A M T; Derksen, J J L

2015-07-01

Recent research addressed the relationship between staff behaviour and challenging behaviour of individuals with an intellectual disability (ID). Consequently, research on interventions aimed at staff is warranted. The present study focused on the effectiveness of a staff training aimed at emotional intelligence and interactions between staff and clients. The effects of the training on emotional intelligence, coping style and emotions of support staff were investigated. Participants were 214 support staff working within residential settings for individuals with ID and challenging behaviour. The experimental group consisted of 76 staff members, 138 staff members participated in two different control groups. A pre-test, post-test, follow-up control group design was used. Effectiveness was assessed using questionnaires addressing emotional intelligence, coping and emotions. Emotional intelligence of the experimental group changed significantly more than that of the two control groups. The experimental group showed an increase in task-oriented coping, whereas one control group did not. The results with regard to emotions were mixed. Follow-up data revealed that effects within the experimental group were still present four months after the training ended. A staff training aimed at emotional intelligence and staff-client interactions is effective in improving emotional intelligence and coping styles of support staff. However, the need for more research aiming at the relationship between staff characteristics, organisational factors and their mediating role in the effectiveness of staff training is emphasised. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Flexible Learning for the Information Economy: A Framework for National Collaboration in Vocational Education and Training, 2000-2004.

ERIC Educational Resources Information Center

2000

Vocational education and training (VET) has a fundamental role to play in enabling Australia's successful transition to the information economy. Competitive advantage can be supported by intelligent competition and creative collaboration. Governments have played the fundamental role in building a coordinated VET system in Australia and in helping…

Working memory training may increase working memory capacity but not fluid intelligence.

PubMed

Harrison, Tyler L; Shipstead, Zach; Hicks, Kenny L; Hambrick, David Z; Redick, Thomas S; Engle, Randall W

2013-12-01

Working memory is a critical element of complex cognition, particularly under conditions of distraction and interference. Measures of working memory capacity correlate positively with many measures of real-world cognition, including fluid intelligence. There have been numerous attempts to use training procedures to increase working memory capacity and thereby performance on the real-world tasks that rely on working memory capacity. In the study reported here, we demonstrated that training on complex working memory span tasks leads to improvement on similar tasks with different materials but that such training does not generalize to measures of fluid intelligence.

Realization of Intelligent Measurement and Control System for Limb Rehabilitation Based on PLC and Touch Screen

NASA Astrophysics Data System (ADS)

Liu, Xiangquan

According to the treatment needs of patients with limb movement disorder, on the basis of the limb rehabilitative training prototype, function of measure and control system are analyzed, design of system hardware and software is completed. The touch screen which is adopt as host computer and man-machine interaction window is responsible for sending commands and training information display; The PLC which is adopt as slave computer is responsible for receiving control command from touch screen, collecting the sensor data, regulating torque and speed of motor by analog output according to the different training mode, realizing ultimately active and passive training for limb rehabilitation therapy.

Applications for Mission Operations Using Multi-agent Model-based Instructional Systems with Virtual Environments

NASA Technical Reports Server (NTRS)

Clancey, William J.

2004-01-01

This viewgraph presentation provides an overview of past and possible future applications for artifical intelligence (AI) in astronaut instruction and training. AI systems have been used in training simulation for the Hubble Space Telescope repair, the International Space Station, and operations simulation for the Mars Exploration Rovers. In the future, robots such as may work as partners with astronauts on missions such as planetary exploration and extravehicular activities.

Training emotional intelligence improves both emotional intelligence and depressive symptoms in inpatients with borderline personality disorder and depression.

PubMed

Jahangard, Leila; Haghighi, Mohammad; Bajoghli, Hafez; Ahmadpanah, Mohammad; Ghaleiha, Ali; Zarrabian, Mohammad Kazem; Brand, Serge

2012-09-01

Borderline personality disorder (BPD) is defined as a pervasive pattern of instability in emotion, mood and interpersonal relationships, with a comorbidity between PBD and depressive disorders (DD). A key competence for successful management of interpersonal relationships is emotional intelligence (EI). Given the low EI of patients suffering from BPD, the present study aimed at investigating the effect on both emotional intelligence and depression of training emotional intelligence in patients with BPD and DD. A total of 30 inpatients with BPD and DD (53% females; mean age 24.20 years) took part in the study. Patients were randomly assigned either to the treatment or to the control group. Pre- and post-testing 4 weeks later involved experts' rating of depressive disorder and self-reported EI. The treatment group received 12 sessions of training in components of emotional intelligence. Relative to the control group, EI increased significantly in the treatment group over time. Depressive symptoms decreased significantly over time in both groups, though improvement was greater in the treatment than the control group. For inpatients suffering from BPD and DD, regular skill training in EI can be successfully implemented and leads to improvements both in EI and depression. Results suggest an additive effect of EI training on both EI and depressive symptoms.

Improving fluid intelligence with training on working memory: a meta-analysis.

PubMed

Au, Jacky; Sheehan, Ellen; Tsai, Nancy; Duncan, Greg J; Buschkuehl, Martin; Jaeggi, Susanne M

2015-04-01

Working memory (WM), the ability to store and manipulate information for short periods of time, is an important predictor of scholastic aptitude and a critical bottleneck underlying higher-order cognitive processes, including controlled attention and reasoning. Recent interventions targeting WM have suggested plasticity of the WM system by demonstrating improvements in both trained and untrained WM tasks. However, evidence on transfer of improved WM into more general cognitive domains such as fluid intelligence (Gf) has been more equivocal. Therefore, we conducted a meta-analysis focusing on one specific training program, n-back. We searched PubMed and Google Scholar for all n-back training studies with Gf outcome measures, a control group, and healthy participants between 18 and 50 years of age. In total, we included 20 studies in our analyses that met our criteria and found a small but significant positive effect of n-back training on improving Gf. Several factors that moderate this transfer are identified and discussed. We conclude that short-term cognitive training on the order of weeks can result in beneficial effects in important cognitive functions as measured by laboratory tests.

The Impact of Counsellor Training on Emotional Intelligence

ERIC Educational Resources Information Center

Pearson, Anne; Weinberg, Ashley

2017-01-01

This study evaluated the impact of counsellor training on emotional intelligence (EI) in 45 undergraduates and 58 postgraduates. Significant improvements were recorded by students on completion of both programmes, suggesting that these were attributable to training which enhanced intra- and interpersonal aspects of emotional functioning. As a…

The Importance of Artificial Intelligence for Naval Intelligence Training Simulations

DTIC Science & Technology

2006-09-01

experimental investigation described later. B. SYSTEM ARCHITECTURE The game-based simulator was created using NetBeans , which is an open source integrated...development environment (IDE) written entirely in Java using the NetBeans Platform. NetBeans is based upon the Java language which contains the...involved within the simulation are conducted in a GUI built within the NetBeans IDE. The opening display allows the user to setup the simulation

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 ...

The Anti-RFI Design of Intelligent Electric Energy Meters with UHF RFID

NASA Astrophysics Data System (ADS)

Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

2018-03-01

In order to solve the existing artificial meter reading watt-hour meter industry is still slow and inventory of common problems, using the uhf radio frequency identification (RFID) technology and intelligent watt-hour meter depth fusion, which has a one-time read multiple tags, identification distance, high transmission rate, high reliability, etc, while retaining the original asset management functions, in order to ensure the uhf RFID and minimum impact on the operation of the intelligent watt-hour meter, proposed to improve the stability of the electric meter system while working at the same time, this paper designs the uhf RFID intelligent watt-hour meter radio frequency interference resistance, put forward to improve intelligent watt-hour meter electromagnetic compatibility design train of thought, and introduced its power and the hardware circuit design of printed circuit board, etc.

Developing Meaningfulness at Work through Emotional Intelligence Training

ERIC Educational Resources Information Center

Thory, Kathryn

2016-01-01

To date, there remains a significant gap in the human resource development (HRD) literature in understanding how training and development contributes to meaningful work. In addition, little is known about how individuals proactively make their work more meaningful. This article shows how emotional intelligence (EI) training promotes learning about…

Working Memory Training: Improving Intelligence--Changing Brain Activity

ERIC Educational Resources Information Center

Jausovec, Norbert; Jausovec, Ksenija

2012-01-01

The main objectives of the study were: to investigate whether training on working memory (WM) could improve fluid intelligence, and to investigate the effects WM training had on neuroelectric (electroencephalography--EEG) and hemodynamic (near-infrared spectroscopy--NIRS) patterns of brain activity. In a parallel group experimental design,…

Emotional Intelligence: Pedagogical Considerations for Skills-Based Learning in Business Communication Courses

ERIC Educational Resources Information Center

Sigmar, Lucia; Hynes, Geraldine E.; Cooper, Tab

2010-01-01

This study investigates the effect of Emotional Intelligence (EQ) training on student satisfaction with the collaborative writing process and product. Business communication students at an AACSB-accredited state university worked collaboratively on writing assignments in pre-and post-EQ-training sessions. Pre-and post-training surveys measured…

Emotional Intelligence Training: A Case of Caveat Emptor

ERIC Educational Resources Information Center

Clarke, Nicholas

2006-01-01

Training programs purporting to develop emotional intelligence (EI) are widely available, yet to date few empirical studies have appeared in the literature providing support that training results in demonstrable changes to EI, and more significantly whether these changes can then be traced to more positive individual or organizational outcomes.…

On the Effects of Training Inductive Reasoning: How Far Does It Transfer and How Long Do the Effects Persist?

ERIC Educational Resources Information Center

Tomic, Welko; Klauer, Karl Josef

1996-01-01

Reports on two training experiments in which it was expected that training in inductive reasoning would transfer to intelligence tests measuring inductive reasoning and on mathematics performance. Shows that transfer on intelligence tests as well as on mathematics performance was linearly dependent on the amount of prior training. (DSK)

The effect of deliberate play on tactical performance in basketball.

PubMed

Greco, Pablo; Memmert, Daniel; Morales, Juan C P

2010-06-01

This field-based study analyzed effects of a deliberate-play training program in basketball on tactical game intelligence and tactical creativity. 22 youth basketball players, ages 10 to 12 years, completed basketball training in one of two equal-sized groups. The deliberate-play training program contained unstructured game forms in basketball. The placebo group played in traditional structured basketball game forms. Tactical intelligence and creativity was assessed before and after an 18-lesson intervention. Analysis showed significant training improvement only for the deliberate-play group. In addition, this outperformance of the placebo group was not only observed for tactical creativity but also for tactical intelligence.

Ontology for E-Learning: A Case Study

ERIC Educational Resources Information Center

Colace, Francesco; De Santo, Massimo; Gaeta, Matteo

2009-01-01

Purpose: The development of adaptable and intelligent educational systems is widely considered one of the great challenges in scientific research. Among key elements for building advanced training systems, an important role is played by methodologies chosen for knowledge representation. In this scenario, the introduction of ontology formalism can…

Making intelligent systems team players. A guide to developing intelligent monitoring systems

NASA Technical Reports Server (NTRS)

Land, Sherry A.; Malin, Jane T.; Thronesberry, Carroll; Schreckenghost, Debra L.

1995-01-01

This reference guide for developers of intelligent monitoring systems is based on lessons learned by developers of the DEcision Support SYstem (DESSY), an expert system that monitors Space Shuttle telemetry data in real time. DESSY makes inferences about commands, state transitions, and simple failures. It performs failure detection rather than in-depth failure diagnostics. A listing of rules from DESSY and cue cards from DESSY subsystems are included to give the development community a better understanding of the selected model system. The G-2 programming tool used in developing DESSY provides an object-oriented, rule-based environment, but many of the principles in use here can be applied to any type of monitoring intelligent system. The step-by-step instructions and examples given for each stage of development are in G-2, but can be used with other development tools. This guide first defines the authors' concept of real-time monitoring systems, then tells prospective developers how to determine system requirements, how to build the system through a combined design/development process, and how to solve problems involved in working with real-time data. It explains the relationships among operational prototyping, software evolution, and the user interface. It also explains methods of testing, verification, and validation. It includes suggestions for preparing reference documentation and training users.

Ambient intelligence systems for personalized sport training.

PubMed

Vales-Alonso, Javier; López-Matencio, Pablo; Gonzalez-Castaño, Francisco J; Navarro-Hellín, Honorio; Baños-Guirao, Pedro J; Pérez-Martínez, Francisco J; Martínez-Álvarez, Rafael P; González-Jiménez, Daniel; Gil-Castiñeira, Felipe; Duro-Fernández, Richard

2010-01-01

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project "Ambient Intelligence Systems Support for Athletes with Specific Profiles", which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes' mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes' training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m, s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably.

Ambient Intelligence Systems for Personalized Sport Training

PubMed Central

Vales-Alonso, Javier; López-Matencio, Pablo; Gonzalez-Castaño, Francisco J.; Navarro-Hellín, Honorio; Baños-Guirao, Pedro J.; Pérez-Martínez, Francisco J.; Martínez-Álvarez, Rafael P.; González-Jiménez, Daniel; Gil-Castiñeira, Felipe; Duro-Fernández, Richard

2010-01-01

Several research programs are tackling the use of Wireless Sensor Networks (WSN) at specific fields, such as e-Health, e-Inclusion or e-Sport. This is the case of the project “Ambient Intelligence Systems Support for Athletes with Specific Profiles”, which intends to assist athletes in their training. In this paper, the main developments and outcomes from this project are described. The architecture of the system comprises a WSN deployed in the training area which provides communication with athletes’ mobile equipments, performs location tasks, and harvests environmental data (wind speed, temperature, etc.). Athletes are equipped with a monitoring unit which obtains data from their training (pulse, speed, etc.). Besides, a decision engine combines these real-time data together with static information about the training field, and from the athlete, to direct athletes’ training to fulfill some specific goal. A prototype is presented in this work for a cross country running scenario, where the objective is to maintain the heart rate (HR) of the runner in a target range. For each track, the environmental conditions (temperature of the next track), the current athlete condition (HR), and the intrinsic difficulty of the track (slopes) influence the performance of the athlete. The decision engine, implemented by means of (m, s)-splines interpolation, estimates the future HR and selects the best track in each fork of the circuit. This method achieves a success ratio in the order of 80%. Indeed, results demonstrate that if environmental information is not take into account to derive training orders, the success ratio is reduced notably. PMID:22294931

Improving fluid intelligence with training on working memory.

PubMed

Jaeggi, Susanne M; Buschkuehl, Martin; Jonides, John; Perrig, Walter J

2008-05-13

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications.

Improving fluid intelligence with training on working memory

PubMed Central

Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J.

2008-01-01

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications. PMID:18443283

Word Processor Training on Intelligent Videodisc.

ERIC Educational Resources Information Center

Yampolsky, Michael

1983-01-01

Presents an overview of the Wang Word Processing Intelligent Learning Program on interactive videodisc, which is used at Eastman Kodak to train hundreds of word processing operators. Operation of the program is discussed in detail. (MBR)

Short-term music training enhances verbal intelligence and executive function.

PubMed

Moreno, Sylvain; Bialystok, Ellen; Barac, Raluca; Schellenberg, E Glenn; Cepeda, Nicholas J; Chau, Tom

2011-11-01

Researchers have designed training methods that can be used to improve mental health and to test the efficacy of education programs. However, few studies have demonstrated broad transfer from such training to performance on untrained cognitive activities. Here we report the effects of two interactive computerized training programs developed for preschool children: one for music and one for visual art. After only 20 days of training, only children in the music group exhibited enhanced performance on a measure of verbal intelligence, with 90% of the sample showing this improvement. These improvements in verbal intelligence were positively correlated with changes in functional brain plasticity during an executive-function task. Our findings demonstrate that transfer of a high-level cognitive skill is possible in early childhood.

Training Strategies for the Twenty-First Century: Using Recent Research on Learning To Enhance Training.

ERIC Educational Resources Information Center

Dwyer, Brian M.

2002-01-01

Discusses a new training model that takes into account the diversity of learners and the emotional, physical and social environmental conditions essential for lifelong learning. Considers how the brain learns and functions, brain-based learning, multiple intelligence, and emotional intelligence as well as personal reflection. (LRW)

Competitive Intelligence.

ERIC Educational Resources Information Center

Bergeron, Pierrette; Hiller, Christine A.

2002-01-01

Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

Adding an Intelligent Tutoring System to an Existing Training Simulation

DTIC Science & Technology

2006-01-01

to apply information in a job should be the goal of training. Also, conventional IMI is not able to meaningfully incorporate use of free - play simulators...incorporating desktop free - play simulators into computer-based training since the software can stand in for a human tutor in all the roles. Existing IMI...2. ITS can integrate free - play simulators and IMI BC2010 ITS DESCRIPTION Overview Figure 3 illustrates the interaction between BC2010, ITS

A structure for maturing intelligent tutoring system student models

NASA Technical Reports Server (NTRS)

Holmes, Willard M.

1990-01-01

A special structure is examined for evolving a detached model of the user of an intelligent tutoring system. Tutoring is used in the context of education and training devices. A detached approach to populating the student model data structure is examined in the context of the need for time dependent reasoning about what the student knows about a particular concept in the domain of interest. This approach, to generating a data structure for the student model, allows an inference engine separate from the tutoring strategy determination to be used. This methodology has advantages in environments requiring real-time operation.

Instructional authoring by direct manipulation of simulations: Exploratory applications of RAPIDS. RAPIDS 2 authoring manual

NASA Technical Reports Server (NTRS)

1990-01-01

RAPIDS II is a simulation-based intelligent tutoring system environment. It is a system for producing computer-based training courses that are built on the foundation of graphical simulations. RAPIDS II simulations can be animated and they can have continuously updating elements.

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.

A General Architecture for Intelligent Tutoring of Diagnostic Classification Problem Solving

PubMed Central

Crowley, Rebecca S.; Medvedeva, Olga

2003-01-01

We report on a general architecture for creating knowledge-based medical training systems to teach diagnostic classification problem solving. The approach is informed by our previous work describing the development of expertise in classification problem solving in Pathology. The architecture envelops the traditional Intelligent Tutoring System design within the Unified Problem-solving Method description Language (UPML) architecture, supporting component modularity and reuse. Based on the domain ontology, domain task ontology and case data, the abstract problem-solving methods of the expert model create a dynamic solution graph. Student interaction with the solution graph is filtered through an instructional layer, which is created by a second set of abstract problem-solving methods and pedagogic ontologies, in response to the current state of the student model. We outline the advantages and limitations of this general approach, and describe it’s implementation in SlideTutor–a developing Intelligent Tutoring System in Dermatopathology. PMID:14728159

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

An architectural approach to create self organizing control systems for practical autonomous robots

NASA Technical Reports Server (NTRS)

Greiner, Helen

1991-01-01

For practical industrial applications, the development of trainable robots is an important and immediate objective. Therefore, the developing of flexible intelligence directly applicable to training is emphasized. It is generally agreed upon by the AI community that the fusion of expert systems, neural networks, and conventionally programmed modules (e.g., a trajectory generator) is promising in the quest for autonomous robotic intelligence. Autonomous robot development is hindered by integration and architectural problems. Some obstacles towards the construction of more general robot control systems are as follows: (1) Growth problem; (2) Software generation; (3) Interaction with environment; (4) Reliability; and (5) Resource limitation. Neural networks can be successfully applied to some of these problems. However, current implementations of neural networks are hampered by the resource limitation problem and must be trained extensively to produce computationally accurate output. A generalization of conventional neural nets is proposed, and an architecture is offered in an attempt to address the above problems.

A Data Management System for International Space Station Simulation Tools

NASA Technical Reports Server (NTRS)

Betts, Bradley J.; DelMundo, Rommel; Elcott, Sharif; McIntosh, Dawn; Niehaus, Brian; Papasin, Richard; Mah, Robert W.; Clancy, Daniel (Technical Monitor)

2002-01-01

Groups associated with the design, operational, and training aspects of the International Space Station make extensive use of modeling and simulation tools. Users of these tools often need to access and manipulate large quantities of data associated with the station, ranging from design documents to wiring diagrams. Retrieving and manipulating this data directly within the simulation and modeling environment can provide substantial benefit to users. An approach for providing these kinds of data management services, including a database schema and class structure, is presented. Implementation details are also provided as a data management system is integrated into the Intelligent Virtual Station, a modeling and simulation tool developed by the NASA Ames Smart Systems Research Laboratory. One use of the Intelligent Virtual Station is generating station-related training procedures in a virtual environment, The data management component allows users to quickly and easily retrieve information related to objects on the station, enhancing their ability to generate accurate procedures. Users can associate new information with objects and have that information stored in a database.

Emerging CAE technologies and their role in Future Ambient Intelligence Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2011-03-01

Dramatic improvements are on the horizon in Computer Aided Engineering (CAE) and various simulation technologies. The improvements are due, in part, to the developments in a number of leading-edge technologies and their synergistic combinations/convergence. The technologies include ubiquitous, cloud, and petascale computing; ultra high-bandwidth networks, pervasive wireless communication; knowledge based engineering; networked immersive virtual environments and virtual worlds; novel human-computer interfaces; and powerful game engines and facilities. This paper describes the frontiers and emerging simulation technologies, and their role in the future virtual product creation and learning/training environments. The environments will be ambient intelligence environments, incorporating a synergistic combination of novel agent-supported visual simulations (with cognitive learning and understanding abilities); immersive 3D virtual world facilities; development chain management systems and facilities (incorporating a synergistic combination of intelligent engineering and management tools); nontraditional methods; intelligent, multimodal and human-like interfaces; and mobile wireless devices. The Virtual product creation environment will significantly enhance the productivity and will stimulate creativity and innovation in future global virtual collaborative enterprises. The facilities in the learning/training environment will provide timely, engaging, personalized/collaborative and tailored visual learning.

Reverse engineering the human: artificial intelligence and acting theory

NASA Astrophysics Data System (ADS)

Soto-Morettini, Donna

2017-01-01

In two separate papers, Artificial Intelligence (AI)/Robotics researcher Guy Hoffman takes as a starting point that actors have been in the business of reverse engineering human behaviour for centuries. In this paper, I follow the similar trajectories of AI and acting theory (AT), looking at three primary questions, in the hope of framing a response to Hoffman's papers: (1) How are the problems of training a human to simulate a fictional human both similar to and different from training a machine to simulate a human? (2) How are the larger questions of AI design and architecture similar to the larger questions that still remain within the area of AT? (3) Is there anything in the work of AI design that might advance the work of acting theorists and practitioners? The paper explores the use of "swarm intelligence" in recent models of both AT and AI, and considers the issues of embodied cognition, and the kinds of intelligence that enhances or inhibits imaginative immersion for the actor, and concludes with a consideration of the ontological questions raised by the trend towards intersubjective, dynamic systems of generative thought in both AT and AI.

A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment.

PubMed

Li, Yongcheng; Sun, Rong; Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

2016-01-01

We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot's performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks.

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

PubMed

Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

2018-05-01

A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

A Novel Robot System Integrating Biological and Mechanical Intelligence Based on Dissociated Neural Network-Controlled Closed-Loop Environment

PubMed Central

Wang, Yuechao; Li, Hongyi; Zheng, Xiongfei

2016-01-01

We propose the architecture of a novel robot system merging biological and artificial intelligence based on a neural controller connected to an external agent. We initially built a framework that connected the dissociated neural network to a mobile robot system to implement a realistic vehicle. The mobile robot system characterized by a camera and two-wheeled robot was designed to execute the target-searching task. We modified a software architecture and developed a home-made stimulation generator to build a bi-directional connection between the biological and the artificial components via simple binomial coding/decoding schemes. In this paper, we utilized a specific hierarchical dissociated neural network for the first time as the neural controller. Based on our work, neural cultures were successfully employed to control an artificial agent resulting in high performance. Surprisingly, under the tetanus stimulus training, the robot performed better and better with the increasement of training cycle because of the short-term plasticity of neural network (a kind of reinforced learning). Comparing to the work previously reported, we adopted an effective experimental proposal (i.e. increasing the training cycle) to make sure of the occurrence of the short-term plasticity, and preliminarily demonstrated that the improvement of the robot’s performance could be caused independently by the plasticity development of dissociated neural network. This new framework may provide some possible solutions for the learning abilities of intelligent robots by the engineering application of the plasticity processing of neural networks, also for the development of theoretical inspiration for the next generation neuro-prostheses on the basis of the bi-directional exchange of information within the hierarchical neural networks. PMID:27806074

Sensemaking Training Requirements for the Adaptive Battlestaff

DTIC Science & Technology

2007-06-01

for the Adaptive Battlestaff Topic: Cognitive and Social Issues Celestine A. Ntuen1& Dennis Leedom2 1Army Center for Human-Centric Command...intelligent analysts. We need a new training strategy, paradigms, and methods for this purpose. The sensemaking trainability factors o must be identified...juxtapositions of social forces—a complex of network of information systems with people, technology, and domains of adversaries (tasks) that have been

Development and training of a learning expert system in an autonomous mobile robot via simulation

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

Spelt, P.F.; Lyness, E.; DeSaussure, G.

1989-11-01

The Center for Engineering Systems Advanced Research (CESAR) conducts basic research in the area of intelligent machines. Recently at CESAR a learning expert system was created to operate on board an autonomous robot working at a process control panel. The authors discuss two-computer simulation system used to create, evaluate and train this learning system. The simulation system has a graphics display of the current status of the process being simulated, and the same program which does the simulating also drives the actual control panel. Simulation results were validated on the actual robot. The speed and safety values of using amore » computerized simulator to train a learning computer, and future uses of the simulation system, are discussed.« less

Low-Cost, Full-Field Surface Profiling Tool for Mechanical Damage Evaluation

DOT National Transportation Integrated Search

2010-03-03

In this project, Intelligent Optical Systems (IOS) developed an inexpensive, full-field, surfaceprofiling tool for mechanical damage evaluation based on the processing of a single digital image. Little operator training is required for acquiring the ...

ITS/CVO technical project management for non-technical managers : participant guide

DOT National Transportation Integrated Search

1998-09-01

In 1996, the FHWA Office of Motor Carriers (OMC) identified the need to develop a Technical Training Program to support the deployment of Intelligent Transportation System (ITS) technologies for Commercial Vehicle Operations (CVO). The workforce -...

Developing an Emotional Intelligence Program Training and Study Its Effectiveness on Emotional Intelligence of Adolescents with Emotional and Behavioral Problems That Living in Single Parent Families

ERIC Educational Resources Information Center

Motamedi, Farzaneh; Ghobari-Bonab, Bagher; Beh-pajooh, Ahmad; Yekta, Mohsen Shokoohi; Afrooz, Gholam Ali

2017-01-01

Development of children and adolescents' personality is strongly affected by their parents, and absence of one of them has an undesirable effect on their development, and makes them vulnerable to later psychological disorders and behavioral problems. The purpose of this study was to develop an emotional intelligence training program and to…

Optimization of knowledge-based systems and expert system building tools

NASA Technical Reports Server (NTRS)

Yasuda, Phyllis; Mckellar, Donald

1993-01-01

The objectives of the NASA-AMES Cooperative Agreement were to investigate, develop, and evaluate, via test cases, the system parameters and processing algorithms that constrain the overall performance of the Information Sciences Division's Artificial Intelligence Research Facility. Written reports covering various aspects of the grant were submitted to the co-investigators for the grant. Research studies concentrated on the field of artificial intelligence knowledge-based systems technology. Activities included the following areas: (1) AI training classes; (2) merging optical and digital processing; (3) science experiment remote coaching; (4) SSF data management system tests; (5) computer integrated documentation project; (6) conservation of design knowledge project; (7) project management calendar and reporting system; (8) automation and robotics technology assessment; (9) advanced computer architectures and operating systems; and (10) honors program.

Effects of cross-language voice training on speech perception: Whose familiar voices are more intelligible?

PubMed Central

Levi, Susannah V.; Winters, Stephen J.; Pisoni, David B.

2011-01-01

Previous research has shown that familiarity with a talker’s voice can improve linguistic processing (herein, “Familiar Talker Advantage”), but this benefit is constrained by the context in which the talker’s voice is familiar. The current study examined how familiarity affects intelligibility by manipulating the type of talker information available to listeners. One group of listeners learned to identify bilingual talkers’ voices from English words, where they learned language-specific talker information. A second group of listeners learned the same talkers from German words, and thus only learned language-independent talker information. After voice training, both groups of listeners completed a word recognition task with English words produced by both familiar and unfamiliar talkers. Results revealed that English-trained listeners perceived more phonemes correct for familiar than unfamiliar talkers, while German-trained listeners did not show improved intelligibility for familiar talkers. The absence of a processing advantage in speech intelligibility for the German-trained listeners demonstrates limitations on the Familiar Talker Advantage, which crucially depends on the language context in which the talkers’ voices were learned; knowledge of how a talker produces linguistically relevant contrasts in a particular language is necessary to increase speech intelligibility for words produced by familiar talkers. PMID:22225059

The effectiveness of cognitive-behavioral group therapy training on improving emotional intelligence and general health of adolescents.

PubMed

Aghel Masjedi, M; Taghavizadeh, M; Azadi, N; Hosseinzadeh, F; Koushkestani, A

2015-01-01

Introduction: The aim of the current research was to examine the effectiveness of cognitive-behavioral group therapy (CBT) training on the general health and improve the emotional intelligence of male adolescents in Tehran city. Methodology: The current research is a semi-trial research with pretest-posttest experimental design and two test and control groups, which were carried out in the 2014-2015 academic year. 40 high school male students were chosen via proper sampling approach and they were stochastically classified into test and control team (each team, n = 20). The students were protested via Baron emotional intelligence and GHQ-28 general health questionnaire. Subsequently, the test group was trained in the cognitive-behavioral group therapy for eight sessions and the control group received no interventions. In the end, both groups were post-tested, and the data were investigated by using a multivariate investigation of covariance method and SPSS-20. Findings: The outcomes demonstrated that there were notable distinctions between the experiment and the checking teams after the implementation of the CBT training (P < 0.001) so that the average score of emotional intelligence and general health increased in test group rather than in the check team. Conclusion: The findings indicated that the CBT practice is useful in improving emotional intelligence and general health in adolescent male students. Thus, one can recommend that appropriate therapy training could be designed to improve their emotional intelligence and general health.

The effectiveness of cognitive-behavioral group therapy training on improving emotional intelligence and general health of adolescents

PubMed Central

Aghel Masjedi, M; Taghavizadeh, M; Azadi, N; Hosseinzadeh, F; Koushkestani, A

2015-01-01

Introduction: The aim of the current research was to examine the effectiveness of cognitive-behavioral group therapy (CBT) training on the general health and improve the emotional intelligence of male adolescents in Tehran city. Methodology: The current research is a semi-trial research with pretest-posttest experimental design and two test and control groups, which were carried out in the 2014-2015 academic year. 40 high school male students were chosen via proper sampling approach and they were stochastically classified into test and control team (each team, n = 20). The students were protested via Baron emotional intelligence and GHQ-28 general health questionnaire. Subsequently, the test group was trained in the cognitive-behavioral group therapy for eight sessions and the control group received no interventions. In the end, both groups were post-tested, and the data were investigated by using a multivariate investigation of covariance method and SPSS-20. Findings: The outcomes demonstrated that there were notable distinctions between the experiment and the checking teams after the implementation of the CBT training (P < 0.001) so that the average score of emotional intelligence and general health increased in test group rather than in the check team. Conclusion: The findings indicated that the CBT practice is useful in improving emotional intelligence and general health in adolescent male students. Thus, one can recommend that appropriate therapy training could be designed to improve their emotional intelligence and general health. PMID:28316719

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).

Intelligent Tutor

NASA Technical Reports Server (NTRS)

1990-01-01

NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

Emergency Response Virtual Environment for Safe Schools

NASA Technical Reports Server (NTRS)

Wasfy, Ayman; Walker, Teresa

2008-01-01

An intelligent emergency response virtual environment (ERVE) that provides emergency first responders, response planners, and managers with situational awareness as well as training and support for safe schools is presented. ERVE incorporates an intelligent agent facility for guiding and assisting the user in the context of the emergency response operations. Response information folders capture key information about the school. The system enables interactive 3D visualization of schools and academic campuses, including the terrain and the buildings' exteriors and interiors in an easy to use Web..based interface. ERVE incorporates live camera and sensors feeds and can be integrated with other simulations such as chemical plume simulation. The system is integrated with a Geographical Information System (GIS) to enable situational awareness of emergency events and assessment of their effect on schools in a geographic area. ERVE can also be integrated with emergency text messaging notification systems. Using ERVE, it is now possible to address safe schools' emergency management needs with a scaleable, seamlessly integrated and fully interactive intelligent and visually compelling solution.

Developing an Intelligent System for Diagnosis of Asthma Based on Artificial Neural Network.

PubMed

Alizadeh, Behrouz; Safdari, Reza; Zolnoori, Maryam; Bashiri, Azadeh

2015-08-01

Lack of proper diagnosis and inadequate treatment of asthma, leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different modes was made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. So considering the data mining approaches due to the nature of medical data is necessary.

A learning-based agent for home neurorehabilitation.

PubMed

Lydakis, Andreas; Meng, Yuanliang; Munroe, Christopher; Wu, Yi-Ning; Begum, Momotaz

2017-07-01

This paper presents the iterative development of an artificially intelligent system to promote home-based neurorehabilitation. Although proper, structured practice of rehabilitation exercises at home is the key to successful recovery of motor functions, there is no home-program out there which can monitor a patient's exercise-related activities and provide corrective feedback in real time. To this end, we designed a Learning from Demonstration (LfD) based home-rehabilitation framework that combines advanced robot learning algorithms with commercially available wearable technologies. The proposed system uses exercise-related motion information and electromyography signals (EMG) of a patient to train a Markov Decision Process (MDP). The trained MDP model can enable an agent to serve as a coach for a patient. On a system level, this is the first initiative, to the best of our knowledge, to employ LfD in an health-care application to enable lay users to program an intelligent system. From a rehabilitation research perspective, this is a completely novel initiative to employ machine learning to provide interactive corrective feedback to a patient in home settings.

Artificial intelligence technology assessment for the US Army Depot System Command

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

Pennock, K A

1991-07-01

This assessment of artificial intelligence (AI) has been prepared for the US Army's Depot System Command (DESCOM) by Pacific Northwest Laboratory. The report describes several of the more promising AI technologies, focusing primarily on knowledge-based systems because they have been more successful in commercial applications than any other AI technique. The report also identifies potential Depot applications in the areas of procedural support, scheduling and planning, automated inspection, training, diagnostics, and robotic systems. One of the principal objectives of the report is to help decisionmakers within DESCOM to evaluate AI as a possible tool for solving individual depot problems. Themore » report identifies a number of factors that should be considered in such evaluations. 22 refs.« less

INTERIOR OF TARGET INTELLIGENCE ROOM. view TO WEST. Plattsburgh ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

INTERIOR OF TARGET INTELLIGENCE ROOM. view TO WEST. - Plattsburgh Air Force Base, Target Intelligence Training Building-Combat Center, Off Connecticut Road, east of Idaho Avenue, Plattsburgh, Clinton County, NY

Defense Intelligence: Foreign Area/Language Needs and Academe.

ERIC Educational Resources Information Center

SRI International, Menlo Park, CA.

The Department of Defense's (DOD) need for foreign language/area expertise was assessed, along with opportunities for the academic community to supplement government training. In addition to interviewing intelligence managers, questionnaires were administered to defense analysts to determine their background, training, and use of external…

Can Intelligence Be Taught? Fastback 29.

ERIC Educational Resources Information Center

Sexton, Thomas G.; Poling, Donald R.

This booklet cites evidence indicating that intelligence can be trained, given a physiologically normal student and an intensely persistant tutor. Methodologies for increasing mental efficiency have in common the principle of coordination of physical and mental processes, whether achieved by simple relaxation training, brain polarization, or…

An overview of the education and training component of RICIS

NASA Technical Reports Server (NTRS)

Freedman, Glenn B.

1987-01-01

Research in education and training according to RICIS (Research Institute for Computing and Information Systems) program focuses on means to disseminate knowledge, skills, and technological advances rapidly, accurately, and effectively. A range of areas for study include: artificial intelligence, hypermedia and full-text retrieval strategies, use of mass storage and retrieval options such as CD-ROM and laser disks, and interactive video and interactive media presentations.

Intelligent Virtual Station (IVS)

NASA Technical Reports Server (NTRS)

2002-01-01

The Intelligent Virtual Station (IVS) is enabling the integration of design, training, and operations capabilities into an intelligent virtual station for the International Space Station (ISS). A viewgraph of the IVS Remote Server is presented.

TARDEC Annual Report 2010

DTIC Science & Technology

2011-06-15

capable of engaging threats while interacting with system operators. Through autonomous perception and navigation, intelligent tactical behavior... systems integration approach. TARDEC’s role is to assess the best way to apply the VICTORY architecture to future tactical wheeled vehicles and...Track tops Thrown Object Protection System traDoc U.S. Army Training and Doctrine Command twVs Tactical Wheeled Vehicle Survivability ugV Unmanned

University Research Initiative Research Program Summaries

DTIC Science & Technology

1987-06-01

application to intelligent tutoring systems (John Anderson), o Autonomous learning systems (Jaime Carbonell), o Learning algorithms for parallel processing...test them. The primary project will be: o Learning mechanisms in scientific discovery (Herbert Simon). Tutoring systems. These projects are aimed at...near-term results. They 19 will produce tutors for training specific subject matter areas. These projects will push theories of learning forward by

Bringing Chatbots into education: Towards Natural Language Negotiation of Open Learner Models

NASA Astrophysics Data System (ADS)

Kerlyl, Alice; Hall, Phil; Bull, Susan

There is an extensive body of work on Intelligent Tutoring Systems: computer environments for education, teaching and training that adapt to the needs of the individual learner. Work on personalisation and adaptivity has included research into allowing the student user to enhance the system's adaptivity by improving the accuracy of the underlying learner model. Open Learner Modelling, where the system's model of the user's knowledge is revealed to the user, has been proposed to support student reflection on their learning. Increased accuracy of the learner model can be obtained by the student and system jointly negotiating the learner model. We present the initial investigations into a system to allow people to negotiate the model of their understanding of a topic in natural language. This paper discusses the development and capabilities of both conversational agents (or chatbots) and Intelligent Tutoring Systems, in particular Open Learner Modelling. We describe a Wizard-of-Oz experiment to investigate the feasibility of using a chatbot to support negotiation, and conclude that a fusion of the two fields can lead to developing negotiation techniques for chatbots and the enhancement of the Open Learner Model. This technology, if successful, could have widespread application in schools, universities and other training scenarios.

Effects of Emotional Intelligence and Locus of Control Training on the Psychological Well-Being of Adolescents with Visual Impairments in Nigeria

ERIC Educational Resources Information Center

Eniola, M. S.; Ajobiewe, Abthonia Ifeoma

2013-01-01

This current study, investigated the relative effectiveness of Emotional Intelligence Training (EIT) and Locus of Control Training (LCT) on the psychological well-being of adolescent with visual impairment. The pretest-posttest control group experimental design with a 3x2x2 factorial matrix was used. The participants were 120 adolescents with…

Dual N-Back Working Memory Training in Healthy Adults: A Randomized Comparison to Processing Speed Training

PubMed Central

Lawlor-Savage, Linette; Goghari, Vina M.

2016-01-01

Enhancing cognitive ability is an attractive concept, particularly for middle-aged adults interested in maintaining cognitive functioning and preventing age-related declines. Computerized working memory training has been investigated as a safe method of cognitive enhancement in younger and older adults, although few studies have considered the potential impact of working memory training on middle-aged adults. This study investigated dual n-back working memory training in healthy adults aged 30–60. Fifty-seven adults completed measures of working memory, processing speed, and fluid intelligence before and after a 5-week web-based dual n-back or active control (processing speed) training program. Results: Repeated measures multivariate analysis of variance failed to identify improvements across the three cognitive composites, working memory, processing speed, and fluid intelligence, after training. Follow-up Bayesian analyses supported null findings for training effects for each individual composite. Findings suggest that dual n-back working memory training may not benefit working memory or fluid intelligence in healthy adults. Further investigation is necessary to clarify if other forms of working memory training may be beneficial, and what factors impact training-related benefits, should they occur, in this population. PMID:27043141

DETAIL OF DOORWAY INTO COMBAT INTELLIGENCE ROOM. view TO WEST. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

DETAIL OF DOORWAY INTO COMBAT INTELLIGENCE ROOM. view TO WEST. - Plattsburgh Air Force Base, Target Intelligence Training Building-Combat Center, Off Connecticut Road, east of Idaho Avenue, Plattsburgh, Clinton County, NY

Selecting Appropriate Functionality and Technologies for EPSS.

ERIC Educational Resources Information Center

McGraw, Karen L.

1995-01-01

Presents background information that describes the major components of an embedded performance support system, compares levels of functionality, and discusses some of the required technologies. Highlights include the human-computer interface; online help; advisors; training and tutoring; hypermedia; and artificial intelligence techniques. (LRW)

Speech intelligibility in complex acoustic environments in young children

NASA Astrophysics Data System (ADS)

Litovsky, Ruth

2003-04-01

While the auditory system undergoes tremendous maturation during the first few years of life, it has become clear that in complex scenarios when multiple sounds occur and when echoes are present, children's performance is significantly worse than their adult counterparts. The ability of children (3-7 years of age) to understand speech in a simulated multi-talker environment and to benefit from spatial separation of the target and competing sounds was investigated. In these studies, competing sources vary in number, location, and content (speech, modulated or unmodulated speech-shaped noise and time-reversed speech). The acoustic spaces were also varied in size and amount of reverberation. Finally, children with chronic otitis media who received binaural training were tested pre- and post-training on a subset of conditions. Results indicated the following. (1) Children experienced significantly more masking than adults, even in the simplest conditions tested. (2) When the target and competing sounds were spatially separated speech intelligibility improved, but the amount varied with age, type of competing sound, and number of competitors. (3) In a large reverberant classroom there was no benefit of spatial separation. (4) Binaural training improved speech intelligibility performance in children with otitis media. Future work includes similar studies in children with unilateral and bilateral cochlear implants. [Work supported by NIDCD, DRF, and NOHR.

Student Modeling in Orthopedic Surgery Training: Exploiting Symbiosis between Temporal Bayesian Networks and Fine-Grained Didactic Analysis

ERIC Educational Resources Information Center

Chieu, Vu Minh; Luengo, Vanda; Vadcard, Lucile; Tonetti, Jerome

2010-01-01

Cognitive approaches have been used for student modeling in intelligent tutoring systems (ITSs). Many of those systems have tackled fundamental subjects such as mathematics, physics, and computer programming. The change of the student's cognitive behavior over time, however, has not been considered and modeled systematically. Furthermore, the…

Adaptive Reading and Writing Instruction in iSTART and W-Pal

ERIC Educational Resources Information Center

Johnson, Amy M.; McCarthy, Kathryn S.; Kopp, Kristopher J.; Perret, Cecile A.; McNamara, Danielle S.

2017-01-01

Intelligent tutoring systems for ill-defined domains, such as reading and writing, are critically needed, yet uncommon. Two such systems, the Interactive Strategy Training for Active Reading and Thinking (iSTART) and Writing Pal (W-Pal) use natural language processing (NLP) to assess learners' written (i.e., typed) responses and provide immediate,…

Learning Emotional Intelligence: Training & Assessment

ERIC Educational Resources Information Center

Shults, Allison

2015-01-01

This core assessment provides an overview and training of the use of Emotional Intelligence (EI) in the workplace. It includes a needs analysis for a local Chamber of Commerce, and outlines the importance of improving their organizational communication with the improvement of their EI. Behavioral objectives related to the skills needed are…

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

NASA Technical Reports Server (NTRS)

Ali, Moonis; Whitehead, Bruce; Gupta, Uday K.; Ferber, Harry

1989-01-01

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

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

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

System Diagnostic Builder - A rule generation tool for expert systems that do intelligent data evaluation. [applied to Shuttle Mission Simulator

NASA Technical Reports Server (NTRS)

Nieten, Joseph; Burke, Roger

1993-01-01

Consideration is given to the System Diagnostic Builder (SDB), an automated knowledge acquisition tool using state-of-the-art AI technologies. The SDB employs an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert. Thus, data are captured from the subject system, classified, and used to drive the rule generation process. These rule bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The knowledge bases captured from the Shuttle Mission Simulator can be used as black box simulations by the Intelligent Computer Aided Training devices. The SDB can also be used to construct knowledge bases for the process control industry, such as chemical production or oil and gas production.

Will There Be Teachers in the Classroom of the Future?.... But We Don't Think about That.

ERIC Educational Resources Information Center

Chaiklin, Seth; Lewis, Matthew W.

1988-01-01

The impact of ICAI systems on teacher role, classroom structure, educational goals and preservice teacher training are discussed. The artificial intelligence research community is urged to consider the societal impact of its work. (Author/JL)

Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

NASA Astrophysics Data System (ADS)

Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

AI in manufacturing

NASA Astrophysics Data System (ADS)

Gross, John E.; Minato, Rick; Smith, David M.; Loftin, R. B.; Savely, Robert T.

1991-10-01

AI techniques are shown to have been useful in such aerospace industry tasks as vehicle configuration layouts, process planning, tool design, numerically-controlled programming of tools, production scheduling, and equipment testing and diagnosis. Accounts are given of illustrative experiences at the production facilities of three major aerospace defense contractors. Also discussed is NASA's autonomous Intelligent Computer-Aided Training System, for such ambitious manned programs as Space Station Freedom, which employs five different modules to constitute its job-independent training architecture.

“Chickens Are a Lot Smarter than I Originally Thought”: Changes in Student Attitudes to Chickens Following a Chicken Training Class

PubMed Central

Hazel, Susan J.; O’Dwyer, Lisel; Ryan, Terry

2015-01-01

Simple Summary Our attitudes to animals are linked to our beliefs about their cognitive abilities, such as intelligence and capacity to experience emotional states. In this study, undergraduate students were surveyed on their attitudes to chickens pre- and post- a practical class in which they learnt to clicker train chickens. Students were more likely to agree that chickens are intelligent and easy to teach tricks to, and that chickens feel emotions such as boredom, frustration and happiness, following the practical class. Similar workshops may be an effective method to improve animal training skills, and promote more positive attitudes to specific animal species. Abstract A practical class using clicker training of chickens to apply knowledge of how animals learn and practice skills in animal training was added to an undergraduate course. Since attitudes to animals are related to their perceived intelligence, surveys of student attitudes were completed pre- and post- the practical class, to determine if (1) the practical class changed students’ attitudes to chickens and their ability to experience affective states, and (2) any changes were related to previous contact with chickens, training experience or gender. In the post- versus pre-surveys, students agreed more that chickens are easy to teach tricks to, are intelligent, and have individual personalities and disagreed more that they are difficult to train and are slow learners. Following the class, they were more likely to believe chickens experience boredom, frustration and happiness. Females rated the intelligence and ability to experience affective states in chickens more highly than males, although there were shifts in attitude in both genders. This study demonstrated shifts in attitudes following a practical class teaching clicker training in chickens. Similar practical classes may provide an effective method of teaching animal training skills and promoting more positive attitudes to animals. PMID:26479388

Neural imaging to track mental states while using an intelligent tutoring system.

PubMed

Anderson, John R; Betts, Shawn; Ferris, Jennifer L; Fincham, Jon M

2010-04-13

Hemodynamic measures of brain activity can be used to interpret a student's mental state when they are interacting with an intelligent tutoring system. Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distribution of solution times from measures of problem complexity. Separately, a linear discriminant analysis used fMRI data to predict whether or not students were engaged in problem solving. A hidden Markov algorithm merged these two sources of information to predict the mental states of students during problem-solving episodes. The algorithm was trained on data from 1 day of interaction and tested with data from a later day. In terms of predicting what state a student was in during a 2-s period, the algorithm achieved 87% accuracy on the training data and 83% accuracy on the test data. The results illustrate the importance of integrating the bottom-up information from imaging data with the top-down information from a cognitive model.

Intelligent power management in a vehicular system with multiple power sources

NASA Astrophysics Data System (ADS)

Murphey, Yi L.; Chen, ZhiHang; Kiliaris, Leonidas; Masrur, M. Abul

This paper presents an optimal online power management strategy applied to a vehicular power system that contains multiple power sources and deals with largely fluctuated load requests. The optimal online power management strategy is developed using machine learning and fuzzy logic. A machine learning algorithm has been developed to learn the knowledge about minimizing power loss in a Multiple Power Sources and Loads (M_PS&LD) system. The algorithm exploits the fact that different power sources used to deliver a load request have different power losses under different vehicle states. The machine learning algorithm is developed to train an intelligent power controller, an online fuzzy power controller, FPC_MPS, that has the capability of finding combinations of power sources that minimize power losses while satisfying a given set of system and component constraints during a drive cycle. The FPC_MPS was implemented in two simulated systems, a power system of four power sources, and a vehicle system of three power sources. Experimental results show that the proposed machine learning approach combined with fuzzy control is a promising technology for intelligent vehicle power management in a M_PS&LD power system.

Evolutionary and Neural Computing Based Decision Support System for Disease Diagnosis from Clinical Data Sets in Medical Practice.

PubMed

Sudha, M

2017-09-27

As a recent trend, various computational intelligence and machine learning approaches have been used for mining inferences hidden in the large clinical databases to assist the clinician in strategic decision making. In any target data the irrelevant information may be detrimental, causing confusion for the mining algorithm and degrades the prediction outcome. To address this issue, this study attempts to identify an intelligent approach to assist disease diagnostic procedure using an optimal set of attributes instead of all attributes present in the clinical data set. In this proposed Application Specific Intelligent Computing (ASIC) decision support system, a rough set based genetic algorithm is employed in pre-processing phase and a back propagation neural network is applied in training and testing phase. ASIC has two phases, the first phase handles outliers, noisy data, and missing values to obtain a qualitative target data to generate appropriate attribute reduct sets from the input data using rough computing based genetic algorithm centred on a relative fitness function measure. The succeeding phase of this system involves both training and testing of back propagation neural network classifier on the selected reducts. The model performance is evaluated with widely adopted existing classifiers. The proposed ASIC system for clinical decision support has been tested with breast cancer, fertility diagnosis and heart disease data set from the University of California at Irvine (UCI) machine learning repository. The proposed system outperformed the existing approaches attaining the accuracy rate of 95.33%, 97.61%, and 93.04% for breast cancer, fertility issue and heart disease diagnosis.

Individualised training to address variability of radiologists' performance

NASA Astrophysics Data System (ADS)

Sun, Shanghua; Taylor, Paul; Wilkinson, Louise; Khoo, Lisanne

2008-03-01

Computer-based tools are increasingly used for training and the continuing professional development of radiologists. We propose an adaptive training system to support individualised learning in mammography, based on a set of real cases, which are annotated with educational content by experienced breast radiologists. The system has knowledge of the strengths and weakness of each radiologist's performance: each radiologist is assessed to compute a profile showing how they perform on different sets of cases, classified by type of abnormality, breast density, and perceptual difficulty. We also assess variability in cognitive aspects of image perception, classifying errors made by radiologists as errors of search, recognition or decision. This is a novel element in our approach. The profile is used to select cases to present to the radiologist. The intelligent and flexible presentation of these cases distinguishes our system from existing training tools. The training cases are organised and indexed by an ontology we have developed for breast radiologist training, which is consistent with the radiologists' profile. Hence, the training system is able to select appropriate cases to compose an individualised training path, addressing the variability of the radiologists' performance. A substantial part of the system, the ontology has been evaluated on a large number of cases, and the training system is under implementation for further evaluation.

Modeling and simulating human teamwork behaviors using intelligent agents

NASA Astrophysics Data System (ADS)

Fan, Xiaocong; Yen, John

2004-12-01

Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors. Teamwork modeling is important for training humans in gaining collaborative skills, for supporting humans in making critical decisions by proactively gathering, fusing, and sharing information, and for building coherent teams with both humans and agents working effectively on intelligence-intensive problems. Teamwork modeling is also challenging because the research has spanned diverse disciplines from business management to cognitive science, human discourse, and distributed artificial intelligence. This article presents an extensive, but not exhaustive, list of work in the field, where the taxonomy is organized along two main dimensions: team social structure and social behaviors. Along the dimension of social structure, we consider agent-only teams and mixed human-agent teams. Along the dimension of social behaviors, we consider collaborative behaviors, communicative behaviors, helping behaviors, and the underpinning of effective teamwork-shared mental models. The contribution of this article is that it presents an organizational framework for analyzing a variety of teamwork simulation systems and for further studying simulated teamwork behaviors.

Do We Really Become Smarter When Our Fluid-Intelligence Test Scores Improve?

PubMed

Hayes, Taylor R; Petrov, Alexander A; Sederberg, Per B

2015-01-01

Recent reports of training-induced gains on fluid intelligence tests have fueled an explosion of interest in cognitive training-now a billion-dollar industry. The interpretation of these results is questionable because score gains can be dominated by factors that play marginal roles in the scores themselves, and because intelligence gain is not the only possible explanation for the observed control-adjusted far transfer across tasks. Here we present novel evidence that the test score gains used to measure the efficacy of cognitive training may reflect strategy refinement instead of intelligence gains. A novel scanpath analysis of eye movement data from 35 participants solving Raven's Advanced Progressive Matrices on two separate sessions indicated that one-third of the variance of score gains could be attributed to test-taking strategy alone, as revealed by characteristic changes in eye-fixation patterns. When the strategic contaminant was partialled out, the residual score gains were no longer significant. These results are compatible with established theories of skill acquisition suggesting that procedural knowledge tacitly acquired during training can later be utilized at posttest. Our novel method and result both underline a reason to be wary of purported intelligence gains, but also provide a way forward for testing for them in the future.

Self-Calibration and Optimal Response in Intelligent Sensors Design Based on Artificial Neural Networks

PubMed Central

Rivera, José; Carrillo, Mariano; Chacón, Mario; Herrera, Gilberto; Bojorquez, Gilberto

2007-01-01

The development of smart sensors involves the design of reconfigurable systems capable of working with different input sensors. Reconfigurable systems ideally should spend the least possible amount of time in their calibration. An autocalibration algorithm for intelligent sensors should be able to fix major problems such as offset, variation of gain and lack of linearity, as accurately as possible. This paper describes a new autocalibration methodology for nonlinear intelligent sensors based on artificial neural networks, ANN. The methodology involves analysis of several network topologies and training algorithms. The proposed method was compared against the piecewise and polynomial linearization methods. Method comparison was achieved using different number of calibration points, and several nonlinear levels of the input signal. This paper also shows that the proposed method turned out to have a better overall accuracy than the other two methods. Besides, experimentation results and analysis of the complete study, the paper describes the implementation of the ANN in a microcontroller unit, MCU. In order to illustrate the method capability to build autocalibration and reconfigurable systems, a temperature measurement system was designed and tested. The proposed method is an improvement over the classic autocalibration methodologies, because it impacts on the design process of intelligent sensors, autocalibration methodologies and their associated factors, like time and cost.

Testing and Evaluating C3I Systems That Employ AI. Volume 4. Published Articles

DTIC Science & Technology

1991-01-31

development performance in an naming, design and actions The system ’ s & Sophisticated system organizational setting) evaluated in a classroom setting by...observing designed as an intelligent the system in use and administering training aid in r questionnaires . Observers videotape and tave classroom setting...notes to assess how both students and instructors use the system in an actual classroom setting. Questionnaires are administered to both students and

Using Appreciative Intelligence for Ice-Breaking: A New Design

ERIC Educational Resources Information Center

Verma, Neena; Pathak, Anil Anand

2011-01-01

Purpose: The purpose of this paper is to highlight the importance of applying appreciative intelligence and appreciative inquiry concepts to design a possibly new model of ice-breaking, which is strengths-based and very often used in any training in general and team building training in particular. Design/methodology/approach: The design has…

Previous International Experience, Cross-Cultural Training, and Expatriates' Cross-Cultural Adjustment: Effects of Cultural Intelligence and Goal Orientation

ERIC Educational Resources Information Center

Koo Moon, Hyoung; Kwon Choi, Byoung; Shik Jung, Jae

2012-01-01

Although various antecedents of expatriates' cross-cultural adjustment have been addressed, previous international experience, predeparture cross-cultural training, and cultural intelligence (CQ) have been most frequently examined. However, there are few attempts that explore the effects of these antecedents simultaneously or consider the possible…

The Effectiveness of Staff Training Focused on Increasing Emotional Intelligence and Improving Interaction between Support Staff and Clients

ERIC Educational Resources Information Center

Zijlmans, L. J. M.; Embregts, P. J. C. M.; Gerits, L.; Bosman, A. M. T.; Derksen, J. J. L.

2015-01-01

Background: Recent research addressed the relationship between staff behaviour and challenging behaviour of individuals with an intellectual disability (ID). Consequently, research on interventions aimed at staff is warranted. The present study focused on the effectiveness of a staff training aimed at emotional intelligence and interactions…

The relationship between emotional intelligence, previous caring experience and mindfulness in student nurses and midwives: a cross sectional analysis.

PubMed

Snowden, Austyn; Stenhouse, Rosie; Young, Jenny; Carver, Hannah; Carver, Fiona; Brown, Norrie

2015-01-01

Emotional Intelligence (EI), previous caring experience and mindfulness training may have a positive impact on nurse education. More evidence is needed to support the use of these variables in nurse recruitment and retention. To explore the relationship between EI, gender, age, programme of study, previous caring experience and mindfulness training. Cross sectional element of longitudinal study. 938year one nursing, midwifery and computing students at two Scottish Higher Education Institutes (HEIs) who entered their programme in September 2013. Participants completed a measure of 'trait' EI: Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF); and 'ability' EI: Schutte's et al. (1998) Emotional Intelligence Scale (SEIS). Demographics, previous caring experience and previous training in mindfulness were recorded. Relationships between variables were tested using non-parametric tests. Emotional intelligence increased with age on both measures of EI [TEIQ-SF H(5)=15.157 p=0.001; SEIS H(5)=11.388, p=0.044]. Females (n=786) scored higher than males (n=149) on both measures [TEIQ-SF, U=44,931, z=-4.509, p<.001; SEIS, U=44,744, z=-5.563, p<.001]. Nursing students scored higher that computing students [TEIQ-SF H(5)=46,496, p<.001; SEIS H(5)=33.309, p<0.001. There were no statistically significant differences in TEIQ-SF scores between those who had previous mindfulness training (n=50) and those who had not (n=857) [U=22,980, z=0.864, p = 0.388]. However, median SEIS was statistically significantly different according to mindfulness training [U=25,115.5, z=2.05, p=.039]. Neither measure demonstrated statistically significantly differences between those with (n=492) and without (n=479) previous caring experience, [TEIQ-SF, U=112, 102, z=0.938, p=.348; SEIS, U=115,194.5, z=1.863, p=0.063]. Previous caring experience was not associated with higher emotional intelligence. Mindfulness training was associated with higher 'ability' emotional intelligence. Implications for recruitment, retention and further research are explored. Copyright © 2014. Published by Elsevier Ltd.

Serious Use of a Serious Game for Language Learning

ERIC Educational Resources Information Center

Johnson, W. Lewis

2010-01-01

The Tactical Language and Culture Training System (TLCTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners acquire communication skills through a combination of interactive lessons and serious games. Artificial intelligence plays multiple roles in this learning environment: to process the learner's…

Brain Training Draws Questions about Benefits

ERIC Educational Resources Information Center

Sparks, Sarah D.

2012-01-01

While programs to improve students' working memory are among the hottest new education interventions, new studies are calling into question whether exercises to improve this foundational skill can actually translate into greater intelligence, problem-solving ability, or academic achievement. Working memory is the system the mind uses to hold…

Knowledge Engineering (Or, Catching Black Cats in Dark Rooms).

ERIC Educational Resources Information Center

Ruyle, Kim E.

1993-01-01

Discusses knowledge engineering, its relationship to artificial intelligence, and possible applications to developing expert systems, job aids, and technical training. The educational background of knowledge engineers is considered; the role of subject matter experts is described; and examples of flow charts, lists, and pictorial representations…

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.

Theories of intelligence in children with reading disabilities: a training proposal.

PubMed

Pepi, Annamaria; Alesi, Marianna; Geraci, Maria

2004-12-01

A recent trend in the study of reading difficulties promotes multidimensional intervention, focusing on the reciprocal influences exerted by cognitive and emotional-motivational variables. This study evaluated improvements in reading performance as a function of metacognitive training in 36 children (M age = 8.7 yr.) with different representations of intelligence. Posttest evaluations show significantly more improvement in reading comprehension in children with an incremental theory of intelligence. These results indicate the importance of treatment programmes that take into account both the specificity of deficits and factors relating to the domain of motivation.

An Intelligent Computer-aided Training System (CAT) for Diagnosing Adult Illiterates: Integrating NASA Technology into Workplace Literacy

NASA Technical Reports Server (NTRS)

Yaden, David B., Jr.

1991-01-01

An important part of NASA's mission involves the secondary application of its technologies in the public and private sectors. One current application being developed is The Adult Literacy Evaluator, a simulation-based diagnostic tool designed to assess the operant literacy abilities of adults having difficulties in learning to read and write. Using Intelligent Computer-Aided Training (ICAT) system technology in addition to speech recognition, closed-captioned television (CCTV), live video and other state-of-the-art graphics and storage capabilities, this project attempts to overcome the negative effects of adult literacy assessment by allowing the client to interact with an intelligent computer system which simulates real-life literacy activities and materials and which measures literacy performance in the actual context of its use. The specific objectives of the project are as follows: (1) to develop a simulation-based diagnostic tool to assess adults' prior knowledge about reading and writing processes in actual contexts of application; (2) to provide a profile of readers' strengths and weaknesses; and (3) to suggest instructional strategies and materials which can be used as a beginning point for remediation. In the first and development phase of the project, descriptions of literacy events and environments are being written and functional literacy documents analyzed for their components. From these descriptions, scripts are being generated which define the interaction between the student, an on-screen guide and the simulated literacy environment.

Topics in programmable automation. [for materials handling, inspection, and assembly

NASA Technical Reports Server (NTRS)

Rosen, C. A.

1975-01-01

Topics explored in the development of integrated programmable automation systems include: numerically controlled and computer controlled machining; machine intelligence and the emulation of human-like capabilities; large scale semiconductor integration technology applications; and sensor technology for asynchronous local computation without burdening the executive minicomputer which controls the whole system. The role and development of training aids, and the potential application of these aids to augmented teleoperator systems are discussed.

STEPS: A Simulated, Tutorable Physics Student.

ERIC Educational Resources Information Center

Ur, Sigalit; VanLehn, Kurt

1995-01-01

Describes a simulated student that learns by interacting with a human tutor. Tests suggest that simulated students, when developed past the prototype stage, could be valuable for training human tutors. Provides a computational cognitive task analysis of the skill of learning from a tutor that is useful for designing intelligent tutoring systems.…

Pathfinder, Volume 7, Number 3, May/June 2009. A Historic Role

DTIC Science & Technology

2009-06-01

Intelligence System (DMIGS) into service. These self- contained vehicles represent “NGA on wheels” and can travel to any and all National Special Security...never had any formal military training, but with Hogarth’s interces - sion, he received a commission as a second lieutenant interpreter in the British

Design and Implementation of a Relational Database Management System for the AFIT Thesis Process.

DTIC Science & Technology

1985-09-01

AIRLIFT Gourdin 4. APPLIED MATHEMATICS Daneman Lee Na rga rsen ker 5. ARTIFICIAL INTELLEGENCE Gen et 6. CAPARILITY ASSESSMENT S Budde Talbott 31...05 ARTIFICIAL INTELLIGENCE 06 CAPABILITY ASSESSMENT 07 COMMUNIICATIONS 08 COMPUTER AIDED DESIGN 09 COMPUTER BASED TRAINING 10 COMPUTER SOFTWARE 11

Poisson-Based Inference for Perturbation Models in Adaptive Spelling Training

ERIC Educational Resources Information Center

Baschera, Gian-Marco; Gross, Markus

2010-01-01

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

Teaching Social Skills: An Effective Online Program

ERIC Educational Resources Information Center

Sanchez, Rebecca P.; Brown, Emily; DeRosier, Melissa E.

2015-01-01

Educators, policymakers, and the general public agree that social skills should be taught to children. In an effort to bridge this gap between evidence-based social skills training and populations in need, the authors have developed an Intelligent Social Tutoring System (ISTS) that fosters learning through adaptive interaction between the student…

Designing Adaptive Instruction for Teams: A Meta-Analysis

ERIC Educational Resources Information Center

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

2018-01-01

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

Training Employees of a Public Iranian Bank on Emotional Intelligence Competencies

ERIC Educational Resources Information Center

Dadehbeigi, Mina; Shirmohammadi, Melika

2010-01-01

Purpose: The purpose of this paper is to examine the possibility of developing emotional intelligence (EI) as conceptualized in Boyatzis et al.'s competency model. Design/methodology/approach: Designing a context-based EI training program, the study utilized a sample of 68 fully-employed members of five branches of a public bank in Iran; each…

Effectiveness of Emotional Intelligence Group Training on Anger in Adolescents with Substance-Abusing Fathers

ERIC Educational Resources Information Center

Hojjat, Seyed Kaveh; Rezaei, Mahdi; Namadian, Gholamreza; Hatami, Seyed Esmaeil; Norozi Khalili, Mina

2017-01-01

Parental substance abuse is associated with impaired skills and ability to take care of children. Children of substance-abusing parents display higher levels of emotional difficulties. This article shows the effectiveness of emotional intelligence group training on anger in adolescents with substance-abusing fathers. The sample consisted of 60…

Weaving Emotional Intelligence into a Home Visiting Model

ERIC Educational Resources Information Center

Enson, Beth; Imberger, Jaci

2017-01-01

This article details the impact of Emotional Intelligence (EI) training on the 10-year evolution of the Taos First Steps Home Visiting program. While EI has become standard fare in corporate training and practice, it is less well known in the world of early childhood services. This article highlights interviews with key personnel, both in-house…

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.

An intelligent system with EMG-based joint angle estimation for telemanipulation.

PubMed

Suryanarayanan, S; Reddy, N P; Gupta, V

1996-01-01

Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle and the actual angle to be less than 3% during training and less than 15% during testing. The technique of direct bio-control using EMG has the potential as an interface for telemanipulation applications.

Impact of the picture exchange communication system: effects on communication and collateral effects on maladaptive behaviors.

PubMed

Ganz, Jennifer B; Parker, Richard; Benson, Joanne

2009-12-01

Many children with autism require intensive instruction in the use of augmentative or alternative communication systems, such as the Picture Exchange Communication System (PECS). This study investigated the use of PECS with three young boys with autism to determine the impact of PECS training on use of pictures for requesting, use of intelligible words, and maladaptive behaviors. A multiple baseline-probe design with a staggered start was implemented. Results indicated that all of the participants quickly learned to make requests using pictures and that two used intelligible speech following PECS instruction; maladaptive behaviors were variable throughout baseline and intervention phases. Although all of the participants improved in at least one dependent variable, there remain questions regarding who is best suited for PECS and similar interventions.

Variety Wins: Soccer-Playing Robots and Infant Walking.

PubMed

Ossmy, Ori; Hoch, Justine E; MacAlpine, Patrick; Hasan, Shohan; Stone, Peter; Adolph, Karen E

2018-01-01

Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontaneous infant walking a "feature" or a "bug?" In other words, is variability beneficial for functional walking performance? To address this question, we trained soccer-playing robots on walking paths generated by infants during free play and tested them in simulated games of "RoboCup." In Tournament 1, we compared the functional performance of a simulated robot soccer team trained on infants' natural paths with teams trained on less varied, geometric paths-straight lines, circles, and squares. Across 1,000 head-to-head simulated soccer matches, the infant-trained team consistently beat all teams trained with less varied walking paths. In Tournament 2, we compared teams trained on different clusters of infant walking paths. The team trained with the most varied combination of path shape, step direction, number of steps, and number of starts and stops outperformed teams trained with less varied paths. This evidence indicates that variety is a crucial feature supporting functional walking performance. More generally, we propose that robotics provides a fruitful avenue for testing hypotheses about infant development; reciprocally, observations of infant behavior may inform research on artificial intelligence.

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

PubMed

Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

2006-04-01

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

The U.S. Intelligence Community: Dilemmas of Management and Law.

DTIC Science & Technology

1980-06-01

power, it must share the limelight with money: who gets a piece of the half-trillion dollar federal budget, and how they spend it, is a primary activity...tasking of sys- tems whose primary mission is support to operating forces; train personnel for intelligence duties; provide an intelligence reserve; or are...mission, organization, and 4 fuctions of the Intelligence Community. And considering that the ultimate function of the Intelligence Community, as a service

System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

NASA Astrophysics Data System (ADS)

Nieten, Joseph L.; Burke, Roger

1993-03-01

The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

"Chickens Are a Lot Smarter than I Originally Thought": Changes in Student Attitudes to Chickens Following a Chicken Training Class.

PubMed

Hazel, Susan J; O'Dwyer, Lisel; Ryan, Terry

2015-08-21

A practical class using clicker training of chickens to apply knowledge of how animals learn and practice skills in animal training was added to an undergraduate course. Since attitudes to animals are related to their perceived intelligence, surveys of student attitudes were completed pre- and post- the practical class, to determine if (1) the practical class changed students' attitudes to chickens and their ability to experience affective states, and (2) any changes were related to previous contact with chickens, training experience or gender. In the post- versus pre-surveys, students agreed more that chickens are easy to teach tricks to, are intelligent, and have individual personalities and disagreed more that they are difficult to train and are slow learners. Following the class, they were more likely to believe chickens experience boredom, frustration and happiness. Females rated the intelligence and ability to experience affective states in chickens more highly than males, although there were shifts in attitude in both genders. This study demonstrated shifts in attitudes following a practical class teaching clicker training in chickens. Similar practical classes may provide an effective method of teaching animal training skills and promoting more positive attitudes to animals.

Emotional intelligence skills for maintaining social networks in healthcare organizations.

PubMed

Freshman, Brenda; Rubino, Louis

2004-01-01

For healthcare organizations to survive in these increasingly challenging times, leadership and management must face mounting interpersonal concerns. The authors present the boundaries of internal and external social networks with respect to leadership and managerial functions: Social networks within the organization are stretched by reductions in available resources and structural ambiguity, whereas external social networks are stressed by interorganizational competitive pressures. The authors present the development of emotional intelligence skills in employees as a strategic training objective that can strengthen the internal and external social networks of healthcare organizations. The authors delineate the unique functions of leadership and management with respect to the application of emotional intelligence skills and discuss training and future research implications for emotional intelligence skill sets and social networks.

The Effects of Working Memory on Brain-Computer Interface Performance

PubMed Central

Sprague, Samantha A.; McBee, Matthew; Sellers, Eric W.

2015-01-01

Objective The purpose of the present study is to evaluate the relationship between working memory and BCI performance. Methods Participants took part in two separate sessions. The first session consisted of three computerized tasks. The LSWM was used to measure working memory, the TPVT was used to measure general intelligence, and the DCCS was used to measure executive function, specifically cognitive flexibility. The second session consisted of a P300-based BCI copy-spelling task. Results The results indicate that both working memory and general intelligence are significant predictors of BCI performance. Conclusions This suggests that working memory training could be used to improve performance on a BCI task. Significance Working memory training may help to reduce a portion of the individual differences that exist in BCI performance allowing for a wider range of users to successfully operate the BCI system as well as increase the BCI performance of current users. PMID:26620822

Towards an intelligent wheelchair system for users with cerebral palsy.

PubMed

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

2010-04-01

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

Altering the Mission Statement: The Training of Firefighters as Intelligence Gatherers

DTIC Science & Technology

2008-09-01

estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services ...distribution is unlimited 12b. DISTRIBUTION CODE A 13. ABSTRACT (maximum 200 words) The fire service is one of the...safety of our communities. 15. NUMBER OF PAGES 71 14. SUBJECT TERMS Fire Service , first responders, intelligence, firefighter training, awareness

The Effect of Self-Care Education on Emotional Intelligence of Iranian Nursing Students: A Quasi-experimental Study.

PubMed

Goudarzian, Amir Hossein; Nesami, Masoumeh Bagheri; Sedghi, Parisa; Gholami, Mahsan; Faraji, Maryam; Hatkehlouei, Mahdi Babaei

2018-01-20

This study aimed to determine the effect of self-care training on emotional intelligence of nursing students. This quasi-experimental study was conducted on nursing students of Mazandaran University of Medical Sciences in 2016. The subjects (60 students) that were collected with random sampling method were divided into experimental and control groups, and then, self-care behaviors were taught to the experimental group' students in 12 sessions by using a checklist. The subjects of control group were not taught. Emotional intelligence was measured by using Bradberry and Greaves' standard questionnaire before and after the intervention. Emotional intelligence scores of students in the experimental group showed positive and significant change between before (75.33 ± 7.23) and after (125.70 ± 7.79) of training (P < 0.001). Also t test shows a significant change in control (78.73 ± 6.54) and experimental groups (125.70 ± 7.79), after of training (P < 0.001). It is recommended that special programs be organized in order to improve the emotional intelligence of students that improve the likelihood of their success in life.

Next generation emotional intelligence (Abstract)

Treesearch

Jim Saveland

2012-01-01

Emotional intelligence has been a hot topic in leadership training since Dan Goleman published his book on the subject in 1995. Emotional intelligence competencies are typically focused on recognition and regulation of emotions in one's self and social situations, yielding four categories: self-awareness, self-management, social awareness and relationship...

Next generation Emotional Intelligence

Treesearch

J. Saveland

2012-01-01

Emotional Intelligence has been a hot topic in leadership training since Dan Goleman published his book on the subject in 1995. Emotional intelligence competencies are typically focused on recognition and regulation of emotions in one's self and social situations, yielding four categories: self-awareness, self-management, social awareness and relationship...

Living and working in space; IAA Man in Space Symposium, 9th, Cologne, Federal Republic of Germany, June 17-21, 1991, Selection of Papers

NASA Technical Reports Server (NTRS)

Klein, Karl E. (Editor); Contant, Jean-Michel (Editor)

1992-01-01

The present symposium on living and working in space encompasses the physiological responses of humans in space and biomedical support for the conditions associated with space travel. Specific physiological issues addressed include cerebral and sensorimotor functions, effects on the cardiovascular and respiratory system, musculoskeletal system, body fluid, hormones and electrolytes, and some orthostatic hypotension mechanisms as countermeasures. The biomedical support techniques examined include selection training, and care, teleoperation and artificial intelligence, robotic automation, bioregenerative life support, and toxic hazard risks in space habitats. Also addressed are determinants of orientation in microgravity, the hormonal control of body fluid metabolism, integrated human-machine intelligence in space machines, and material flow estimation in CELSS.

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.

LAHYSTOTRAIN development and evaluation of a complex training system for hysteroscopy.

PubMed

Müller-Wittig, W K; Bisler, A; Bockholt, U; Los Arcos, J L; Oppelt, P; Stähler, J; Voss, G

2001-01-01

Hysteroscopy has already become an irreplaceable method in gynaecoloic diagnosis and therapy. In the diagnostic case the hysteroscope with a 30 degrees optic is insert transvaginally, in the therapeutic case the resectoscope with a 12 degrees optic is used. The endoscopic intervention requires special surgical skills for endoscope handling and remote instrument control. To acquire these skills currently hands-on training in clinical praxis has become standard, which is linked with higher danger for the women. To overcome current drawbacks of traditional training methods the European project LAHYSTOTRAIN was set up, that tries to combine Virtual Reality (VR), Multimedia (MM) technology, and Intelligent Tutoring Systems (ITS) to develop an alternative training system for hysteroscopic interventions. The first prototype of the LAHYSTOTRAIN demonstrator has been shown on several European conferences. An evaluation of the system was performed, with the idea, to collect feedback and impressions, that should be considered in further developments. This paper presents the LAHYSTOTRAIN prototype and the results of these evaluations.

Artificial intelligence: Neural network model as the multidisciplinary team member in clinical decision support to avoid medical mistakes.

PubMed

Buzaev, Igor Vyacheslavovich; Plechev, Vladimir Vyacheslavovich; Nikolaeva, Irina Evgenievna; Galimova, Rezida Maratovna

2016-09-01

The continuous uninterrupted feedback system is the essential part of any well-organized system. We propose aLYNX concept that is a possibility to use an artificial intelligence algorithm or a neural network model in decision-making system so as to avoid possible mistakes and to remind the doctors to review tactics once more in selected cases. aLYNX system includes: registry with significant factors, decisions and results; machine learning process based on this registry data; the use of the machine learning results as the adviser. We show a possibility to build a computer adviser with a neural network model for making a choice between coronary aortic bypass surgery (CABG) and percutaneous coronary intervention (PCI) in order to achieve a higher 5-year survival rate in patients with angina based on the experience of 5107 patients. The neural network was trained by 4679 patients who achieved 5-year survival. Among them, 2390 patients underwent PCI and 2289 CABG. After training, the correlation coefficient ( r ) of the network was 0.74 for training, 0.67 for validation, 0.71 for test and 0.73 for total. Simulation of the neural network function has been performed after training in the two groups of patients with known 5-year outcome. The disagreement rate was significantly higher in the dead patient group than that in the survivor group between neural network model and heart team [16.8% (787/4679) vs. 20.3% (87/428), P  = 0.065)]. The study shows the possibility to build a computer adviser with a neural network model for making a choice between CABG and PCI in order to achieve a higher 5-year survival rate in patients with angina.

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.

Neurotechnology for intelligence analysts

NASA Astrophysics Data System (ADS)

Kruse, Amy A.; Boyd, Karen C.; Schulman, Joshua J.

2006-05-01

Geospatial Intelligence Analysts are currently faced with an enormous volume of imagery, only a fraction of which can be processed or reviewed in a timely operational manner. Computer-based target detection efforts have failed to yield the speed, flexibility and accuracy of the human visual system. Rather than focus solely on artificial systems, we hypothesize that the human visual system is still the best target detection apparatus currently in use, and with the addition of neuroscience-based measurement capabilities it can surpass the throughput of the unaided human severalfold. Using electroencephalography (EEG), Thorpe et al1 described a fast signal in the brain associated with the early detection of targets in static imagery using a Rapid Serial Visual Presentation (RSVP) paradigm. This finding suggests that it may be possible to extract target detection signals from complex imagery in real time utilizing non-invasive neurophysiological assessment tools. To transform this phenomenon into a capability for defense applications, the Defense Advanced Research Projects Agency (DARPA) currently is sponsoring an effort titled Neurotechnology for Intelligence Analysts (NIA). The vision of the NIA program is to revolutionize the way that analysts handle intelligence imagery, increasing both the throughput of imagery to the analyst and overall accuracy of the assessments. Successful development of a neurobiologically-based image triage system will enable image analysts to train more effectively and process imagery with greater speed and precision.

Train Your Brain.

ERIC Educational Resources Information Center

Salopek, Jennifer J.

1998-01-01

In an interview, Daniel Goleman, author of "Working with Emotional Intelligence," explains how emotional intelligence outweighs cognitive ability and technical skills as a contributor to success in the workplace. (Author/JOW)

Air Education and Training Command: Education and Training Technology Application (ETTAP) Program

DTIC Science & Technology

2007-05-15

benefit  vs  cost)  •  Measurable  •  Completed within approximately 18 months  •  Of potential use across AETC  •  Cost ≈ $200K ­ $700K  •  Current...Airbase Sim  MAXWELL  Intelligence Tutoring  KEESLER  Ultimate Virtual  Classroom   TYNDALL  Airborne Warning & Control System  Stand­alone Training...LACKLAND  Tablet  PCs w/Dog Training  LUKE  Barry Goldwater Range  Live Virtual Data Link  LAUGHLIN  Virtual Interactive Pattern  Environment & Radio

Thinking and Writing: Cognitive Science and Intelligence Analysis

DTIC Science & Technology

2010-02-01

well as books and monographs addressing historical, operational, doctrinal, and theoretical aspects of the intelligence profession. It also...Intelligence published an updated version of Heuer’s articles in a book , Psychology of Intelligence Analysis, in 1999. Since reprinted by CIA and available...commercially, the book is now a staple in many analytic training courses. conclusion. This and other examples, he says, il- lustrate how the things

An Experiential Approach to Cultural Intelligence Education

ERIC Educational Resources Information Center

MacNab, Brent R.

2012-01-01

Cultural intelligence (CQ) represents a promising advancement in the area of cross-cultural training and management. Experiential approaches for CQ development have been proposed as highly effective; however, there is a lack of CQ-specific approaches in the management literature. This work overviews the concept of cultural intelligence and its…

IQ Test Controversy: Past, Present, and Future Trends.

ERIC Educational Resources Information Center

Alford, David W.

The controversies surrounding the use of intelligence quotient (IQ) tests with children are summarized. This article discusses what intelligence is and how intelligence is measured. It also examines factors which can affect measurement, including examiner training or bias, examinee age, misinterpretation of test scores, and poor tests. The…

A Leadership Preparatory Program and Emotional Intelligence

ERIC Educational Resources Information Center

Tison, Jackie

2011-01-01

Within the construct of No Child Left Behind, training future educational leaders has become more important to universities and school systems alike. Educational leadership programs have begun to analyze ways to adequately prepare future leaders to be effective in all aspects of leading including the emotional areas. The purpose of this study was…

Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning

ERIC Educational Resources Information Center

Forsyth, Carol; Pavlik, Philip, Jr.; Graesser, Arthur C.; Cai, Zhiqiang; Germany, Mae-lynn; Millis, Keith; Dolan, Robert P.; Butler, Heather; Halpern, Diane

2012-01-01

"OperationARIES!" is an Intelligent Tutoring System that teaches scientific inquiry skills in a game-like atmosphere. Students complete three different training modules, each with natural language conversations, in order to acquire deep-level knowledge of 21 core concepts of research methodology (e.g., correlation does not mean…

A System for Adaptive High-Variability Segmental Perceptual Training: Implementation, Effectiveness, Transfer

ERIC Educational Resources Information Center

Qian, Manman; Chukharev-Hudilainen, Evgeny; Levis, John

2018-01-01

Many types of L2 phonological perception are often difficult to acquire without instruction. These difficulties with perception may also be related to intelligibility in production. Instruction on perception contrasts is more likely to be successful with the use of phonetically variable input made available through computer-assisted pronunciation…

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm.

PubMed

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-24

Indoor occupants' positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans' position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization.

Passive Infrared (PIR)-Based Indoor Position Tracking for Smart Homes Using Accessibility Maps and A-Star Algorithm

PubMed Central

Yang, Dan; Xu, Bin; Rao, Kaiyou; Sheng, Weihua

2018-01-01

Indoor occupants’ positions are significant for smart home service systems, which usually consist of robot service(s), appliance control and other intelligent applications. In this paper, an innovative localization method is proposed for tracking humans’ position in indoor environments based on passive infrared (PIR) sensors using an accessibility map and an A-star algorithm, aiming at providing intelligent services. First the accessibility map reflecting the visiting habits of the occupants is established through the integral training with indoor environments and other prior knowledge. Then the PIR sensors, which placement depends on the training results in the accessibility map, get the rough location information. For more precise positioning, the A-start algorithm is used to refine the localization, fused with the accessibility map and the PIR sensor data. Experiments were conducted in a mock apartment testbed. The ground truth data was obtained from an Opti-track system. The results demonstrate that the proposed method is able to track persons in a smart home environment and provide a solution for home robot localization. PMID:29364188

Emotional intelligence as a crucial component to medical education.

PubMed

Johnson, Debbi R

2015-12-06

The primary focus of this review was to discover what is already known about Emotional Intelligence (EI) and the role it plays within social relationships, as well as its importance in the fields of health care and health care education. This article analyzes the importance of EI in the field of health care and recommends various ways that this important skill can be built into medical programs. Information was gathered using various database searches including EBSCOHOST, Academic Search Premier and ERIC. The search was conducted in English language journals from the last ten years. Descriptors include: Emotional Intelligence, medical students and communication skills, graduate medical education, Emotional Intelligence and graduate medical education, Emotional Intelligence training programs, program evaluation and development. Results of the study show a direct correlation between medical education and emotional intelligence competencies, which makes the field of medical education an ideal one in which to integrate further EI training. The definition of EI as an ability-based skill allows for training in specific competencies that can be directly applied to a specialized field. When EI is conceptualized as an ability that can be taught, learned, and changed, it may be used to address the specific aspects of the clinician-patient relationship that are not working well. For this reason, teaching EI should be a priority in the field of medical education in order to better facilitate this relationship in the future.

Simulation-Based Cryosurgery Intelligent Tutoring System Prototype.

PubMed

Sehrawat, Anjali; Keelan, Robert; Shimada, Kenji; Wilfong, Dona M; McCormick, James T; Rabin, Yoed

2016-04-01

As a part of an ongoing effort to develop computerized training tools for cryosurgery, the current study presents a proof of concept for a computerized tool for cryosurgery tutoring. The tutoring system lists geometrical constraints of cryoprobes placement, simulates cryoprobe insertion, displays a rendered shape of the prostate, enables distance measurements, simulates the corresponding thermal history, and evaluates the mismatch between the target region shape and a preselected planning isotherm. The quality of trainee planning is measured in comparison with a computer-generated planning, created for each case study by previously developed planning algorithms. The following two versions of the tutoring system have been tested in the current study: (1) an unguided version, where the trainee can practice cases in unstructured sessions and (2) an intelligent tutoring system, which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. Although the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal histories, it creates a unique opportunity to gain insight into the process outside the operation room. Post-test results indicate that the intelligent tutoring system may be more beneficial than the nonintelligent tutoring system, but the proof of concept is demonstrated with either system. © The Author(s) 2015.

Advanced Networks in Dental Rich Online MEDiA (ANDROMEDA)

NASA Astrophysics Data System (ADS)

Elson, Bruce; Reynolds, Patricia; Amini, Ardavan; Burke, Ezra; Chapman, Craig

There is growing demand for dental education and training not only in terms of knowledge but also skills. This demand is driven by continuing professional development requirements in the more developed economies, personnel shortages and skills differences across the European Union (EU) accession states and more generally in the developing world. There is an excellent opportunity for the EU to meet this demand by developing an innovative online flexible learning platform (FLP). Current clinical online systems are restricted to the delivery of general, knowledge-based training with no easy method of personalization or delivery of skill-based training. The PHANTOM project, headed by Kings College London is developing haptic-based virtual reality training systems for clinical dental training. ANDROMEDA seeks to build on this and establish a Flexible Learning Platform that can integrate the haptic and sensor based training with rich media knowledge transfer, whilst using sophisticated technologies such as including service-orientated architecture (SOA), Semantic Web technologies, knowledge-based engineering, business intelligence (BI) and virtual worlds for personalization.

Individual Differences in Military Training Environments: Four Areas of Research

DTIC Science & Technology

1987-01-30

training setting. Such factors as ability, skills, experience, intelligence , interests, personal characteristics (e.g., age) and motivation interact...recruits than were Intelligence scores; fast learners retained more and relearned more quickly than slow learners. This suggests that if the goal is to...and Development Center. Gottfredson , G.D., Holland, J.L. and Ogawa, D.K. (1982). Dictionary of Holland occupational codes. Palo Alto, CA: Consulting

Student Science Training Program in Mathematics, Physics and Computer Science. Final Report to the National Science Foundation. Artificial Intelligence Memo No. 393.

ERIC Educational Resources Information Center

Abelson, Harold; diSessa, Andy

During the summer of 1976, the MIT Artificial Intelligence Laboratory sponsored a Student Science Training Program in Mathematics, Physics, and Computer Science for high ability secondary school students. This report describes, in some detail, the style of the program, the curriculum and the projects the students under-took. It is hoped that this…

A Preliminary Investigation into Cognitive Aptitudes Predictive of Overall MQ-1 Predator Pilot Qualification Training Performance

DTIC Science & Technology

2015-11-06

Predator pilot vacancies. The purpose of this study was to evaluate computer-based intelligence and neuropsychological testing on training...high-risk, high-demand occupation. 15. SUBJECT TERMS Remotely piloted aircraft, RPA, neuropsychological screening, intelligence testing , computer...based testing , Predator, MQ-1 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18. NUMBER OF PAGES 20 19a. NAME OF

Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

PubMed

Tajmir, Shahein H; Alkasab, Tarik K

2018-06-01

Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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.

Intelligent tutoring in the spacecraft command/control environment

NASA Technical Reports Server (NTRS)

Truszkowski, Walter F.

1988-01-01

The spacecraft command/control environment is becoming increasingly complex. As we enter the era of Space Station and the era of more highly automated systems, it is evident that the critical roles played by operations personnel in supervising the many required control center system components is becoming more cognitively demanding. In addition, the changing and emerging roles in the operations picture have far-reaching effects on the achievement of mission objectives. Thus highly trained and competent operations personnel are mandatory for success. Keeping pace with these developments has been computer-aided instruction utilizing various artificial intelligence technologies. The impacts of this growing capability on the stringent requirements for efficient and effective control center operations personnel is an area of much concentrated study. Some of the research and development of automated tutoring systems for the spacecraft command/control environment is addressed.

Conversion of paper-based technical manuals to interactive electronic technical manuals

NASA Astrophysics Data System (ADS)

Kuo, Mu-Hsing

1999-12-01

An IETM is intended to be the functional equivalent of a paper-based Technical Manual (TM), and in most cases a total replacement for paper manual. In this paper, we will describe some of document image understanding technologies applied to the conversion of paper-based TMs to IETMs. Using these advanced technologies allow us to convert paper-based TMs to class 1/2 IETMs. However, these were not sufficient for an automated integrated logistics support system in the ROC Department of Defense. An advanced IETM system is therefore required. Such class 4/5 like IETM system could provide intelligent display of information and other user applications such as diagnostics, intelligent design and manufacturing, or computer-managed training. The author has developed some of the advanced functions, and examples will be shown to demonstrate the new aspect of IETMs.

Leadership training to improve nurse retention.

PubMed

Wallis, Allan; Kennedy, Kathy I

2013-05-01

This paper discusses findings from an evaluation of a training programme designed to promote collaborative, team-based approaches to improve nurse retention within health care organizations. A year-long leadership training programme was designed and implemented to develop effective teams that could address retention challenges in a diverse set of organizations in Colorado ranging from public, private to non-profit. An evaluation, based on a combination of participant observation, group interviews, and the use of standardized tests measuring individual emotional intelligence and team dynamics was conducted to assess the effectiveness of the training programme. What role do the emotional intelligence of individual members and organizational culture play in team effectiveness? Out of five teams participating in the training programme, two performed exceptionally well, one experienced moderate success and two encountered significant problems. Team dynamics were significantly affected by the emotional intelligence of key members holding supervisory positions and by the existing culture and structure of the participating organizations. Team approaches to retention hold promise but require careful development and are most likely to work where organizations have a collaborative problem-solving environment. © 2012 Blackwell Publishing Ltd.

The role of individual differences in cognitive training and transfer.

PubMed

Jaeggi, Susanne M; Buschkuehl, Martin; Shah, Priti; Jonides, John

2014-04-01

Working memory (WM) training has recently become a topic of intense interest and controversy. Although several recent studies have reported near- and far-transfer effects as a result of training WM-related skills, others have failed to show far transfer, suggesting that generalization effects are elusive. Also, many of the earlier intervention attempts have been criticized on methodological grounds. The present study resolves some of the methodological limitations of previous studies and also considers individual differences as potential explanations for the differing transfer effects across studies. We recruited intrinsically motivated participants and assessed their need for cognition (NFC; Cacioppo & Petty Journal of Personality and Social Psychology 42:116-131, 1982) and their implicit theories of intelligence (Dweck, 1999) prior to training. We assessed the efficacy of two WM interventions by comparing participants' improvements on a battery of fluid intelligence tests against those of an active control group. We observed that transfer to a composite measure of fluid reasoning resulted from both WM interventions. In addition, we uncovered factors that contributed to training success, including motivation, need for cognition, preexisting ability, and implicit theories about intelligence.

A machine learning system to improve heart failure patient assistance.

PubMed

Guidi, Gabriele; Pettenati, Maria Chiara; Melillo, Paolo; Iadanza, Ernesto

2014-11-01

In this paper, we present a clinical decision support system (CDSS) for the analysis of heart failure (HF) patients, providing various outputs such as an HF severity evaluation, HF-type prediction, as well as a management interface that compares the different patients' follow-ups. The whole system is composed of a part of intelligent core and of an HF special-purpose management tool also providing the function to act as interface for the artificial intelligence training and use. To implement the smart intelligent functions, we adopted a machine learning approach. In this paper, we compare the performance of a neural network (NN), a support vector machine, a system with fuzzy rules genetically produced, and a classification and regression tree and its direct evolution, which is the random forest, in analyzing our database. Best performances in both HF severity evaluation and HF-type prediction functions are obtained by using the random forest algorithm. The management tool allows the cardiologist to populate a "supervised database" suitable for machine learning during his or her regular outpatient consultations. The idea comes from the fact that in literature there are a few databases of this type, and they are not scalable to our case.

Adding intelligent services to an object oriented system

NASA Technical Reports Server (NTRS)

Robideaux, Bret R.; Metzler, Theodore A.

1994-01-01

As today's software becomes increasingly complex, the need grows for intelligence of one sort or another to becomes part of the application, often an intelligence that does not readily fit the paradigm of one's software development. There are many methods of developing software, but at this time, the most promising is the object oriented (OO) method. This method involves an analysis to abstract the problem into separate 'objects' that are unique in the data that describe them and the behavior that they exhibit, and eventually to convert this analysis into computer code using a programming language that was designed (or retrofitted) for OO implementation. This paper discusses the creation of three different applications that are analyzed, designed, and programmed using the Shlaer/Mellor method of OO development and C++ as the programming language. All three, however, require the use of an expert system to provide an intelligence that C++ (or any other 'traditional' language) is not directly suited to supply. The flexibility of CLIPS permitted us to make modifications to it that allow seamless integration with any of our applications that require an expert system. We illustrate this integration with the following applications: (1) an after action review (AAR) station that assists a reviewer in watching a simulated tank battle and developing an AAR to critique the performance of the participants in the battle; (2) an embedded training system and over-the-shoulder coach for howitzer crewmen; and (3) a system to identify various chemical compounds from their infrared absorption spectra.

Proceedings of the Workshop on software tools for distributed intelligent control systems

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

Herget, C.J.

1990-09-01

The Workshop on Software Tools for Distributed Intelligent Control Systems was organized by Lawrence Livermore National Laboratory for the United States Army Headquarters Training and Doctrine Command and the Defense Advanced Research Projects Agency. The goals of the workshop were to the identify the current state of the art in tools which support control systems engineering design and implementation, identify research issues associated with writing software tools which would provide a design environment to assist engineers in multidisciplinary control design and implementation, formulate a potential investment strategy to resolve the research issues and develop public domain code which can formmore » the core of more powerful engineering design tools, and recommend test cases to focus the software development process and test associated performance metrics. Recognizing that the development of software tools for distributed intelligent control systems will require a multidisciplinary effort, experts in systems engineering, control systems engineering, and compute science were invited to participate in the workshop. In particular, experts who could address the following topics were selected: operating systems, engineering data representation and manipulation, emerging standards for manufacturing data, mathematical foundations, coupling of symbolic and numerical computation, user interface, system identification, system representation at different levels of abstraction, system specification, system design, verification and validation, automatic code generation, and integration of modular, reusable code.« less

Tactical Action Officer Intelligent Tutoring System (TAO ITS)

DTIC Science & Technology

2006-01-01

scenario. As well as the intrinsic feedback that free - play simulations naturally provide a student, the TAO ITS provides detailed, useful extrinsic feedback...incorporate use of free - play simulators into their curriculum, affordably. This is a major shortcoming of conventional CBT as student manipulation of...tutoring systems are ideal for incorporating desktop free - play simulators into computer-based training since the software can stand in for a human

Similar prefrontal cortical activities between general fluid intelligence and visuospatial working memory tasks in preschool children as revealed by optical topography.

PubMed

Kuwajima, Mariko; Sawaguchi, Toshiyuki

2010-10-01

General fluid intelligence (gF) is a major component of intellect in both adults and children. Whereas its neural substrates have been studied relatively thoroughly in adults, those are poorly understood in children, particularly preschoolers. Here, we hypothesized that gF and visuospatial working memory share a common neural system within the lateral prefrontal cortex (LPFC) during the preschool years (4-6 years). At the behavioral level, we found that gF positively and significantly correlated with abilities (especially accuracy) in visuospatial working memory. Optical topography revealed that the LPFC of preschoolers was activated and deactivated during the visuospatial working memory task and the gF task. We found that the spatio-temporal features of neural activity in the LPFC were similar for both the visuospatial working memory task and the gF task. Further, 2 months of training for the visuospatial working memory task significantly increased gF in the preschoolers. These findings suggest that a common neural system in the LPFC is recruited to improve the visuospatial working memory and gF in preschoolers. Efficient recruitment of this neural system may be important for good performance in these functions in preschoolers, and behavioral training using this system would help to increase gF at these ages.

Naval Computer-Based Instruction: Cost, Implementation and Effectiveness Issues.

DTIC Science & Technology

1988-03-01

logical follow on to MITIPAC and are an attempt to use some artificial intelligence (AI) techniques with computer-based training. A good intelligent ...principles of steam plant operation and maintenance. Steamer was written in LISP on a LISP machine in an attempt to use artificial intelligence . "What... Artificial Intelligence and Speech Technology", Electronic Learning, September 1987. Montague, William. E., code 5, Navy Personnel Research and

Variety Wins: Soccer-Playing Robots and Infant Walking

PubMed Central

Ossmy, Ori; Hoch, Justine E.; MacAlpine, Patrick; Hasan, Shohan; Stone, Peter; Adolph, Karen E.

2018-01-01

Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontaneous infant walking a “feature” or a “bug?” In other words, is variability beneficial for functional walking performance? To address this question, we trained soccer-playing robots on walking paths generated by infants during free play and tested them in simulated games of “RoboCup.” In Tournament 1, we compared the functional performance of a simulated robot soccer team trained on infants' natural paths with teams trained on less varied, geometric paths—straight lines, circles, and squares. Across 1,000 head-to-head simulated soccer matches, the infant-trained team consistently beat all teams trained with less varied walking paths. In Tournament 2, we compared teams trained on different clusters of infant walking paths. The team trained with the most varied combination of path shape, step direction, number of steps, and number of starts and stops outperformed teams trained with less varied paths. This evidence indicates that variety is a crucial feature supporting functional walking performance. More generally, we propose that robotics provides a fruitful avenue for testing hypotheses about infant development; reciprocally, observations of infant behavior may inform research on artificial intelligence. PMID:29867427

Playing with the Multiple Intelligences: How Play Helps Them Grow

ERIC Educational Resources Information Center

Eberle, Scott G.

2011-01-01

Howard Gardner first posited a list of "multiple intelligences" as a liberating alternative to the assumptions underlying traditional IQ testing in his widely read study "Frames of Mind" (1983). Play has appeared only in passing in Gardner's thinking about intelligence, however, even though play instructs and trains the verbal, interpersonal,…

Prerequisites for Emotional Intelligence Formation in Second Language Learning and Career Choice

ERIC Educational Resources Information Center

Baklashova, Tatiana A.; Galishnikova, Elena M.; Khafizova, Liliya A.

2016-01-01

The relevance of the topic is due to the enhancing role of emotional intelligence in second language learning. The article aims to substantiate that emotional intelligence (EI) strengthens training quality of future professionals, gives it an emotional color, and thereby increases a variety of intellectual skills. The leading methodical approaches…

Interference and deception detection technology of satellite navigation based on deep learning

NASA Astrophysics Data System (ADS)

Chen, Weiyi; Deng, Pingke; Qu, Yi; Zhang, Xiaoguang; Li, Yaping

2017-10-01

Satellite navigation system plays an important role in people's daily life and war. The strategic position of satellite navigation system is prominent, so it is very important to ensure that the satellite navigation system is not disturbed or destroyed. It is a critical means to detect the jamming signal to avoid the accident in a navigation system. At present, the detection technology of jamming signal in satellite navigation system is not intelligent , mainly relying on artificial decision and experience. For this issue, the paper proposes a method based on deep learning to monitor the interference source in a satellite navigation. By training the interference signal data, and extracting the features of the interference signal, the detection sys tem model is constructed. The simulation results show that, the detection accuracy of our detection system can reach nearly 70%. The method in our paper provides a new idea for the research on intelligent detection of interference and deception signal in a satellite navigation system.

Intelligent Predictor of Energy Expenditure with the Use of Patch-Type Sensor Module

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn-Tae

2012-01-01

This paper is concerned with an intelligent predictor of energy expenditure (EE) using a developed patch-type sensor module for wireless monitoring of heart rate (HR) and movement index (MI). For this purpose, an intelligent predictor is designed by an advanced linguistic model (LM) with interval prediction based on fuzzy granulation that can be realized by context-based fuzzy c-means (CFCM) clustering. The system components consist of a sensor board, the rubber case, and the communication module with built-in analysis algorithm. This sensor is patched onto the user's chest to obtain physiological data in indoor and outdoor environments. The prediction performance was demonstrated by root mean square error (RMSE). The prediction performance was obtained as the number of contexts and clusters increased from 2 to 6, respectively. Thirty participants were recruited from Chosun University to take part in this study. The data sets were recorded during normal walking, brisk walking, slow running, and jogging in an outdoor environment and treadmill running in an indoor environment, respectively. We randomly divided the data set into training (60%) and test data set (40%) in the normalized space during 10 iterations. The training data set is used for model construction, while the test set is used for model validation. The experimental results revealed that the prediction error on treadmill running simulation was improved by about 51% and 12% in comparison to conventional LM for training and checking data set, respectively. PMID:23202166

Sustainable Model for Public Health Emergency Operations Centers for Global Settings.

PubMed

Balajee, S Arunmozhi; Pasi, Omer G; Etoundi, Alain Georges M; Rzeszotarski, Peter; Do, Trang T; Hennessee, Ian; Merali, Sharifa; Alroy, Karen A; Phu, Tran Dac; Mounts, Anthony W

2017-10-01

Capacity to receive, verify, analyze, assess, and investigate public health events is essential for epidemic intelligence. Public health Emergency Operations Centers (PHEOCs) can be epidemic intelligence hubs by 1) having the capacity to receive, analyze, and visualize multiple data streams, including surveillance and 2) maintaining a trained workforce that can analyze and interpret data from real-time emerging events. Such PHEOCs could be physically located within a ministry of health epidemiology, surveillance, or equivalent department rather than exist as a stand-alone space and serve as operational hubs during nonoutbreak times but in emergencies can scale up according to the traditional Incident Command System structure.

A conceptual model for worksite intelligent physical exercise training--IPET--intervention for decreasing life style health risk indicators among employees: a randomized controlled trial.

PubMed

Sjøgaard, Gisela; Justesen, Just Bendix; Murray, Mike; Dalager, Tina; Søgaard, Karen

2014-06-26

Health promotion at the work site in terms of physical activity has proven positive effects but optimization of relevant exercise training protocols and implementation for high adherence are still scanty. The aim of this paper is to present a study protocol with a conceptual model for planning the optimal individually tailored physical exercise training for each worker based on individual health check, existing guidelines and state of the art sports science training recommendations in the broad categories of cardiorespiratory fitness, muscle strength in specific body parts, and functional training including balance training. The hypotheses of this research are that individually tailored worksite-based intelligent physical exercise training, IPET, among workers with inactive job categories will: 1) Improve cardiorespiratory fitness and/or individual health risk indicators, 2) Improve muscle strength and decrease musculoskeletal disorders, 3) Succeed in regular adherence to worksite and leisure physical activity training, and 3) Reduce sickness absence and productivity losses (presenteeism) in office workers. The present RCT study enrolled almost 400 employees with sedentary jobs in the private as well as public sectors. The training interventions last 2 years with measures at baseline as well as one and two years follow-up. If proven effective, the intelligent physical exercise training scheduled as well as the information for its practical implementation can provide meaningful scientifically based information for public health policy. ClinicalTrials.gov, number: NCT01366950.

A conceptual model for worksite intelligent physical exercise training - IPET - intervention for decreasing life style health risk indicators among employees: a randomized controlled trial

PubMed Central

2014-01-01

Background Health promotion at the work site in terms of physical activity has proven positive effects but optimization of relevant exercise training protocols and implementation for high adherence are still scanty. Methods/Design The aim of this paper is to present a study protocol with a conceptual model for planning the optimal individually tailored physical exercise training for each worker based on individual health check, existing guidelines and state of the art sports science training recommendations in the broad categories of cardiorespiratory fitness, muscle strength in specific body parts, and functional training including balance training. The hypotheses of this research are that individually tailored worksite-based intelligent physical exercise training, IPET, among workers with inactive job categories will: 1) Improve cardiorespiratory fitness and/or individual health risk indicators, 2) Improve muscle strength and decrease musculoskeletal disorders, 3) Succeed in regular adherence to worksite and leisure physical activity training, and 3) Reduce sickness absence and productivity losses (presenteeism) in office workers. The present RCT study enrolled almost 400 employees with sedentary jobs in the private as well as public sectors. The training interventions last 2 years with measures at baseline as well as one and two years follow-up. Discussion If proven effective, the intelligent physical exercise training scheduled as well as the information for its practical implementation can provide meaningful scientifically based information for public health policy. Trial Registration ClinicalTrials.gov, number: NCT01366950. PMID:24964869

Artificial intelligence in sports on the example of weight training.

PubMed

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key pointsArtificial intelligence is a promising field for sport-related analysis.Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements.Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates.

Artificial Intelligence in Sports on the Example of Weight Training

PubMed Central

Novatchkov, Hristo; Baca, Arnold

2013-01-01

The overall goal of the present study was to illustrate the potential of artificial intelligence (AI) techniques in sports on the example of weight training. The research focused in particular on the implementation of pattern recognition methods for the evaluation of performed exercises on training machines. The data acquisition was carried out using way and cable force sensors attached to various weight machines, thereby enabling the measurement of essential displacement and force determinants during training. On the basis of the gathered data, it was consequently possible to deduce other significant characteristics like time periods or movement velocities. These parameters were applied for the development of intelligent methods adapted from conventional machine learning concepts, allowing an automatic assessment of the exercise technique and providing individuals with appropriate feedback. In practice, the implementation of such techniques could be crucial for the investigation of the quality of the execution, the assistance of athletes but also coaches, the training optimization and for prevention purposes. For the current study, the data was based on measurements from 15 rather inexperienced participants, performing 3-5 sets of 10-12 repetitions on a leg press machine. The initially preprocessed data was used for the extraction of significant features, on which supervised modeling methods were applied. Professional trainers were involved in the assessment and classification processes by analyzing the video recorded executions. The so far obtained modeling results showed good performance and prediction outcomes, indicating the feasibility and potency of AI techniques in assessing performances on weight training equipment automatically and providing sportsmen with prompt advice. Key points Artificial intelligence is a promising field for sport-related analysis. Implementations integrating pattern recognition techniques enable the automatic evaluation of data measurements. Artificial neural networks applied for the analysis of weight training data show good performance and high classification rates. PMID:24149722

Do We Really Become Smarter When Our Fluid-Intelligence Test Scores Improve?

PubMed Central

Hayes, Taylor R.; Petrov, Alexander A.; Sederberg, Per B.

2014-01-01

Recent reports of training-induced gains on fluid intelligence tests have fueled an explosion of interest in cognitive training—now a billion-dollar industry. The interpretation of these results is questionable because score gains can be dominated by factors that play marginal roles in the scores themselves, and because intelligence gain is not the only possible explanation for the observed control-adjusted far transfer across tasks. Here we present novel evidence that the test score gains used to measure the efficacy of cognitive training may reflect strategy refinement instead of intelligence gains. A novel scanpath analysis of eye movement data from 35 participants solving Raven’s Advanced Progressive Matrices on two separate sessions indicated that one-third of the variance of score gains could be attributed to test-taking strategy alone, as revealed by characteristic changes in eye-fixation patterns. When the strategic contaminant was partialled out, the residual score gains were no longer significant. These results are compatible with established theories of skill acquisition suggesting that procedural knowledge tacitly acquired during training can later be utilized at posttest. Our novel method and result both underline a reason to be wary of purported intelligence gains, but also provide a way forward for testing for them in the future. PMID:25395695

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding. Interim Report for Period September 1982-July 1983.

ERIC Educational Resources Information Center

Richardson, J. Jeffrey

This paper is part of an Air Force planning effort to develop a research, development, and applications program for the use of artificial intelligence (AI) technology in three target areas: training, performance measurement, and job performance aiding. The paper is organized in five sections that (1) introduce the reader to AI and those subfields…

Relationship between the Short-Term Visual Memory and IQ in the Right-and Left-Handed Subjects Trained in Different Educational Programs: I-General Assessment

ERIC Educational Resources Information Center

Yilmaz, Yavuz; Yetkin, Yalçin

2014-01-01

The relationship between mean intelligence quotient (IQ), hand preferences and visual memory (VM) were investigated on (N = 612) males and females students trained in different educational programs in viewpoint of laterality. IQ was assessed by cattle's culture Fair intelligence test-A (CCFIT-A). The laterality of the one side of the body was…

Irregular Conflict and the Wicked Problem Dilemma: Strategies of Imperfection

DTIC Science & Technology

2011-06-01

behavioral concepts will enhance the pros- pects of achieving “good enough” resolutions. The elements of such an approach are set forth below. Goal...strategic communications.5 The manual assumes competency in, among other areas, the ability to collect useful intelligence, the ability to train host...including the difficulty of useful intelligence collection, the history of multiple ineffective training efforts, and the com- petition for what are

Key Issues in the Analysis of Remote Sensing Data: A report on the workshop

NASA Technical Reports Server (NTRS)

Swain, P. H. (Principal Investigator)

1981-01-01

The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented.

Artificial Intelligence Technology for the Maintainer's Associate. Final Report for the Period October 1983 to December 1985.

ERIC Educational Resources Information Center

Richardson, J. Jeffrey; And Others

In keeping with current Department of Defense policies on integrated diagnostics and a reduced reliance on paper-based documentation, the concept of a portable, expert-system-based job aid and training device was proposed to assist inexperienced electronics maintenance technicians in learning to maintain sophisticated equipment. A prototype was…

Automatic Detection of Student Mental Models Based on Natural Language Student Input during Metacognitive Skill Training

ERIC Educational Resources Information Center

Lintean, Mihai; Rus, Vasile; Azevedo, Roger

2012-01-01

This article describes the problem of detecting the student mental models, i.e. students' knowledge states, during the self-regulatory activity of prior knowledge activation in MetaTutor, an intelligent tutoring system that teaches students self-regulation skills while learning complex science topics. The article presents several approaches to…

Microfluidic Power Generation

DTIC Science & Technology

2008-03-28

It is designed to help patients with retinitus pigmentosa . The eye glasses and photoprocessor worn on the waist are used to train the retinal ...patient [5]. ............................................................. 3 Figure 1.3: The Learning Retinal Implant from Intelligent Medical Systems...implantable biosensors [4]. Examples of such advances include the AbioCor implantable replacement heart (Figure 1.2), Learning Retinal Implant (Figure 1.3

A Web Based Intelligent Training System for SMEs

ERIC Educational Resources Information Center

Mullins, Roisin; Duan, Yanqing; Hamblin, David; Burrell, Phillip; Jin, Huan; Jerzy, Goluchowski; Ewa, Ziemba; Aleksander, Billewicz

2007-01-01

It is widely accepted that employees in small business suffer from a lack of knowledge and skills. This lack of skills means that small companies will miss out on new business opportunities. This is even more evident with respect to the adoption of Internet marketing in Small and Medium Enterprises (SMEs). This paper reports a pilot research…

Creating a Team Tutor Using GIFT

ERIC Educational Resources Information Center

Gilbert, Stephen B.; Slavina, Anna; Dorneich, Michael C.; Sinatra, Anne M.; Bonner, Desmond; Johnston, Joan; Holub, Joseph; MacAllister, Anastacia; Winer, Eliot

2018-01-01

With the movement in education towards collaborative learning, it is becoming more important that learners be able to work together in groups and teams. Intelligent tutoring systems (ITSs) have been used successfully to teach individuals, but so far only a few ITSs have been used for the purpose of training teams. This is due to the difficulty of…

Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

NASA Technical Reports Server (NTRS)

Niewoehner, Kevin R.; Carter, John (Technical Monitor)

2001-01-01

The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

Training Software in Artificial-Intelligence Computing Techniques

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

2005-01-01

The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

Emotional intelligence as a crucial component to medical education

PubMed Central

2015-01-01

Objectives The primary focus of this review was to discover what is already known about Emotional Intelligence (EI) and the role it plays within social relationships, as well as its importance in the fields of health care and health care education. This article analyzes the importance of EI in the field of health care and recommends various ways that this important skill can be built into medical programs. Methods Information was gathered using various database searches including EBSCOHOST, Academic Search Premier and ERIC. The search was conducted in English language journals from the last ten years. Descriptors include: Emotional Intelligence, medical students and communication skills, graduate medical education, Emotional Intelligence and graduate medical education, Emotional Intelligence training programs, program evaluation and development. Results Results of the study show a direct correlation between medical education and emotional intelligence competencies, which makes the field of medical education an ideal one in which to integrate further EI training. Conclusions The definition of EI as an ability-based skill allows for training in specific competencies that can be directly applied to a specialized field. When EI is conceptualized as an ability that can be taught, learned, and changed, it may be used to address the specific aspects of the clinician–patient relationship that are not working well. For this reason, teaching EI should be a priority in the field of medical education in order to better facilitate this relationship in the future. PMID:26638080

Human Activity Behavior and Gesture Generation in Virtual Worlds for Long- Duration Space Missions. Chapter 8

NASA Technical Reports Server (NTRS)

Sierhuis, Maarten; Clancey, William J.; Damer, Bruce; Brodsky, Boris; vanHoff, Ron

2007-01-01

A virtual worlds presentation technique with embodied, intelligent agents is being developed as an instructional medium suitable to present in situ training on long term space flight. The system combines a behavioral element based on finite state automata, a behavior based reactive architecture also described as subsumption architecture, and a belief-desire-intention agent structure. These three features are being integrated to describe a Brahms virtual environment model of extravehicular crew activity which could become a basis for procedure training during extended space flight.

Joint Dictionary Learning-Based Non-Negative Matrix Factorization for Voice Conversion to Improve Speech Intelligibility After Oral Surgery.

PubMed

Fu, Szu-Wei; Li, Pei-Chun; Lai, Ying-Hui; Yang, Cheng-Chien; Hsieh, Li-Chun; Tsao, Yu

2017-11-01

Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients. Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients.

Working memory training in older adults: evidence of transfer and maintenance effects.

PubMed

Borella, Erika; Carretti, Barbara; Riboldi, Francesco; De Beni, Rossana

2010-12-01

Few studies have examined working memory (WM) training-related gains and their transfer and maintenance effects in older adults. This present research investigates the efficacy of a verbal WM training program in adults aged 65-75 years, considering specific training gains on a verbal WM (criterion) task as well as transfer effects on measures of visuospatial WM, short-term memory, inhibition, processing speed, and fluid intelligence. Maintenance of training benefits was evaluated at 8-month follow-up. Trained older adults showed higher performance than did controls on the criterion task and maintained this benefit after 8 months. Substantial general transfer effects were found for the trained group, but not for the control one. Transfer maintenance gains were found at follow-up, but only for fluid intelligence and processing speed tasks. The results are discussed in terms of cognitive plasticity in older adults. (c) 2010 APA, all rights reserved).

A Preliminary Investigation on the Application of Robotics to Missile Fire Control.

DTIC Science & Technology

1983-11-01

application. Even this is a broad area, but it is one in which Okhe general theories and concepts of robo - tics and/or artificial intelligence can be...K::. 3. Expert Advisors .J1. %4. Data Assimilation and Access Aids 5. Handling Support Systems 6. Support Systems 7...appears, therefore, that a robo - tic forward observer can be manufactured in quantities for a reasonable cost when compared to the cost of training

The Training Services Agency

ERIC Educational Resources Information Center

Holland, Geoffrey

1974-01-01

In a paper presented at the BACIE (British Association for Commercial and Industrial Education) national conference, the Training Services Agency director of planning and intelligence considers the agency's three major responsibilities: corrdinating the statutory industrial training boards, promoting training in other sectors, and administering…

Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information preview and neural networks for plug-in hybrid electric vehicles fuel economy

NASA Astrophysics Data System (ADS)

Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.

2015-06-01

The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

[Inductive reasoning and intelligence test performance--analysis of the manner of the effect of 2 thought training methods for children].

PubMed

Hager, W; Hasselhorn, M; Hübner, S

1995-10-01

For his training programs of inductive reasoning Klauer postulates a transfer effect to inductive thinking as well as to (performance in tests of) intelligence. As evidence for these claims, however, he uses the same data. That means the same tests are used to prove enhancement of inductive thinking and to prove transfer to performance in tests of intelligence. Moreover, Klauer's claim to train inductive thinking is criticized since better performances in at least some of the tests he administers can result due to enhancements in the area of visual perception. Finally, we ask what kind of effects the programs result in: Are they mere coaching effects or do the programs result in better performance due to enhanced competencies? The empirical evidence suggest that positive effects on inductive thinking do not last as long as perceptual competencies that are necessarily fostered when visual material is presented to children.

Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC

NASA Technical Reports Server (NTRS)

Velez, Victor Hugo

2016-01-01

Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.

Context-Based Filtering for Assisted Brain-Actuated Wheelchair Driving

PubMed Central

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

2007-01-01

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

Contributions of Work-Related Stress and Emotional Intelligence to Teacher Engagement: Additive and Interactive Effects.

PubMed

Mérida-López, Sergio; Extremera, Natalio; Rey, Lourdes

2017-09-29

This study examined the additive and interactive effects of role stress and emotional intelligence for predicting engagement among 288 teachers. Emotional intelligence and engagement were positively associated. Role ambiguity and role conflict showed negative associations with vigor and dedication scores. The interaction of role ambiguity and emotional intelligence was significant in explaining engagement dimensions. Similar results were found considering overall teacher engagement. Emotional intelligence boosted engagement when the levels of role ambiguity were higher. Our findings suggest the need for future research examining the impact of job hindrances on the links between emotional intelligence and teachers' occupational well-being indicators. Finally, the implications for emotional intelligence training in education are discussed.

Kongiganak Wind Turbine Replacement and System Upgrade Project

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

Boonstra, Patrick

2016-12-13

The Native Village of Kongiganak, Alaska was awarded a grant to upgrade the braking systems on five wind turbines and upgrade the monitoring and data collection unit to insure that enough energy is available to power the utility. The project manager for this award is Intelligent Energy Systems, LLC located in Anchorage, Alaska. In addition to accomplishing these upgrades, it was the intent for a local wind tech crew to be trained in Kongiganak so that routine maintenance and future repairs will be made by local workers.

Forecasting daily lake levels using artificial intelligence approaches

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal; Nikoofar, Bagher

2012-04-01

Accurate prediction of lake-level variations is important for planning, design, construction, and operation of lakeshore structures and also in the management of freshwater lakes for water supply purposes. In the present paper, three artificial intelligence approaches, namely artificial neural networks (ANNs), adaptive-neuro-fuzzy inference system (ANFIS), and gene expression programming (GEP), were applied to forecast daily lake-level variations up to 3-day ahead time intervals. The measurements at the Lake Iznik in Western Turkey, for the period of January 1961-December 1982, were used for training, testing, and validating the employed models. The results obtained by the GEP approach indicated that it performs better than ANFIS and ANNs in predicting lake-level variations. A comparison was also made between these artificial intelligence approaches and convenient autoregressive moving average (ARMA) models, which demonstrated the superiority of GEP, ANFIS, and ANN models over ARMA models.

Development of the Russian matrix sentence test.

PubMed

Warzybok, Anna; Zokoll, Melanie; Wardenga, Nina; Ozimek, Edward; Boboshko, Maria; Kollmeier, Birger

2015-01-01

To develop the Russian matrix sentence test for speech intelligibility measurements in noise. Test development included recordings, optimization of speech material, and evaluation to investigate the equivalency of the test lists and training. For each of the 500 test items, the speech intelligibility function, speech reception threshold (SRT: signal-to-noise ratio, SNR, that provides 50% speech intelligibility), and slope was obtained. The speech material was homogenized by applying level corrections. In evaluation measurements, speech intelligibility was measured at two fixed SNRs to compare list-specific intelligibility functions. To investigate the training effect and establish reference data, speech intelligibility was measured adaptively. Overall, 77 normal-hearing native Russian listeners. The optimization procedure decreased the spread in SRTs across words from 2.8 to 0.6 dB. Evaluation measurements confirmed that the 16 test lists were equivalent, with a mean SRT of -9.5 ± 0.2 dB and a slope of 13.8 ± 1.6%/dB. The reference SRT, -8.8 ± 0.8 dB for the open-set and -9.4 ± 0.8 dB for the closed-set format, increased slightly for noise levels above 75 dB SPL. The Russian matrix sentence test is suitable for accurate and reliable speech intelligibility measurements in noise.

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

NASA Technical Reports Server (NTRS)

Schmidtchen, Bryce; Solano, Wanda M.; Albasini, Colby

2015-01-01

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

An oil fraction neural sensor developed using electrical capacitance tomography sensor data.

PubMed

Zainal-Mokhtar, Khursiah; Mohamad-Saleh, Junita

2013-08-26

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical Capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes.

Macrocell path loss prediction using artificial intelligence techniques

NASA Astrophysics Data System (ADS)

Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

2014-04-01

The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

The effects of working memory on brain-computer interface performance.

PubMed

Sprague, Samantha A; McBee, Matthew T; Sellers, Eric W

2016-02-01

The purpose of the present study is to evaluate the relationship between working memory and BCI performance. Participants took part in two separate sessions. The first session consisted of three computerized tasks. The List Sorting Working Memory Task was used to measure working memory, the Picture Vocabulary Test was used to measure general intelligence, and the Dimensional Change Card Sort Test was used to measure executive function, specifically cognitive flexibility. The second session consisted of a P300-based BCI copy-spelling task. The results indicate that both working memory and general intelligence are significant predictors of BCI performance. This suggests that working memory training could be used to improve performance on a BCI task. Working memory training may help to reduce a portion of the individual differences that exist in BCI performance allowing for a wider range of users to successfully operate the BCI system as well as increase the BCI performance of current users. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

An Oil Fraction Neural Sensor Developed Using Electrical capacitance Tomography Sensor Data

PubMed Central

Zainal-Mokhtar, Khursiah; Mohamad-Saleh, Junita

2013-01-01

This paper presents novel research on the development of a generic intelligent oil fraction sensor based on Electrical capacitance Tomography (ECT) data. An artificial Neural Network (ANN) has been employed as the intelligent system to sense and estimate oil fractions from the cross-sections of two-component flows comprising oil and gas in a pipeline. Previous works only focused on estimating the oil fraction in the pipeline based on fixed ECT sensor parameters. With fixed ECT design sensors, an oil fraction neural sensor can be trained to deal with ECT data based on the particular sensor parameters, hence the neural sensor is not generic. This work focuses on development of a generic neural oil fraction sensor based on training a Multi-Layer Perceptron (MLP) ANN with various ECT sensor parameters. On average, the proposed oil fraction neural sensor has shown to be able to give a mean absolute error of 3.05% for various ECT sensor sizes. PMID:24064598

Intelligent Multisensor Prodder for Training Operators in Humanitarian Demining

PubMed Central

Fernández, Roemi; Montes, Héctor; Armada, Manuel

2016-01-01

Manual prodding is still one of the most utilized procedures for identifying buried landmines during humanitarian demining activities. However, due to the high number of accidents reported during its practice, it is considered an outmoded and risky procedure and there is a general consensus about the need of introducing upgrades for enhancing the safety of human operators. With the aim of contributing to reduce the number of demining accidents, this paper presents an intelligent multisensory system for training operators in the use of prodders. The proposed tool is able to provide to deminers useful information in two critical issues: (a) the amount of force exerted on the target and if it is greater than the safe limit and, (b) to alert them when the angle of insertion of the prodder is approaching or exceeding a certain dangerous limit. Results of preliminary tests show the feasibility and reliability of the proposed design and highlight the potential benefits of the tool. PMID:27347963

Intelligent Multisensor Prodder for Training Operators in Humanitarian Demining.

PubMed

Fernández, Roemi; Montes, Héctor; Armada, Manuel

2016-06-24

Manual prodding is still one of the most utilized procedures for identifying buried landmines during humanitarian demining activities. However, due to the high number of accidents reported during its practice, it is considered an outmoded and risky procedure and there is a general consensus about the need of introducing upgrades for enhancing the safety of human operators. With the aim of contributing to reduce the number of demining accidents, this paper presents an intelligent multisensory system for training operators in the use of prodders. The proposed tool is able to provide to deminers useful information in two critical issues: (a) the amount of force exerted on the target and if it is greater than the safe limit and, (b) to alert them when the angle of insertion of the prodder is approaching or exceeding a certain dangerous limit. Results of preliminary tests show the feasibility and reliability of the proposed design and highlight the potential benefits of the tool.

Modeling human behaviors and reactions under dangerous environment.

PubMed

Kang, J; Wright, D K; Qin, S F; Zhao, Y

2005-01-01

This paper describes the framework of a real-time simulation system to model human behavior and reactions in dangerous environments. The system utilizes the latest 3D computer animation techniques, combined with artificial intelligence, robotics and psychology, to model human behavior, reactions and decision making under expected/unexpected dangers in real-time in virtual environments. The development of the system includes: classification on the conscious/subconscious behaviors and reactions of different people; capturing different motion postures by the Eagle Digital System; establishing 3D character animation models; establishing 3D models for the scene; planning the scenario and the contents; and programming within Virtools Dev. Programming within Virtools Dev is subdivided into modeling dangerous events, modeling character's perceptions, modeling character's decision making, modeling character's movements, modeling character's interaction with environment and setting up the virtual cameras. The real-time simulation of human reactions in hazardous environments is invaluable in military defense, fire escape, rescue operation planning, traffic safety studies, and safety planning in chemical factories, the design of buildings, airplanes, ships and trains. Currently, human motion modeling can be realized through established technology, whereas to integrate perception and intelligence into virtual human's motion is still a huge undertaking. The challenges here are the synchronization of motion and intelligence, the accurate modeling of human's vision, smell, touch and hearing, the diversity and effects of emotion and personality in decision making. There are three types of software platforms which could be employed to realize the motion and intelligence within one system, and their advantages and disadvantages are discussed.

Tuberculosis control, and the where and why of artificial intelligence

PubMed Central

Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

2017-01-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

PubMed

Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

2014-04-01

This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Tuberculosis control, and the where and why of artificial intelligence.

PubMed

Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

2017-04-01

Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

Advanced Technology Training System on Motor-Operated Valves

NASA Technical Reports Server (NTRS)

Wiederholt, Bradley J.; Widjaja, T. Kiki; Yasutake, Joseph Y.; Isoda, Hachiro

1993-01-01

This paper describes how features from the field of Intelligent Tutoring Systems are applied to the Motor-Operated Valve (MOV) Advanced Technology Training System (ATTS). The MOV ATTS is a training system developed at Galaxy Scientific Corporation for the Central Research Institute of Electric Power Industry in Japan and the Electric Power Research Institute in the United States. The MOV ATTS combines traditional computer-based training approaches with system simulation, integrated expert systems, and student and expert modeling. The primary goal of the MOV ATTS is to reduce human errors that occur during MOV overhaul and repair. The MOV ATTS addresses this goal by providing basic operational information of the MOV, simulating MOV operation, providing troubleshooting practice of MOV failures, and tailoring this training to the needs of each individual student. The MOV ATTS integrates multiple expert models (functional and procedural) to provide advice and feedback to students. The integration also provides expert model validation support to developers. Student modeling is supported by two separate student models: one model registers and updates the student's current knowledge of basic MOV information, while another model logs the student's actions and errors during troubleshooting exercises. These two models are used to provide tailored feedback to the student during the MOV course.

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…

Emotional Intelligence: A Quantitative Study of the Relationship among Academic Success Factors and Emotional Intelligence

ERIC Educational Resources Information Center

Iannucci, Brian A.

2013-01-01

Researchers have found a correlation between emotional intelligence (EI) and success in the workplace. As a result, many companies have invested a large amount of resources into EI testing during their hiring process. In the United States, corporations are spending over $33 billion on hiring, training, and development. In addition to the increase…

Transforming the Conflict in Afghanistan

DTIC Science & Technology

2011-09-01

Company Level Intelligence Cells, Civil Affairs teams, Economic and Political Intelligence Cells, SOICs , and other niche organizations should be...Intelligence Cells, SOICs , and other niche organizations should be harvested to inform VSCC training and other preparatory efforts. Technology should be...central government in Kabul has been most successful in controlling the country through provincial elites of various sorts who organized local men into

Driver's behavioural changes with new intelligent transport system interventions at railway level crossings--A driving simulator study.

PubMed

Larue, Grégoire S; Kim, Inhi; Rakotonirainy, Andry; Haworth, Narelle L; Ferreira, Luis

2015-08-01

Improving safety at railway level crossings is an important issue for the Australian transport system. Governments, the rail industry and road organisations have tried a variety of countermeasures for many years to improve railway level crossing safety. New types of intelligent transport system (ITS) interventions are now emerging due to the availability and the affordability of technology. These interventions target both actively and passively protected railway level crossings and attempt to address drivers' errors at railway crossings, which are mainly a failure to detect the crossing or the train and misjudgement of the train approach speed and distance. This study aims to assess the effectiveness of three emerging ITS that the rail industry considers implementing in Australia: a visual in-vehicle ITS, an audio in-vehicle ITS, as well as an on-road flashing beacons intervention. The evaluation was conducted on an advanced driving simulator with 20 participants per trialled technology, each participant driving once without any technology and once with one of the ITS interventions. Every participant drove through a range of active and passive crossings with and without trains approaching. Their speed approach of the crossing, head movements and stopping compliance were measured. Results showed that driver behaviour was changed with the three ITS interventions at passive crossings, while limited effects were found at active crossings, even with reduced visibility. The on-road intervention trialled was unsuccessful in improving driver behaviour; the audio and visual ITS improved driver behaviour when a train was approaching. A trend toward worsening driver behaviour with the visual ITS was observed when no trains were approaching. This trend was not observed for the audio ITS intervention, which appears to be the ITS intervention with the highest potential for improving safety at passive crossings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Intelligent Maintenance Training Technology

DTIC Science & Technology

1988-03-31

Psychology Knowledge Systems Laboratory University of California Stanford University Berkeley, CA 94720 701 Welch Road Palo Alto, CA 94304 Dr. Milton S ...David S . Surmon James Wogulis 0 Behavioral Technology Laboratories Department of Psychology University of Southern California Sponsored by Office of...Munro Quentin A. Pizzini David S . Surmon James Wogulis March 1988 U Technical Report No. 110 Behavioral Technology Laboratories University of Southern

Let's talk it over : interagency cooperation facilities success : a case study : the New York, New Jersey, Connecticut metropolitan area TRANSMIT operational test : ensuring integration of intelligent transportation systems products and services

DOT National Transportation Integrated Search

1989-01-01

This manual provides basic background information and step-by-step procedures for conducting traffic conflict surveys at signalized and unsignalized intersections. The manual was prepared as a training aid and reference source for persons who are ass...

Intelligent transportation systems Professional Capacity Building Program : planning and deploying ITS : six white papers describing current and planned programs of five transportation associations and four university ITS Research Centers of Excellence

DOT National Transportation Integrated Search

1997-12-01

In the fall of 1997, the ITS Professional Capacity Building Program initiated the development of six White Papers to briefly describe the current status of, and plans for future education and training activities of six organizations engaged in ...

How to Construct More Accurate Student Models: Comparing and Optimizing Knowledge Tracing and Performance Factor Analysis

ERIC Educational Resources Information Center

Gong, Yue; Beck, Joseph E.; Heffernan, Neil T.

2011-01-01

Student modeling is a fundamental concept applicable to a variety of intelligent tutoring systems (ITS). However, there is not a lot of practical guidance on how to construct and train such models. This paper compares two approaches for student modeling, Knowledge Tracing (KT) and Performance Factors Analysis (PFA), by evaluating their predictive…

Effectiveness of training of spiritual intelligence components on depression, anxiety, and stress of adolescents.

PubMed

Ebrahimi, M; Jalilabadi, Z; Ghareh Chenagh, K H; Amini, F; Arkian, F

2015-01-01

Objective: As the development of adolescence is identified by different types of stress and youths are further exhibited because of bodily, psychic and cultural issues, this research tried to examine the training efficacy of spiritual intelligence parts on depression, tension, and pressure of teenagers. Methodology: The present study was undergone in the initial part of the educational year 2014-2015. Moreover, it was quasi-empirical via post test-pretest, which employed a checking team. Therefore, forty of the large schoolman scholars in Tehran chose to use the utility sampling approach and registered in the test team, overlooking the group randomly (n = 20). Both groups were pretested by using a demographic survey, rate of grief, stress, and anxiety DASS-42. Eventually, the test team rose for 8 gatherings following the practice of spiritual intelligence elements and the checking team obtained no interruption. Next, both teams were post-tested, and the obtained data were analyzed by using presumed and circumstantial analytical approaches conducted through SPSS21. Results: The sequences showed that the exercise of the spiritual intelligence parts clearly decreased grief, stress, and anxiety in youths. Conclusion: The research found that because of the clear stage of the efficacy of spiritual intelligence factors training, its inexpensive and great acceptability by the youths, particularly while working in a team, it had an immense direct effect on the decrease of grief, stress, and anxiety.

Side-by-side ANFIS as a useful tool for estimating correlated thermophysical properties

NASA Astrophysics Data System (ADS)

Grieu, Stéphane; Faugeroux, Olivier; Traoré, Adama; Claudet, Bernard; Bodnar, Jean-Luc

2015-12-01

In the present paper, an artificial intelligence-based approach dealing with the estimation of correlated thermophysical properties is designed and evaluated. This new and "intelligent" approach makes use of photothermal responses obtained when homogeneous materials are subjected to a light flux. Commonly, gradient-based algorithms are used as parameter estimation techniques. Unfortunately, such algorithms show instabilities leading to non-convergence in case of correlated properties to be estimated from a rebuilt impulse response. So, the main objective of the present work was to simultaneously estimate both the thermal diffusivity and conductivity of homogeneous materials, from front-face or rear-face photothermal responses to pseudo random binary signals. To this end, we used side-by-side neuro-fuzzy systems (adaptive network-based fuzzy inference systems) trained with a hybrid algorithm. We focused on the impact on generalization of both the examples used during training and the fuzzification process. In addition, computation time was a key point to consider. That is why the developed algorithm is computationally tractable and allows both the thermal diffusivity and conductivity of homogeneous materials to be simultaneously estimated with very good accuracy (the generalization error ranges between 4.6% and 6.2%).

Building an intelligent tutoring system for procedural domains

NASA Technical Reports Server (NTRS)

Warinner, Andrew; Barbee, Diann; Brandt, Larry; Chen, Tom; Maguire, John

1990-01-01

Jobs that require complex skills that are too expensive or dangerous to develop often use simulators in training. The strength of a simulator is its ability to mimic the 'real world', allowing students to explore and experiment. A good simulation helps the student develop a 'mental model' of the real world. The closer the simulation is to 'real life', the less difficulties there are transferring skills and mental models developed on the simulator to the real job. As graphics workstations increase in power and become more affordable they become attractive candidates for developing computer-based simulations for use in training. Computer based simulations can make training more interesting and accessible to the student.

Telehealth innovations in health education and training.

PubMed

Conde, José G; De, Suvranu; Hall, Richard W; Johansen, Edward; Meglan, Dwight; Peng, Grace C Y

2010-01-01

Telehealth applications are increasingly important in many areas of health education and training. In addition, they will play a vital role in biomedical research and research training by facilitating remote collaborations and providing access to expensive/remote instrumentation. In order to fulfill their true potential to leverage education, training, and research activities, innovations in telehealth applications should be fostered across a range of technology fronts, including online, on-demand computational models for simulation; simplified interfaces for software and hardware; software frameworks for simulations; portable telepresence systems; artificial intelligence applications to be applied when simulated human patients are not options; and the development of more simulator applications. This article presents the results of discussion on potential areas of future development, barries to overcome, and suggestions to translate the promise of telehealth applications into a transformed environment of training, education, and research in the health sciences.

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.

State of the Art and Challenges of Radio Spectrum Monitoring in China

NASA Astrophysics Data System (ADS)

Lu, Q. N.; Yang, J. J.; Jin, Z. Y.; Chen, D. Z.; Huang, M.

2017-10-01

This paper provides an overview of radio spectrum monitoring in China. First, research background, the motivation is described and then train of thought, the prototype system, and the accomplishments are presented. Current radio spectrum monitoring systems are man-machine communication systems, which are unable to detect and process the radio interference automatically. In order to realize intelligent radio monitoring and spectrum management, we proposed an Internet of Things-based spectrum sensing approach using information system architecture and implemented a pilot program; then some very interesting results were obtained.

Intelligent retrieval of medical images from the Internet

NASA Astrophysics Data System (ADS)

Tang, Yau-Kuo; Chiang, Ted T.

1996-05-01

The object of this study is using Internet resources to provide a cost-effective, user-friendly method to access the medical image archive system and to provide an easy method for the user to identify the images required. This paper describes the prototype system architecture, the implementation, and results. In the study, we prototype the Intelligent Medical Image Retrieval (IMIR) system as a Hypertext Transport Prototype server and provide Hypertext Markup Language forms for user, as an Internet client, using browser to enter image retrieval criteria for review. We are developing the intelligent retrieval engine, with the capability to map the free text search criteria to the standard terminology used for medical image identification. We evaluate retrieved records based on the number of the free text entries matched and their relevance level to the standard terminology. We are in the integration and testing phase. We have collected only a few different types of images for testing and have trained a few phrases to map the free text to the standard medical terminology. Nevertheless, we are able to demonstrate the IMIR's ability to search, retrieve, and review medical images from the archives using general Internet browser. The prototype also uncovered potential problems in performance, security, and accuracy. Additional studies and enhancements will make the system clinically operational.

Comparison of display enhancement with intelligent decision-aiding

NASA Technical Reports Server (NTRS)

Kirlik, Alex; Markert, Wendy J.; Kossack, Merrick

1992-01-01

Currently, two main approaches exist for improving the human-machine interface component of a system in order to improve overall system performance, display enhancement and intelligent decision aiding. Each of these two approaches has its own set of advantages and disadvantages, as well as introduce its own set of additional performance problems. These characteristics should help identify which types of problem situations and domains are better aided by which type of strategy. The characteristic issues are described of these two decision aiding strategies. Then differences in expert and novice decision making are described in order to help determine whether a particular strategy may be better for a particular type of user. Finally, research is outlined to compare and contrast the two technologies, as well as to examine the interaction effects introduced by the different skill levels and the different methods for training operators.

Hybrid supervisory control using recurrent fuzzy neural network for tracking periodic inputs.

PubMed

Lin, F J; Wai, R J; Hong, C M

2001-01-01

A hybrid supervisory control system using a recurrent fuzzy neural network (RFNN) is proposed to control the mover of a permanent magnet linear synchronous motor (PMLSM) servo drive for the tracking of periodic reference inputs. First, the field-oriented mechanism is applied to formulate the dynamic equation of the PMLSM. Then, a hybrid supervisory control system, which combines a supervisory control system and an intelligent control system, is proposed to control the mover of the PMLSM for periodic motion. The supervisory control law is designed based on the uncertainty bounds of the controlled system to stabilize the system states around a predefined bound region. Since the supervisory control law will induce excessive and chattering control effort, the intelligent control system is introduced to smooth and reduce the control effort when the system states are inside the predefined bound region. In the intelligent control system, the RFNN control is the main tracking controller which is used to mimic a idea control law and a compensated control is proposed to compensate the difference between the idea control law and the RFNN control. The RFNN has the merits of fuzzy inference, dynamic mapping and fast convergence speed, In addition, an online parameter training methodology, which is derived using the Lyapunov stability theorem and the gradient descent method, is proposed to increase the learning capability of the RFNN. The proposed hybrid supervisory control system using RFNN can track various periodic reference inputs effectively with robust control performance.

Contributions of Work-Related Stress and Emotional Intelligence to Teacher Engagement: Additive and Interactive Effects

PubMed Central

2017-01-01

This study examined the additive and interactive effects of role stress and emotional intelligence for predicting engagement among 288 teachers. Emotional intelligence and engagement were positively associated. Role ambiguity and role conflict showed negative associations with vigor and dedication scores. The interaction of role ambiguity and emotional intelligence was significant in explaining engagement dimensions. Similar results were found considering overall teacher engagement. Emotional intelligence boosted engagement when the levels of role ambiguity were higher. Our findings suggest the need for future research examining the impact of job hindrances on the links between emotional intelligence and teachers’ occupational well-being indicators. Finally, the implications for emotional intelligence training in education are discussed. PMID:28961218

An Anticipatory and Deceptive AI Utilizing Bayesian Belief Networks

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

Lake, Joe E; Allgood, Glenn O; Olama, Mohammed M

The U.S. military defines antiterrorism as the defensive posture taken against terrorist threats. Antiterrorism includes fostering awareness of potential threats, deterring aggressors, developing security measures, planning for future events, interdicting an event in progress, and ultimately mitigating and managing the consequences of an event. Recent events highlight the need for efficient tools for training our military and homeland security officers for anticipating threats posed by terrorists. These tools need to be easy enough so that they are readily usable without substantial training, but still maintain the complexity to allow for a level of deceptive reasoning on the part of themore » opponent. To meet this need, we propose to integrate a Bayesian Belief Network (BBN) model for threat anticipation and deceptive reasoning into training simulation environments currently utilized by several organizations within the Department of Defense (DoD). BBNs have the ability to deal with various types of uncertainties; such as identities, capabilities, target attractiveness, and the combinations of the previous. They also allow for disparate types of data to be fused in a coherent, analytically defensible, and understandable manner. A BBN has been developed by ORNL uses a network engineering process that treats the probability distributions of each node with in the broader context of the system development effort as a whole, and not in isolation. The network will be integrated into the Research Network Inc,(RNI) developed Game Distributed Interactive Simulation (GDIS) as a smart artificial intelligence module. GDIS is utilized by several DoD and civilian organizations as a distributed training tool for a multiplicity of reasons. It has garnered several awards for its realism, ease of use, and popularity. One area that it still has room to excel in, as most video training tools do, is in the area of artificial intelligence of opponent combatants. It is believed that by utilizing BBN as the backbone of the artificial intelligence code, a more realistic and helpful training experience will be available and enemy combatants that move and strategize with purpose will be obtained.« less

Audiomotor Perceptual Training Enhances Speech Intelligibility in Background Noise.

PubMed

Whitton, Jonathon P; Hancock, Kenneth E; Shannon, Jeffrey M; Polley, Daniel B

2017-11-06

Sensory and motor skills can be improved with training, but learning is often restricted to practice stimuli. As an exception, training on closed-loop (CL) sensorimotor interfaces, such as action video games and musical instruments, can impart a broad spectrum of perceptual benefits. Here we ask whether computerized CL auditory training can enhance speech understanding in levels of background noise that approximate a crowded restaurant. Elderly hearing-impaired subjects trained for 8 weeks on a CL game that, like a musical instrument, challenged them to monitor subtle deviations between predicted and actual auditory feedback as they moved their fingertip through a virtual soundscape. We performed our study as a randomized, double-blind, placebo-controlled trial by training other subjects in an auditory working-memory (WM) task. Subjects in both groups improved at their respective auditory tasks and reported comparable expectations for improved speech processing, thereby controlling for placebo effects. Whereas speech intelligibility was unchanged after WM training, subjects in the CL training group could correctly identify 25% more words in spoken sentences or digit sequences presented in high levels of background noise. Numerically, CL audiomotor training provided more than three times the benefit of our subjects' hearing aids for speech processing in noisy listening conditions. Gains in speech intelligibility could be predicted from gameplay accuracy and baseline inhibitory control. However, benefits did not persist in the absence of continuing practice. These studies employ stringent clinical standards to demonstrate that perceptual learning on a computerized audio game can transfer to "real-world" communication challenges. Copyright © 2017 Elsevier Ltd. All rights reserved.

Cogadh na Saoirse: British Intelligence Operations During the Anglo-Irish War (1916-1921)

DTIC Science & Technology

2010-05-21

managed secret service operations. In late 1919, the Irish government transferred responsibility for the secret service to BSS central headquarters...brothers. Intelligence overall suffered greatly as there was no office responsible for information management and analysis or collection guidance to the...trained soldiers able to manage HUMINT sources. Consequently, they often conducted intelligence gathering or source meetings on their own, and in

Does U.S. Army Humint Doctrine Achieve Its Objectives? What Have Iraq and Afghanistan Taught Us?

DTIC Science & Technology

2013-03-01

OSINT Open Source Intelligence PIR Priority Intelligence Requirements PLDC Primary Leadership Development Course PME Professional Military...Exploitation (DOCEX/DOMEX) Analysis, Open Source Intelligence ( OSINT ), Military Source Operations and Interrogations.8 The Army employs HUMINT in a...analysis, and OSINT , although important, are traditionally thought of as less critical than Interrogations or Source Operations. While training does

32 CFR 813.3 - Responsibilities.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., bomb damage assessment, collateral intelligence, training, historical, public affairs, and other needs. (3) Sets combat training standards and develops programs for all Air Force COMCAM personnel (includes both formal classroom and field readiness training). (4) Coordinates and meets COMCAM needs in war...

DoD Civilian Training: Source, Content, Frequency and Cost

DTIC Science & Technology

1994-03-01

Intelligence School Charleston, SC, and the Fire School will move to Fort Huachuca, AZ, from portion of the Naval Technical Training Fort Devens , MA...Recruiting & Retention School 2 10 Fort Bliss, TX Air Defense Artillery 2 I 11 Fort Devens , MA Army Intelligence School 4 12 Fort Eustis, VA Aviation...17457 4385 Gigllng Road- 8th Floor , Fort Ord, CA 93941-5800 94 6 8 07A’ The Assistant Secretary of Defense for Personnel and Readiness issued a tasker

Aviation safety and automation technology for subsonic transports

NASA Technical Reports Server (NTRS)

Albers, James A.

1991-01-01

Discussed here are aviation safety human factors and air traffic control (ATC) automation research conducted at the NASA Ames Research Center. Research results are given in the areas of flight deck and ATC automations, displays and warning systems, crew coordination, and crew fatigue and jet lag. Accident investigation and an incident reporting system that is used to guide the human factors research is discussed. A design philosophy for human-centered automation is given, along with an evaluation of automation on advanced technology transports. Intelligent error tolerant systems such as electronic checklists are discussed along with design guidelines for reducing procedure errors. The data on evaluation of Crew Resource Management (CRM) training indicates highly significant positive changes in appropriate flight deck behavior and more effective use of available resources for crew members receiving the training.

Structure-biodegradability study and computer-automated prediction of aerobic biodegradation of chemicals

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

Klopman, G.; Tu, M.

1997-09-01

It is shown that a combination of two programs, MultiCASE and META, can help assess the biodegradability of industrial organic materials in the ecosystem. MultiCASE is an artificial intelligence computer program that had been trained to identify molecular substructures believed to cause or inhibit biodegradation and META is an expert system trained to predict the aerobic biodegradation products of organic molecules. These two programs can be used to help evaluate the fate of disposed chemicals by estimating their biodegradability and the nature of their biodegradation products under conditions that may model the environment.

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.

Personnel Selection Influences on Remotely Piloted Aircraft Human-System Integration.

PubMed

Carretta, Thomas R; King, Raymond E

2015-08-01

Human-system integration (HSI) is a complex process used to design and develop systems that integrate human capabilities and limitations in an effective and affordable manner. Effective HSI incorporates several domains, including manpower, personnel and training, human factors, environment, safety, occupational health, habitability, survivability, logistics, intelligence, mobility, and command and control. To achieve effective HSI, the relationships among these domains must be considered. Although this integrated approach is well documented, there are many instances where it is not followed. Human factors engineers typically focus on system design with little attention to the skills, abilities, and other characteristics needed by human operators. When problems with fielded systems occur, additional training of personnel is developed and conducted. Personnel selection is seldom considered during the HSI process. Complex systems such as aviation require careful selection of the individuals who will interact with the system. Personnel selection is a two-stage process involving select-in and select-out procedures. Select-in procedures determine which candidates have the aptitude to profit from training and represent the best investment. Select-out procedures focus on medical qualification and determine who should not enter training for medical reasons. The current paper discusses the role of personnel selection in the HSI process in the context of remotely piloted aircraft systems.

Artificial intelligence techniques for embryo and oocyte classification.

PubMed

Manna, Claudio; Nanni, Loris; Lumini, Alessandra; Pappalardo, Sebastiana

2013-01-01

One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns). The proposed system was tested on two data sets of 269 oocytes and 269 corresponding embryos from 104 women and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they show an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in our capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. In this work, we concentrate our efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the 'local binary patterns'). The proposed system is tested on two data sets, of 269 oocytes and 269 corresponding embryos from 104 women, and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they showed an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. Copyright © 2012 Reproductive Healthcare Ltd. Published by Elsevier Ltd. All rights reserved.

Forecasting municipal solid waste generation using artificial intelligence modelling approaches.

PubMed

Abbasi, Maryam; El Hanandeh, Ali

2016-10-01

Municipal solid waste (MSW) management is a major concern to local governments to protect human health, the environment and to preserve natural resources. The design and operation of an effective MSW management system requires accurate estimation of future waste generation quantities. The main objective of this study was to develop a model for accurate forecasting of MSW generation that helps waste related organizations to better design and operate effective MSW management systems. Four intelligent system algorithms including support vector machine (SVM), adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and k-nearest neighbours (kNN) were tested for their ability to predict monthly waste generation in the Logan City Council region in Queensland, Australia. Results showed artificial intelligence models have good prediction performance and could be successfully applied to establish municipal solid waste forecasting models. Using machine learning algorithms can reliably predict monthly MSW generation by training with waste generation time series. In addition, results suggest that ANFIS system produced the most accurate forecasts of the peaks while kNN was successful in predicting the monthly averages of waste quantities. Based on the results, the total annual MSW generated in Logan City will reach 9.4×10(7)kg by 2020 while the peak monthly waste will reach 9.37×10(6)kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-10-01

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

The Department of Homeland Security Intelligence Enterprise: Operational Overview and Oversight Challenges for Congress

DTIC Science & Technology

2009-05-27

technology network architecture to connect various DHS elements and promote information sharing.17 • Establish a DHS State, Local, and Regional...A Strategic Plan; training, and the implementation of a comprehensive information systems architecture .65 As part of its integration...information technology network architecture was submitted to Congress last year. See DHS I&A, Homeland Security Information Technology Network

Voice technology and BBN

NASA Technical Reports Server (NTRS)

Wolf, Jared J.

1977-01-01

The following research was discussed: (1) speech signal processing; (2) automatic speech recognition; (3) continuous speech understanding; (4) speaker recognition; (5) speech compression; (6) subjective and objective evaluation of speech communication system; (7) measurement of the intelligibility and quality of speech when degraded by noise or other masking stimuli; (8) speech synthesis; (9) instructional aids for second-language learning and for training of the deaf; and (10) investigation of speech correlates of psychological stress. Experimental psychology, control systems, and human factors engineering, which are often relevant to the proper design and operation of speech systems are described.

Intelligence, Surveillance, And Reconnaissance Processing, Exploitation, And Dissemination System In Support Of Global Strike In 2035

DTIC Science & Technology

2012-02-15

ways is the human brain. If the US could design its Processing, Exploitation, and Dissemination (PED) architecture to function similarly to the human...is that a lot of training is required before it starts to “think” in a useful fashion. What the PED system needs is a way to jump start this...Cross-network connectivity Once the PED is using identical standards and operating on two networks at different classification levels, install a

A hypertext system that learns from user feedback

NASA Technical Reports Server (NTRS)

Mathe, Nathalie

1994-01-01

Retrieving specific information from large amounts of documentation is not an easy task. It could be facilitated if information relevant in the current problem solving context could be automatically supplied to the user. As a first step towards this goal, we have developed an intelligent hypertext system called CID (Computer Integrated Documentation). Besides providing an hypertext interface for browsing large documents, the CID system automatically acquires and reuses the context in which previous searches were appropriate. This mechanism utilizes on-line user information requirements and relevance feedback either to reinforce current indexing in case of success or to generate new knowledge in case of failure. Thus, the user continually augments and refines the intelligence of the retrieval system. This allows the CID system to provide helpful responses, based on previous usage of the documentation, and to improve its performance over time. We successfully tested the CID system with users of the Space Station Freedom requirements documents. We are currently extending CID to other application domains (Space Shuttle operations documents, airplane maintenance manuals, and on-line training). We are also exploring the potential commercialization of this technique.

Telehealth Innovations in Health Education and Training

PubMed Central

De, Suvranu; Hall, Richard W.; Johansen, Edward; Meglan, Dwight; Peng, Grace C.Y.

2010-01-01

Abstract Telehealth applications are increasingly important in many areas of health education and training. In addition, they will play a vital role in biomedical research and research training by facilitating remote collaborations and providing access to expensive/remote instrumentation. In order to fulfill their true potential to leverage education, training, and research activities, innovations in telehealth applications should be fostered across a range of technology fronts, including online, on-demand computational models for simulation; simplified interfaces for software and hardware; software frameworks for simulations; portable telepresence systems; artificial intelligence applications to be applied when simulated human patients are not options; and the development of more simulator applications. This article presents the results of discussion on potential areas of future development, barries to overcome, and suggestions to translate the promise of telehealth applications into a transformed environment of training, education, and research in the health sciences. PMID:20155874

Multi Modality Brain Mapping System (MBMS) Using Artificial Intelligence and Pattern Recognition

NASA Technical Reports Server (NTRS)

Nikzad, Shouleh (Inventor); Kateb, Babak (Inventor)

2017-01-01

A Multimodality Brain Mapping System (MBMS), comprising one or more scopes (e.g., microscopes or endoscopes) coupled to one or more processors, wherein the one or more processors obtain training data from one or more first images and/or first data, wherein one or more abnormal regions and one or more normal regions are identified; receive a second image captured by one or more of the scopes at a later time than the one or more first images and/or first data and/or captured using a different imaging technique; and generate, using machine learning trained using the training data, one or more viewable indicators identifying one or abnormalities in the second image, wherein the one or more viewable indicators are generated in real time as the second image is formed. One or more of the scopes display the one or more viewable indicators on the second image.

Modeling Shock Train Leading Edge Detection in Dual-Mode Scramjets

NASA Astrophysics Data System (ADS)

Ladeinde, Foluso; Lou, Zhipeng; Li, Wenhai

2016-11-01

The objective of this study is to accurately model the detection of shock train leading edge (STLE) in dual-mode scramjet (DMSJ) engines intended for hypersonic flight in air-breathing propulsion systems. The associated vehicles have applications in military warfare and intelligence, and there is commercial interest as well. Shock trains are of interest because they play a significant role in the inability of a DMSJ engine to develop the required propulsive force. The experimental approach to STLE detection has received some attention; as have numerical calculations. However, virtually all of the numerical work focus on mechanically- (i.e., pressure-) generated shock trains, which are much easier to model relative to the phenomenon in the real system where the shock trains are generated by combustion. A focus on combustion, as in the present studies, enables the investigation of the effects of equivalence ratio, which, together with the Mach number, constitutes an important parameter determining mode transition. The various numerical approaches implemented in our work will be reported, with result comparisons to experimental data. The development of an STLE detection procedure in an a priori manner will also be discussed.

Breast Cancer Recognition Using a Novel Hybrid Intelligent Method

PubMed Central

Addeh, Jalil; Ebrahimzadeh, Ata

2012-01-01

Breast cancer is the second largest cause of cancer deaths among women. At the same time, it is also among the most curable cancer types if it can be diagnosed early. This paper presents a novel hybrid intelligent method for recognition of breast cancer tumors. The proposed method includes three main modules: the feature extraction module, the classifier module, and the optimization module. In the feature extraction module, fuzzy features are proposed as the efficient characteristic of the patterns. In the classifier module, because of the promising generalization capability of support vector machines (SVM), a SVM-based classifier is proposed. In support vector machine training, the hyperparameters have very important roles for its recognition accuracy. Therefore, in the optimization module, the bees algorithm (BA) is proposed for selecting appropriate parameters of the classifier. The proposed system is tested on Wisconsin Breast Cancer database and simulation results show that the recommended system has a high accuracy. PMID:23626945

A Technical Analysis Information Fusion Approach for Stock Price Analysis and Modeling

NASA Astrophysics Data System (ADS)

Lahmiri, Salim

In this paper, we address the problem of technical analysis information fusion in improving stock market index-level prediction. We present an approach for analyzing stock market price behavior based on different categories of technical analysis metrics and a multiple predictive system. Each category of technical analysis measures is used to characterize stock market price movements. The presented predictive system is based on an ensemble of neural networks (NN) coupled with particle swarm intelligence for parameter optimization where each single neural network is trained with a specific category of technical analysis measures. The experimental evaluation on three international stock market indices and three individual stocks show that the presented ensemble-based technical indicators fusion system significantly improves forecasting accuracy in comparison with single NN. Also, it outperforms the classical neural network trained with index-level lagged values and NN trained with stationary wavelet transform details and approximation coefficients. As a result, technical information fusion in NN ensemble architecture helps improving prediction accuracy.

Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

PubMed Central

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2013-01-01

Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. PMID:21917512

Artificial intelligence techniques applied to the development of a decision-support system for diagnosing celiac disease.

PubMed

Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

2011-11-01

Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. To develop a clinical decision-support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision-support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k=0.68 (p<0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician's diagnostic impression and the gold standard k=0. 64 (p<0.0001). There was moderate agreement between the physician's diagnostic impression and CDSS k=0.46 (p=0.0008). The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent accuracy in differentiating possible positive from negative CD diagnoses. This study may contribute towards developing of a computer-assisted environment to support CD diagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Teachers' Emotional Intelligence: The Impact of Training

ERIC Educational Resources Information Center

Dolev, Nina; Leshem, Shosh

2016-01-01

A growing number of studies have suggested that teachers' personal competencies, and more specifically Emotional Intelligence (EI), are particularly important for teacher effectiveness. Recently, there has also been a growing recognition of the importance of social-emotional competencies to students' learning and academic achievement. However,…

Intelligence Studies

ERIC Educational Resources Information Center

Monaghan, Peter

2009-01-01

To make an academic study of matters inherently secret and potentially explosive seems a tall task. But a growing number of scholars are drawn to understanding spycraft. The interdisciplinary field of intelligence studies is mushrooming, as scholars trained in history, international studies, and political science examine such subjects as the…

Intelligent Tutoring Systems for Procedural Task Training of Remote Payload Operations at NASA

NASA Technical Reports Server (NTRS)

Ong, James; Noneman, Steven

2000-01-01

Intelligent Tutoring Systems (ITSs) encode and apply the subject matter and teaching expertise of experienced instructors to provide students with individualized instruction automatically. ITSs complement training simulators by providing automated instruction when it is not economical or feasible to dedicate an instructor to each student during training simulations. Despite their proven training effectiveness and favorable operating cost, however, relatively few ITSs are in use. This is largely because it is usually costly and difficult to encode the task knowledge used by the ITS to evaluate the student's actions and assess the student's performance. Procedural tasks are tasks for which there exist procedures, guidelines, and strategies that determine the correct set of steps to be taken within each situation. To lower the cost and difficulty of creating tutoring systems for procedural task training, Stottler Henke Associates, Inc. (SHAI) worked closely with the Operations Training Group at NASA's Marshall Space Flight Center to develop the Task Tutor Toolkit (T (exp 3)), a generic tutoring system shell and scenario authoring tool. The Task Tutor Toolkit employs a case-based reasoning approach where the instructor creates a procedure template that specifies the range of student actions that are "correct" within each scenario. Because each procedure template is specific to a single scenario, the system can employ relatively simple reasoning methods to represent a correct set of actions and assess student performance. This simplicity enables a non-programmer to specify task knowledge quickly and easily by via graphical user interface, using a "demonstrate, generalize, and annotate" paradigm, that recognizes the range of possible valid actions and infers principles understood (or misunderstood) by the student when those actions are carried out. The Task Tutor Toolkit was also designed to be modular and general, so that it can be interfaced with a wide range of training simulators and support a variety of training domains. SHAI and NASA applied the Task Tutor Toolkit to create the Remote Payload Operations Tutor (RPOT). RPOT is a specific tutoring system application which lets scientists who are new to space mission operations learn to monitor and control their experiments aboard the International Space Station according to NASA payload regulations, guidelines, and procedures. The RPOT simulator lets students practice these skills by monitoring the telemetry variable values of a simple, hypothetical experiment, sending commands to the experiment, coordinating with NASA personnel via voice communication loops, and submitting and retrieving information via documents and forms. At the end of each scenario, RPOT displays the principles correctly or incorrectly demonstrated by the student, along with explanations and background information. The effectiveness of RPOT and the Task Tutor Toolkit are currently under evaluation at NASA.

Teachers and artificial intelligence. The Logo connection.

PubMed

Merbler, J B

1990-12-01

This article describes a three-phase program for training special education teachers to teach Logo and artificial intelligence. Logo is derived from the LISP computer language and is relatively simple to learn and use, and it is argued that these factors make it an ideal tool for classroom experimentation in basic artificial intelligence concepts. The program trains teachers to develop simple demonstrations of artificial intelligence using Logo. The material that the teachers learn to teach is suitable as an advanced level topic for intermediate- through secondary-level students enrolled in computer competency or similar courses. The material emphasizes problem-solving and thinking skills using a nonverbal expressive medium (Logo), thus it is deemed especially appropriate for hearing-impaired children. It is also sufficiently challenging for academically talented children, whether hearing or deaf. Although the notion of teachers as programmers is controversial, Logo is relatively easy to learn, has direct implications for education, and has been found to be an excellent tool for empowerment-for both teachers and children.

Prediction of lithium response in first-episode mania using the LITHium Intelligent Agent (LITHIA): Pilot data and proof-of-concept.

PubMed

Fleck, David E; Ernest, Nicholas; Adler, Caleb M; Cohen, Kelly; Eliassen, James C; Norris, Matthew; Komoroski, Richard A; Chu, Wen-Jang; Welge, Jeffrey A; Blom, Thomas J; DelBello, Melissa P; Strakowski, Stephen M

2017-06-01

Individualized treatment for bipolar disorder based on neuroimaging treatment targets remains elusive. To address this shortcoming, we developed a linguistic machine learning system based on a cascading genetic fuzzy tree (GFT) design called the LITHium Intelligent Agent (LITHIA). Using multiple objectively defined functional magnetic resonance imaging (fMRI) and proton magnetic resonance spectroscopy ( 1 H-MRS) inputs, we tested whether LITHIA could accurately predict the lithium response in participants with first-episode bipolar mania. We identified 20 subjects with first-episode bipolar mania who received an adequate trial of lithium over 8 weeks and both fMRI and 1 H-MRS scans at baseline pre-treatment. We trained LITHIA using 18 1 H-MRS and 90 fMRI inputs over four training runs to classify treatment response and predict symptom reductions. Each training run contained a randomly selected 80% of the total sample and was followed by a 20% validation run. Over a different randomly selected distribution of the sample, we then compared LITHIA to eight common classification methods. LITHIA demonstrated nearly perfect classification accuracy and was able to predict post-treatment symptom reductions at 8 weeks with at least 88% accuracy in training and 80% accuracy in validation. Moreover, LITHIA exceeded the predictive capacity of the eight comparator methods and showed little tendency towards overfitting. The results provided proof-of-concept that a novel GFT is capable of providing control to a multidimensional bioinformatics problem-namely, prediction of the lithium response-in a pilot data set. Future work on this, and similar machine learning systems, could help assign psychiatric treatments more efficiently, thereby optimizing outcomes and limiting unnecessary treatment. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Intelligent systems and advanced user interfaces for design, operation, and maintenance of command management systems

NASA Technical Reports Server (NTRS)

Potter, William J.; Mitchell, Christine M.

1993-01-01

Historically, command management systems (CMS) have been large and expensive spacecraft-specific software systems that were costly to build, operate, and maintain. Current and emerging hardware, software, and user interface technologies may offer an opportunity to facilitate the initial formulation and design of a spacecraft-specific CMS as well as to develop a more generic CMS system. New technologies, in addition to a core CMS common to a range of spacecraft, may facilitate the training and enhance the efficiency of CMS operations. Current mission operations center (MOC) hardware and software include Unix workstations, the C/C++ programming languages, and an X window interface. This configuration provides the power and flexibility to support sophisticated and intelligent user interfaces that exploit state-of-the-art technologies in human-machine interaction, artificial intelligence, and software engineering. One of the goals of this research is to explore the extent to which technologies developed in the research laboratory can be productively applied in a complex system such as spacecraft command management. Initial examination of some of these issues in CMS design and operation suggests that application of technologies such as intelligent planning, case-based reasoning, human-machine systems design and analysis tools (e.g., operator and designer models), and human-computer interaction tools (e.g., graphics, visualization, and animation) may provide significant savings in the design, operation, and maintenance of the CMS for a specific spacecraft as well as continuity for CMS design and development across spacecraft. The first six months of this research saw a broad investigation by Georgia Tech researchers into the function, design, and operation of current and planned command management systems at Goddard Space Flight Center. As the first step, the researchers attempted to understand the current and anticipated horizons of command management systems at Goddard. Preliminary results are given on CMS commonalities and causes of low re-use, and methods are proposed to facilitate increased re-use.

An Intelligent Tutoring System for Antibody Identification

PubMed Central

Smith, Philip J.; Miller, Thomas E.; Fraser, Jane M.

1990-01-01

Empirical studies of medical technology students indicate that there is considerable need for additional skill development in performing tasks such as antibody identification. While this need is currently met by on-the-job training after employment, computer-based tutoring systems offer an alternative or supplemental problem-based learning environment that could be more cost effective. We have developed a prototype for such a tutoring system as part of a project to develop educational tools for the field of transfusion medicine. This system provides a microworld in which students can explore and solve cases, receiving assistance and tutoring from the computer as needed.

Electropalatography in home training of retracted articulation in a Swedish child with cleft palate: effect on articulation pattern and speech.

PubMed

Lohmander, Anette; Henriksson, Cecilia; Havstam, Christina

2010-12-01

The aim was to evaluate the effectiveness of electropalatography (EPG) in home training of persistent articulation errors in an 11-year-old Swedish girl born with isolated cleft palate. The /t/ and /s/ sounds were trained in a single subject design across behaviours during an eight month period using a portable training unit (PTU). Both EPG analysis and perceptual analysis showed an improvement in the production of /t/ and /s/ in words and sentences after therapy. Analysis of tongue-contact patterns showed that the participant had more normal articulatory patterns of /t/ and /s/ after just 2 months (after approximately 8 hours of training) respectively. No statistically significant transfer by means of intelligibility in connected speech was found. The present results show that EPG home training can be a sufficient method for treating persistent speech disorders associated with cleft palate. Methods for transfer from function (articulation) to activity (intelligibility) need to be explored.

Emotional Intelligence and Simulation.

PubMed

McKinley, Sophia K; Phitayakorn, Roy

2015-08-01

Emotional intelligence (EI) is an established concept in the business literature with evidence that it is an important factor in determining career achievement. There is increasing interest in the role that EI has in medical training, but it is still a nascent field. This article reviews the EI literature most relevant to surgical training and proposes that simulation offers many benefits to the development of EI. Although there are many unanswered questions, it is expected that future research will demonstrate the effectiveness of using simulation to develop EI within surgery. Copyright © 2015 Elsevier Inc. All rights reserved.

Artificial Neural Networks and Instructional Technology.

ERIC Educational Resources Information Center

Carlson, Patricia A.

1991-01-01

Artificial neural networks (ANN), part of artificial intelligence, are discussed. Such networks are fed sample cases (training sets), learn how to recognize patterns in the sample data, and use this experience in handling new cases. Two cognitive roles for ANNs (intelligent filters and spreading, associative memories) are examined. Prototypes…

The Application of Artificial Intelligence to Human Resource Development. A Case Study in the Development of a Rule-Based Expert System for Performance Analysis and Development Planning.

ERIC Educational Resources Information Center

Hummel, Thomas J.; Robinson, Judith A.

In 1984, the University of Minnesota's College of Education and Wilson Learning Corporation created the Alliance for Learning to support a variety of research projects focused on developing new areas of knowledge about adult learning and new technologies for delivering training and education. This paper describes an Alliance project exploring the…

Pilot interaction with automated airborne decision making systems

NASA Technical Reports Server (NTRS)

Rouse, W. B.; Hammer, J. M.; Morris, N. M.; Knaeuper, A. E.; Brown, E. N.; Lewis, C. M.; Yoon, W. C.

1984-01-01

Two project areas were pursued: the intelligent cockpit and human problem solving. The first area involves an investigation of the use of advanced software engineering methods to aid aircraft crews in procedure selection and execution. The second area is focused on human problem solving in dynamic environments, particulary in terms of identification of rule-based models land alternative approaches to training and aiding. Progress in each area is discussed.

The Department of Homeland Security Intelligence Enterprise: Operational Overview and Oversight Challenges for Congress

DTIC Science & Technology

2010-03-19

network architecture to connect various DHS elements and promote information sharing.17 • Establish a DHS State, Local, and Regional Fusion Center...of reports; the I&A Strategic Plan; training, and the implementation of a comprehensive information systems architecture .73 As part of its...comprehensive information technology network architecture was submitted to Congress last year. See DHS I&A, Homeland Security Information Technology Network

Detection of nicotine content impact in tobacco manufacturing using computational intelligence.

PubMed

Begic Fazlic, Lejla; Avdagic, Zikrija

2011-01-01

A study is presented for the detection of nicotine impact in different cigarette type, using recorded data and Computational Intelligence techniques. Recorded puffs are processed using Continuous Wavelet Transform and used to extract time-frequency features for normal and abnormal puffs conditions. The wavelet energy distributions are used as inputs to classifiers based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Genetic Algorithms (GAs). The number and the parameters of Membership Functions are used in ANFIS along with the features from wavelet energy distributionare selected using GAs, maximising the diagnosis success. GA with ANFIS (GANFIS) are trained with a subset of data with known nicotine conditions. The trained GANFIS are tested using the other set of data (testing data). A classical method by High-Performance Liquid Chromatography is also introduced to solve this problem, respectively. The results as well as the performances of these two approaches are compared. A combination of these two algorithms is also suggested to improve the efficiency of this solution procedure. Computational results show that this combined algorithm is promising.

Narrative Balance Management in an Intelligent Biosafety Training Application for Improving User Performance

ERIC Educational Resources Information Center

Alvarez, Nahum; Sanchez-Ruiz, Antonio; Cavazza, Marc; Shigematsu, Mika; Prendinger, Helmut

2015-01-01

The use of three-dimensional virtual environments in training applications supports the simulation of complex scenarios and realistic object behaviour. While these environments have the potential to provide an advanced training experience to students, it is difficult to design and manage a training session in real time due to the number of…

No Evidence of Intelligence Improvement after Working Memory Training: A Randomized, Placebo-Controlled Study

ERIC Educational Resources Information Center

Redick, Thomas S.; Shipstead, Zach; Harrison, Tyler L.; Hicks, Kenny L.; Fried, David E.; Hambrick, David Z.; Kane, Michael J.; Engle, Randall W.

2013-01-01

Numerous recent studies seem to provide evidence for the general intellectual benefits of working memory training. In reviews of the training literature, Shipstead, Redick, and Engle (2010, 2012) argued that the field should treat recent results with a critical eye. Many published working memory training studies suffer from design limitations…

How to Teach Emotional Intelligence Skills in IT Project Management

ERIC Educational Resources Information Center

Connolly, Amy J.; Reinicke, Bryan

2017-01-01

High emotional intelligence ("EQ") is considered one of the greatest strengths of an alpha project manager, yet undergraduate project management students are not directly trained in EQ soft skills such as communication, politics and teamwork. This article describes examples of active learning exercises implemented in an undergraduate IT…

Successful Graduate Students: The Roles of Personality Traits and Emotional Intelligence

ERIC Educational Resources Information Center

Grehan, Patrick M.; Flanagan, Rosemary; Malgady, Robert G.

2011-01-01

Given the complex role of school psychologists, it is in the interest of stakeholders to identify characteristics related to student success in graduate training, which is suggestive of their effectiveness as practitioners. This study explores the relationship of personality traits and Emotional Intelligence (EI) to graduate students' performance…

Associations of Early Developmental Milestones with Adult Intelligence

ERIC Educational Resources Information Center

Flensborg-Madsen, Trine; Mortensen, Erik L.

2018-01-01

The study investigated whether age at attainment of 20 developmental milestones within the areas of language, walking, eating, dressing, social interaction, and toilet training was associated with adult intelligence. Mothers of 821 children of the Copenhagen Perinatal Cohort recorded 20 developmental milestones at a 3-year examination, and all…

Emotional Intelligence and Medical Professionalism

ERIC Educational Resources Information Center

Zayapragassarazan, Z.; Kumar, Santosh

2011-01-01

Studies have shown that IQ alone does not contribute to the professional success of medical professionals. Professionals who are trained to be clinically competent, but have inadequate social skills for practice have proved to be less successful in their profession. Emotional intelligence (EI), which has already proved to be a key attribute for…

Reel Leadership II: Getting Emotional at the Movies

ERIC Educational Resources Information Center

Graham, T. Scott; Ackermann, J. Cooper; Maxwell, Kristi K.

2004-01-01

Emotional intelligence (EI) is emerging as an area of interest in leadership development. Recent research stresses how valuable strong EI skills are to the success of the person, team, organization, and society. Unlike IQ, emotional intelligence skills can be improved with focused training, coaching, and lifespan experiences. Effectively used,…

Techniques for Improving Pilot Recovery from System Failures

NASA Technical Reports Server (NTRS)

Pritchett, Amy R.

2001-01-01

This project examined the application of intelligent cockpit systems to aid air transport pilots at the tasks of reacting to in-flight system failures and of planning and then following a safe four dimensional trajectory to the runway threshold during emergencies. Two studies were conducted. The first examined pilot performance with a prototype awareness/alerting system in reacting to on-board system failures. In a full-motion, high-fidelity simulator, Army helicopter pilots were asked to fly a mission during which, without warning or briefing, 14 different failures were triggered at random times. Results suggest that the amount of information pilots require from such diagnostic systems is strongly dependent on their training; for failures they are commonly trained to react to with a procedural response, they needed only an indication of which failure to follow, while for 'un-trained' failures, they benefited from more intelligent and informative systems. Pilots were also found to over-rely on the system in conditions were it provided false or mis-leading information. In the second study, a proof-of-concept system was designed suitable for helping pilots replan their flights in emergency situations for quick, safe trajectory generation. This system is described in this report, including: the use of embedded fast-time simulation to predict the trajectory defined by a series of discrete actions; the models of aircraft and pilot dynamics required by the system; and the pilot interface. Then, results of a flight simulator evaluation with airline pilots are detailed. In 6 of 72 simulator runs, pilots were not able to establish a stable flight path on localizer and glideslope, suggesting a need for cockpit aids. However, results also suggest that, to be operationally feasible, such an aid must be capable of suggesting safe trajectories to the pilot; an aid that only verified plans entered by the pilot was found to have significantly detrimental effects on performance and pilot workload. Results also highlight that the trajectories suggested by the aid must capture the context of the emergency; for example, in some emergencies pilots were willing to violate flight envelope limits to reduce time in flight - in other emergencies the opposite was found.

Development and evaluation of a hand tracker using depth images captured from an overhead perspective.

PubMed

Czarnuch, Stephen; Mihailidis, Alex

2015-03-27

We present the development and evaluation of a robust hand tracker based on single overhead depth images for use in the COACH, an assistive technology for people with dementia. The new hand tracker was designed to overcome limitations experienced by the COACH in previous clinical trials. We train a random decision forest classifier using ∼5000 manually labeled, unbalanced, training images. Hand positions from the classifier are translated into task actions based on proximity to environmental objects. Tracker performance is evaluated using a large set of ∼24 000 manually labeled images captured from 41 participants in a fully-functional washroom, and compared to the system's previous colour-based hand tracker. Precision and recall were 0.994 and 0.938 for the depth tracker compared to 0.981 and 0.822 for the colour tracker with the current data, and 0.989 and 0.466 in the previous study. The improved tracking performance supports integration of the depth-based tracker into the COACH toward unsupervised, real-world trials. Implications for Rehabilitation The COACH is an intelligent assistive technology that can enable people with cognitive disabilities to stay at home longer, supporting the concept of aging-in-place. Automated prompting systems, a type of intelligent assistive technology, can help to support the independent completion of activities of daily living, increasing the independence of people with cognitive disabilities while reducing the burden of care experienced by caregivers. Robust motion tracking using depth imaging supports the development of intelligent assistive technologies like the COACH. Robust motion tracking also has application to other forms of assistive technologies including gaming, human-computer interaction and automated assessments.

Intelligent Automatic Right-Left Sign Lamp Based on Brain Signal Recognition System

NASA Astrophysics Data System (ADS)

Winda, A.; Sofyan; Sthevany; Vincent, R. S.

2017-12-01

Comfort as a part of the human factor, plays important roles in nowadays advanced automotive technology. Many of the current technologies go in the direction of automotive driver assistance features. However, many of the driver assistance features still require physical movement by human to enable the features. In this work, the proposed method is used in order to make certain feature to be functioning without any physical movement, instead human just need to think about it in their mind. In this work, brain signal is recorded and processed in order to be used as input to the recognition system. Right-Left sign lamp based on the brain signal recognition system can potentially replace the button or switch of the specific device in order to make the lamp work. The system then will decide whether the signal is ‘Right’ or ‘Left’. The decision of the Right-Left side of brain signal recognition will be sent to a processing board in order to activate the automotive relay, which will be used to activate the sign lamp. Furthermore, the intelligent system approach is used to develop authorized model based on the brain signal. Particularly Support Vector Machines (SVMs)-based classification system is used in the proposed system to recognize the Left-Right of the brain signal. Experimental results confirm the effectiveness of the proposed intelligent Automatic brain signal-based Right-Left sign lamp access control system. The signal is processed by Linear Prediction Coefficient (LPC) and Support Vector Machines (SVMs), and the resulting experiment shows the training and testing accuracy of 100% and 80%, respectively.

Artificial Intelligence: An Analysis of Potential Applications to Training, Performance Measurement, and Job Performance Aiding.

DTIC Science & Technology

1983-09-01

AD-Ali33 592 ARTIFICIAL INTELLIGENCE: AN ANALYSIS OF POTENTIAL 1/1 APPLICATIONS TO TRAININ..(U) DENVER RESEARCH INST CO JRICHARDSON SEP 83 AFHRL-TP...83-28 b ’ 3 - 4. TITLE (aied Suhkie) 5. TYPE OF REPORT & PERIOD COVERED ARTIFICIAL INTEL11GENCE: AN ANALYSIS OF Interim POTENTIAL APPLICATIONS TO...8217 sde if neceseamy end ides*f by black naumber) artificial intelligence military research * computer-aided diagnosis performance tests computer

Does Wechsler Intelligence Scale administration and scoring proficiency improve during assessment training?

PubMed

Platt, Tyson L; Zachar, Peter; Ray, Glen E; Lobello, Steven G; Underhill, Andrea T

2007-04-01

Studies have found that Wechsler scale administration and scoring proficiency is not easily attained during graduate training. These findings may be related to methodological issues. Using a single-group repeated measures design, this study documents statistically significant, though modest, error reduction on the WAIS-III and WISC-III during a graduate course in assessment. The study design does not permit the isolation of training factors related to error reduction, or assessment of whether error reduction is a function of mere practice. However, the results do indicate that previous study findings of no or inconsistent improvement in scoring proficiency may have been the result of methodological factors. Implications for teaching individual intelligence testing and further research are discussed.

Can Interactive Working Memory Training Improve Learning?

ERIC Educational Resources Information Center

Alloway, Tracy

2012-01-01

Background: Working memory is linked to learning outcomes and there is emerging evidence that training working memory can yield gains in working memory and fluid intelligence. Aims: The aim of the present study was to investigate whether interactive working memory training would transfer to acquired cognitive skills, such as vocabulary and…

Adaptive Technologies for Training and Education

ERIC Educational Resources Information Center

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

2012-01-01

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

The Application of Artificial Intelligence Principles to Teaching and Training

ERIC Educational Resources Information Center

Shaw, Keith

2008-01-01

This paper compares and contrasts the use of AI principles in industrial training with more normal computer-based training (CBT) approaches. A number of applications of CBT are illustrated (for example simulations, tutorial presentations, fault diagnosis, management games, industrial relations exercises) and compared with an alternative approach…

Intelligent Motion and Interaction Within Virtual Environments

NASA Technical Reports Server (NTRS)

Ellis, Stephen R. (Editor); Slater, Mel (Editor); Alexander, Thomas (Editor)

2007-01-01

What makes virtual actors and objects in virtual environments seem real? How can the illusion of their reality be supported? What sorts of training or user-interface applications benefit from realistic user-environment interactions? These are some of the central questions that designers of virtual environments face. To be sure simulation realism is not necessarily the major, or even a required goal, of a virtual environment intended to communicate specific information. But for some applications in entertainment, marketing, or aspects of vehicle simulation training, realism is essential. The following chapters will examine how a sense of truly interacting with dynamic, intelligent agents may arise in users of virtual environments. These chapters are based on presentations at the London conference on Intelligent Motion and Interaction within a Virtual Environments which was held at University College, London, U.K., 15-17 September 2003.

Artificial intelligence and signal processing for infrastructure assessment

NASA Astrophysics Data System (ADS)

Assaleh, Khaled; Shanableh, Tamer; Yehia, Sherif

2015-04-01

The Ground Penetrating Radar (GPR) is being recognized as an effective nondestructive evaluation technique to improve the inspection process. However, data interpretation and complexity of the results impose some limitations on the practicality of using this technique. This is mainly due to the need of a trained experienced person to interpret images obtained by the GPR system. In this paper, an algorithm to classify and assess the condition of infrastructures utilizing image processing and pattern recognition techniques is discussed. Features extracted form a dataset of images of defected and healthy slabs are used to train a computer vision based system while another dataset is used to evaluate the proposed algorithm. Initial results show that the proposed algorithm is able to detect the existence of defects with about 77% success rate.

Streamlining ICAT development through off-the shelf hypermedia systems

NASA Technical Reports Server (NTRS)

Orey, Michael; Trent, Ann; Young, James; Sanders, Michael

1993-01-01

This project examined the efficacy of building intelligent computer assisted training using an off-the-shelf hypermedia package. In addition, we compared this package to an architecture that had been developed in a previous contract which was based in the C programming language. One person developed a tutor in LinkWay (an off-the-shelf hypermedia system) and another developed the same tutor using the ALM C-based architecture. Development times, ease of use, learner preferences, learner options, and learning effectiveness were compared. In all cases, the off-the-shelf package was shown to be superior to the C-based system.

What is Essential for Virtual Reality Systems to Meet Human Performance Goals? (les Caracteristiques essentielles des systemes VR pour atteindre les objectifs militaires en matiere de performances humaines)

DTIC Science & Technology

2001-03-01

term research efforts to focus on natural interfaces ( innovative metaphors) and on how to model (intelligent) human and object behaviour. In the short...Kalawsky A Virtual Environment for Naval Flight Deck Operations Training 1 by V.S.S. Sastry, J. Steel and E.A. Trott Mission Debriefing System 2 by B.I...stricom.army.mil Email: trond.myhrer@ffi.no continued overleaf ix Antonio GRAMAGE MCS Jean- Paul PAPIN ISDEFE 7, rue Roger Edison, 4 92140 CLAMART 28006 Madrid

Enhancing Leadership and Governance Competencies to Strengthen Health Systems in Nigeria: Assessment of Organizational Human Resources Development

PubMed Central

Uneke, Chigozie J.; Ezeoha, Abel E.; Ndukwe, Chinwendu D.; Oyibo, Patrick G.; Onwe, Fri Day

2012-01-01

The lack of effective leadership and governance in the health sector has remained a major challenge in Nigeria and contributes to the failure of health systems and poor development of human resources. In this cross-sectional intervention study, leadership and governance competencies of policy makers were enhanced through a training workshop, and an assessment was conducted of organizational activities designed to promote evidence-informed leadership and governance to improve human resources for health (HRH). The training workshop increased the understanding of policy makers with regard to leadership and governance factors that ensure the functionality of health systems and improve human resources development, including policy guidance, intelligence and oversight, collaboration and coalition building, regulation, system design and accountability. Findings indicated that systems for human resources development exist in all participants' organizations, but the functionality of these systems was suboptimal. More systematic and standardized processes are required to improve competencies of leadership and governance for better human resources development in low-income settings. PMID:23372582

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2014 CFR

2014-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2013 CFR

2013-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2012 CFR

2012-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2011 CFR

2011-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

28 CFR 23.40 - Monitoring and auditing of grants for the funding of intelligence systems.

Code of Federal Regulations, 2010 CFR

2010-07-01

... funding of intelligence systems. 23.40 Section 23.40 Judicial Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.40 Monitoring and auditing of grants for the funding of intelligence systems. (a) Awards for the funding of intelligence systems will receive specialized...

Study of Emotional Intelligence Patterns with Teachers Working in Public Education

ERIC Educational Resources Information Center

Balázs, László

2015-01-01

The data necessary for the empirical research presented it this study were provided by 572 people, from altogether 26 schools. The schools included 18 primary schools, 7 secondary training institutions and 1 primary and secondary school. The major question of the study related to the pedagogues' emotional intelligence, more precisely if the…

Using an Intelligent Tutor and Math Fluency Training to Improve Math Performance

ERIC Educational Resources Information Center

Arroyo, Ivon; Royer, James M.; Woolf, Beverly P.

2011-01-01

This article integrates research in intelligent tutors with psychology studies of memory and math fluency (the speed to retrieve or calculate answers to basic math operations). It describes the impact of computer software designed to improve either strategic behavior or math fluency. Both competencies are key to improved performance and both…

Predictive Factors in Conflict: Assessing the Likelihood of a Preemptive Strike by Israel on Iran Using a Computer Model

DTIC Science & Technology

2013-03-01

Proliferation Treaty OSINT Open Source Intelligence SAFF Safing, Arming, Fuzing, Firing SIAM Situational Influence Assessment Module SME Subject...expertise. One of the analysts can also be trained to tweak CAST logic as needed. In this initial build, only open-source intelligence ( OSINT ) will

Predictors of Effective Leadership in Industry--Should Engineering Education Focus on Traditional Intelligence, Personality, or Emotional Intelligence?

ERIC Educational Resources Information Center

Lappalainen, Pia

2015-01-01

Despite the changing global and industrial conditions requiring new approaches to leadership, management training as part of higher engineering education still remains understudied. The subsequent gap in engineering education calls for research on today's leader requirements and pedagogy supporting the inclusion of management competence in higher…

Honing Emotional Intelligence with Game-Based Crucible Experiences

ERIC Educational Resources Information Center

Raybourn, Elaine M.

2011-01-01

The focus of the present paper is the design of multi-player role-playing game instances as crucible experiences for the exploration of one's emotional intelligence. Subsequent sections describe the design of game-based, intercultural crucible experiences and how this design was employed for training with members of the United States Marine Corps…

Assessing the applied benefits of perceptual training: Lessons from studies of training working-memory.

PubMed

Jacoby, Nori; Ahissar, Merav

2015-01-01

In the 1980s to 1990s, studies of perceptual learning focused on the specificity of training to basic visual attributes such as retinal position and orientation. These studies were considered scientifically innovative since they suggested the existence of plasticity in the early stimulus-specific sensory cortex. Twenty years later, perceptual training has gradually shifted to potential applications, and research tends to be devoted to showing transfer. In this paper we analyze two key methodological issues related to the interpretation of transfer. The first has to do with the absence of a control group or the sole use of a test-retest group in traditional perceptual training studies. The second deals with claims of transfer based on the correlation between improvement on the trained and transfer tasks. We analyze examples from the general intelligence literature dealing with the impact on general intelligence of training on a working memory task. The re-analyses show that the reports of a significantly larger transfer of the trained group over the test-retest group fail to replicate when transfer is compared to an actively trained group. Furthermore, the correlations reported in this literature between gains on the trained and transfer tasks can be replicated even when no transfer is assumed.

Intelligibility of clear speech: effect of instruction.

PubMed

Lam, Jennifer; Tjaden, Kris

2013-10-01

The authors investigated how clear speech instructions influence sentence intelligibility. Twelve speakers produced sentences in habitual, clear, hearing impaired, and overenunciate conditions. Stimuli were amplitude normalized and mixed with multitalker babble for orthographic transcription by 40 listeners. The main analysis investigated percentage-correct intelligibility scores as a function of the 4 conditions and speaker sex. Additional analyses included listener response variability, individual speaker trends, and an alternate intelligibility measure: proportion of content words correct. Relative to the habitual condition, the overenunciate condition was associated with the greatest intelligibility benefit, followed by the hearing impaired and clear conditions. Ten speakers followed this trend. The results indicated different patterns of clear speech benefit for male and female speakers. Greater listener variability was observed for speakers with inherently low habitual intelligibility compared to speakers with inherently high habitual intelligibility. Stable proportions of content words were observed across conditions. Clear speech instructions affected the magnitude of the intelligibility benefit. The instruction to overenunciate may be most effective in clear speech training programs. The findings may help explain the range of clear speech intelligibility benefit previously reported. Listener variability analyses suggested the importance of obtaining multiple listener judgments of intelligibility, especially for speakers with inherently low habitual intelligibility.

Perceptual Learning of Interrupted Speech

PubMed Central

Benard, Michel Ruben; Başkent, Deniz

2013-01-01

The intelligibility of periodically interrupted speech improves once the silent gaps are filled with noise bursts. This improvement has been attributed to phonemic restoration, a top-down repair mechanism that helps intelligibility of degraded speech in daily life. Two hypotheses were investigated using perceptual learning of interrupted speech. If different cognitive processes played a role in restoring interrupted speech with and without filler noise, the two forms of speech would be learned at different rates and with different perceived mental effort. If the restoration benefit were an artificial outcome of using the ecologically invalid stimulus of speech with silent gaps, this benefit would diminish with training. Two groups of normal-hearing listeners were trained, one with interrupted sentences with the filler noise, and the other without. Feedback was provided with the auditory playback of the unprocessed and processed sentences, as well as the visual display of the sentence text. Training increased the overall performance significantly, however restoration benefit did not diminish. The increase in intelligibility and the decrease in perceived mental effort were relatively similar between the groups, implying similar cognitive mechanisms for the restoration of the two types of interruptions. Training effects were generalizable, as both groups improved their performance also with the other form of speech than that they were trained with, and retainable. Due to null results and relatively small number of participants (10 per group), further research is needed to more confidently draw conclusions. Nevertheless, training with interrupted speech seems to be effective, stimulating participants to more actively and efficiently use the top-down restoration. This finding further implies the potential of this training approach as a rehabilitative tool for hearing-impaired/elderly populations. PMID:23469266

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

A Relational Frame Training Intervention to Raise Intelligence Quotients: A Pilot Study

ERIC Educational Resources Information Center

Cassidy, Sarah; Roche, Bryan; Hayes, Steven C.

2011-01-01

The current research consisted of 2 studies designed to test the effectiveness of automated multiple-exemplar relational training in raising children's general intellectual skills. In Study 1, 4 participants were exposed to multiple exemplar training in stimulus equivalence and the relational frames of SAME, OPPOSITE, MORE THAN, and LESS THAN…

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

PubMed Central

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

2016-01-01

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

A comparison of text and technology based training tools to improve cognitive skills in older adults.

PubMed

Power, Kevin; Kirwan, Grainne; Palmer, Marion

2011-01-01

Research has indicated that use of cognitive skills training tools can produce positive benefits with older adults. However, little research has compared the efficacy of technology-based interventions and more traditional, text-based interventions which are also available. This study aimed to investigate cognitive skills improvements experienced by 40 older adults using cognitive skills training tools. A Solomon 4 group design was employed to determine which intervention demonstrated the greatest improvement. Participants were asked to use the interventions for 5-10 minutes per day, over a period of 60 days. Pre and post-tests consisted of measures of numerical ability, self-reported memory and intelligence. Following training, older adults indicated significant improvements on numerical ability and intelligence regardless of intervention type. No improvement in selfreported memory was observed. This research provides a critical appraisal of brain training tools and can help point the way for future improvements in the area. Brain training improvements could lead to improved quality of life, and perhaps, have financial and independent living ramifications for older adults.

Investigating the Improvement of Decoding Abilities and Working Memory in Children with Incremental or Entity Personal Conceptions of Intelligence: Two Case Reports

PubMed Central

Alesi, Marianna; Rappo, Gaetano; Pepi, Annamaria

2016-01-01

One of the most significant current discussions has led to the hypothesis that domain-specific training programs alone are not enough to improve reading achievement or working memory abilities. Incremental or Entity personal conceptions of intelligence may be assumed to be an important prognostic factor to overcome domain-specific deficits. Specifically, incremental students tend to be more oriented toward change and autonomy and are able to adopt more efficacious strategies. This study aims at examining the effect of personal conceptions of intelligence to strengthen the efficacy of a multidimensional intervention program in order to improve decoding abilities and working memory. Participants included two children (M age = 10 years) with developmental dyslexia and different conceptions of intelligence. The children were tested on a whole battery of reading and spelling tests commonly used in the assessment of reading disabilities in Italy. Afterwards, they were given a multimedia test to measure motivational factors such as conceptions of intelligence and achievement goals. The children took part in the T.I.R.D. Multimedia Training for the Rehabilitation of Dyslexia (Rappo and Pepi, 2010) reinforced by specific units to improve verbal working memory for 3 months. This training consisted of specific tasks to rehabilitate both visual and phonological strategies (sound blending, word segmentation, alliteration test and rhyme test, letter recognition, digraph recognition, trigraph recognition, and word recognition as samples of visual tasks) and verbal working memory (rapid words and non-words recognition). Posttest evaluations showed that the child holding the incremental theory of intelligence improved more than the child holding a static representation. On the whole this study highlights the importance of treatment programs in which both specificity of deficits and motivational factors are both taken into account. There is a need to plan multifaceted intervention programs based on a transverse approach, considering both cognitive and motivational factors. PMID:26779069

Applied Epidemiology and Public Health: Are We Training the Future Generations Appropriately?

PubMed Central

Brownson, Ross C.; Samet, Jonathan M.; Bensyl, Diana M.

2017-01-01

To extend the reach and relevance of epidemiology for public health practice, the science needs be broadened beyond etiologic research, to link more strongly with emerging technologies and to acknowledge key societal transformations. This new focus for epidemiology and its implications for epidemiologic training can be considered in the context of macro trends affecting society, including a greater focus on upstream causes of disease, shifting demographics, the Affordable Care Act and health care system reform, globalization, changing health communication environment, growing centrality of team and transdisciplinary science, emergence of translational sciences, greater focus on accountability, big data, informatics, high-throughput technologies (“omics”), privacy changes, and the evolving funding environment. This commentary describes existing approaches to and competencies for training in epidemiology, maps macro trends with competencies, highlights an example of competency-based education in the Epidemic Intelligence Service of Centers for Disease Control and Prevention, and suggests expanded and more dynamic training approaches. A re-examination of current approaches to epidemiologic training is needed. PMID:28038933

Applied epidemiology and public health: are we training the future generations appropriately?

PubMed

Brownson, Ross C; Samet, Jonathan M; Bensyl, Diana M

2017-02-01

To extend the reach and relevance of epidemiology for public health practice, the science needs be broadened beyond etiologic research, to link more strongly with emerging technologies and to acknowledge key societal transformations. This new focus for epidemiology and its implications for epidemiologic training can be considered in the context of macro trends affecting society, including a greater focus on upstream causes of disease, shifting demographics, the Affordable Care Act and health care system reform, globalization, changing health communication environment, growing centrality of team and transdisciplinary science, emergence of translational sciences, greater focus on accountability, big data, informatics, high-throughput technologies ("omics"), privacy changes, and the evolving funding environment. This commentary describes existing approaches to and competencies for training in epidemiology, maps macro trends with competencies, highlights an example of competency-based education in the Epidemic Intelligence Service of Centers for Disease Control and Prevention, and suggests expanded and more dynamic training approaches. A reexamination of current approaches to epidemiologic training is needed. Copyright © 2016 Elsevier Inc. All rights reserved.

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

Information for the user in design of intelligent systems

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Schreckenghost, Debra L.

1993-01-01

Recommendations are made for improving intelligent system reliability and usability based on the use of information requirements in system development. Information requirements define the task-relevant messages exchanged between the intelligent system and the user by means of the user interface medium. Thus, these requirements affect the design of both the intelligent system and its user interface. Many difficulties that users have in interacting with intelligent systems are caused by information problems. These information problems result from the following: (1) not providing the right information to support domain tasks; and (2) not recognizing that using an intelligent system introduces new user supervisory tasks that require new types of information. These problems are especially prevalent in intelligent systems used for real-time space operations, where data problems and unexpected situations are common. Information problems can be solved by deriving information requirements from a description of user tasks. Using information requirements embeds human-computer interaction design into intelligent system prototyping, resulting in intelligent systems that are more robust and easier to use.

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.

Warfighter decision making performance analysis as an investment priority driver

NASA Astrophysics Data System (ADS)

Thornley, David J.; Dean, David F.; Kirk, James C.

2010-04-01

Estimating the relative value of alternative tactics, techniques and procedures (TTP) and information systems requires measures of the costs and benefits of each, and methods for combining and comparing those measures. The NATO Code of Best Practice for Command and Control Assessment explains that decision making quality would ideally be best assessed on outcomes. Lessons learned in practice can be assessed statistically to support this, but experimentation with alternate measures in live conflict is undesirable. To this end, the development of practical experimentation to parameterize effective constructive simulation and analytic modelling for system utility prediction is desirable. The Land Battlespace Systems Department of Dstl has modeled human development of situational awareness to support constructive simulation by empirically discovering how evidence is weighed according to circumstance, personality, training and briefing. The human decision maker (DM) provides the backbone of the information processing activity associated with military engagements because of inherent uncertainty associated with combat operations. To develop methods for representing the process in order to assess equipment and non-technological interventions such as training and TTPs we are developing componentized or modularized timed analytic stochastic model components and instruments as part of a framework to support quantitative assessment of intelligence production and consumption methods in a human decision maker-centric mission space. In this paper, we formulate an abstraction of the human intelligence fusion process from the Defence Science and Technology Laboratory's (Dstl's) INCIDER model to include in our framework, and synthesize relevant cost and benefit characteristics.

Intelligent MRTD testing for thermal imaging system using ANN

NASA Astrophysics Data System (ADS)

Sun, Junyue; Ma, Dongmei

2006-01-01

The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task, for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type, the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP, but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly, we use frame grabber to capture the 4-bar target image data. Then according to image gray scale, we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets, along with known target visibility, are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm, demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.

Working memory training in healthy young adults: Support for the null from a randomized comparison to active and passive control groups.

PubMed

Clark, Cameron M; Lawlor-Savage, Linette; Goghari, Vina M

2017-01-01

Training of working memory as a method of increasing working memory capacity and fluid intelligence has received much attention in recent years. This burgeoning field remains highly controversial with empirically-backed disagreements at all levels of evidence, including individual studies, systematic reviews, and even meta-analyses. The current study investigated the effect of a randomized six week online working memory intervention on untrained cognitive abilities in a community-recruited sample of healthy young adults, in relation to both a processing speed training active control condition, as well as a no-contact control condition. Results of traditional null hypothesis significance testing, as well as Bayesian factor analyses, revealed support for the null hypothesis across all cognitive tests administered before and after training. Importantly, all three groups were similar at pre-training for a variety of individual variables purported to moderate transfer of training to fluid intelligence, including personality traits, motivation to train, and expectations of cognitive improvement from training. Because these results are consistent with experimental trials of equal or greater methodological rigor, we suggest that future research re-focus on: 1) other promising interventions known to increase memory performance in healthy young adults, and; 2) examining sub-populations or alternative populations in which working memory training may be efficacious.

Development and Implementation of an End-Effector Upper Limb Rehabilitation Robot for Hemiplegic Patients with Line and Circle Tracking Training

PubMed Central

Li, Chong; Bi, Sheng; Zhang, Xuemin; Huo, Jianfei

2017-01-01

Numerous robots have been widely used to deliver rehabilitative training for hemiplegic patients to improve their functional ability. Because of the complexity and diversity of upper limb motion, customization of training patterns is one key factor during upper limb rehabilitation training. Most of the current rehabilitation robots cannot intelligently provide adaptive training parameters, and they have not been widely used in clinical rehabilitation. This article proposes a new end-effector upper limb rehabilitation robot, which is a two-link robotic arm with two active degrees of freedom. This work investigated the kinematics and dynamics of the robot system, the control system, and the realization of different rehabilitation therapies. We also explored the influence of constraint in rehabilitation therapies on interaction force and muscle activation. The deviation of the trajectory of the end effector and the required trajectory was less than 1 mm during the tasks, which demonstrated the movement accuracy of the robot. Besides, results also demonstrated the constraint exerted by the robot provided benefits for hemiplegic patients by changing muscle activation in the way similar to the movement pattern of the healthy subjects, which indicated that the robot can improve the patient's functional ability by training the normal movement pattern. PMID:29065614

Development and Implementation of an End-Effector Upper Limb Rehabilitation Robot for Hemiplegic Patients with Line and Circle Tracking Training.

PubMed

Liu, Yali; Li, Chong; Ji, Linhong; Bi, Sheng; Zhang, Xuemin; Huo, Jianfei; Ji, Run

2017-01-01

Numerous robots have been widely used to deliver rehabilitative training for hemiplegic patients to improve their functional ability. Because of the complexity and diversity of upper limb motion, customization of training patterns is one key factor during upper limb rehabilitation training. Most of the current rehabilitation robots cannot intelligently provide adaptive training parameters, and they have not been widely used in clinical rehabilitation. This article proposes a new end-effector upper limb rehabilitation robot, which is a two-link robotic arm with two active degrees of freedom. This work investigated the kinematics and dynamics of the robot system, the control system, and the realization of different rehabilitation therapies. We also explored the influence of constraint in rehabilitation therapies on interaction force and muscle activation. The deviation of the trajectory of the end effector and the required trajectory was less than 1 mm during the tasks, which demonstrated the movement accuracy of the robot. Besides, results also demonstrated the constraint exerted by the robot provided benefits for hemiplegic patients by changing muscle activation in the way similar to the movement pattern of the healthy subjects, which indicated that the robot can improve the patient's functional ability by training the normal movement pattern.

Research on Intelligent Interface in Double-front Work Machines

NASA Astrophysics Data System (ADS)

Kamezaki, Mitsuhiro; Iwata, Hiroyasu; Sugano, Shigeki

This paper proposes a work state identification method with full independent of work environmental conditions and operator skill levels for construction machinery. Advanced operated-work machines, which have been designed for complicated tasks, require intelligent systems that can provide the quantitative work analysis needed to determine effective work procedures and that can provide operational and cognitive support for operators. Construction work environments are extremely complicated, however, and this makes state identification, which is a key technology for an intelligent system, difficult. We therefore defined primitive static states (PSS) that are determined using on-off information for the lever inputs and manipulator loads for each part of the grapple and front and that are completely independent of the various environmental conditions and variation in operator skill level that can cause an incorrect work state identification. To confirm the usefulness of PSS, we performed experiments with a demolition task by using our virtual reality simulator. We confirmed that PSS could robustly and accurately identify the work states and that untrained skills could be easily inferred from the results of PSS-based work analysis. We also confirmed in skill-training experiments that advice information based on PSS-based skill analysis greatly improved operator's work performance. We thus confirmed that PSS can adequately identify work states and are useful for work analysis and skill improvement.

Proposal of an intelligent wayside monitoring system for detection of critical ice accumulations on railway vehicles

NASA Astrophysics Data System (ADS)

Michelberger, Frank; Wagner, Adrian; Ostermann, Michael; Maly, Thomas

2017-09-01

At railway lines with ballasted tracks, under unfavourable conditions, the so-called flying ballast can occur predominantly for trains driving at high speeds. Especially in wintertime, it is highly likely that the causes are adhered snow or ice deposits, which are falling off the vehicle. Due to the high kinetic energy, the impact can lead to the removal of ballast stones from the structure of the ballasted track. If the stones reach the height of vehicles underside, they may be accelerated significantly due to the collision with the vehicle or may detach further ice blocks. In the worst case, a reinforcing effect occurs, which can lead to considerable damage to railway vehicles (under-floor-area, vehicle exteriors, etc.) and infrastructure (signal masts, noise barriers, etc.). Additionally the flying gravel is a significant danger to people in the nearby area of the tracks. With this feasibility study the applicability and meaningfulness of an intelligent monitoring system for identification of the critical ice accumulation to prevent the ballast fly induced by ice dropping was examined. The key findings of the research are that the detection of ice on railway vehicles and the development of an intelligent monitoring seem to be possible with existing technologies, but a proof of concept in terms of field tests is necessary.

Tentative Guidelines for the Development of an Ability-Based Emotional Intelligence Intervention Program for Gifted Students

ERIC Educational Resources Information Center

Zeidner, Moshe

2017-01-01

This paper presents a number of general principles and guidelines for the development of an emotional intelligence training program designed to foster emotional abilities in gifted students. The presented guidelines underscore the need for EI theory-driven program planning geared to the needs of gifted students; integrating activities into routine…

Assessment of Emotional Intelligence in a Sample of Prospective Secondary Education Teachers

ERIC Educational Resources Information Center

Gutiérrez-Moret, Margarita; Ibáñez-Martinez, Raquel; Aguilar-Moya, Remedios; Vidal-Infer, Antonio

2016-01-01

In the past few years, skills related to emotional intelligence (EI) have acquired special relevance in the educational domain. This study assesses EI in a sample of 155 students of 5 different specialities of a Master's degree in Teacher Training for Secondary Education. Data collection was conducted through the administration of the Trait Meta…

Sensors control gas metal arc welding

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

Siewert, T.A.; Madigan, R.B.; Quinn, T.P.

1997-04-01

The response time of a trained welder from the time a weld problem is identified to the time action is taken is about one second--especially after a long, uneventful period of welding. This is acceptable for manual welding because it is close to the time it takes for the weld pool to solidify. If human response time were any slower, manual welding would not be possible. However, human response time is too slow to respond to some weld events, such as melting of the contact tube in gas metal arc welding (GMAW), and only automated intelligent control systems can reactmore » fast enough to correct or avoid these problems. Control systems incorporate welding knowledge that enables intelligent decisions to be made about weld quality and, ultimately, to keep welding parameters in the range where only high-quality welds are produced. This article discusses the correlation of electrical signals with contact-tube wear, changes in shielding gas, changes in arc length, and other weld process data.« less

Instruct: An Example of the Role of Artificial Intelligence in Voice-Based Training Systems.

DTIC Science & Technology

1983-01-01

Lockhart , R.S. Levels of processing : A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 1972, LT, pp. 6𔄁T-684. Ericsson...of covert student processing and knowledge levels from overt student behavior; and a curriculum driver that could use the student model to determine...concentration), then the task is said to be resource-limited. Whenever the performance level remains invariant to increased allocations of processing

Command, Control, Communications and Intelligence (C3I) Project Book: Fiscal Year 1992

DTIC Science & Technology

1992-05-12

PSC-3 is a rugged, lightweight (less than 35 lbs including batteries and whip and mdium gain antennas) portable device capable of being paged while...as Materiel Change (NC) projects. They Include: TACFWR Wpgade NC; Water Entry Resolution NC; FIREFIWER Training Device Upgrade MC; and Backplmn Wiringj... devices consist of a sensor . processor addigital display ibplWsd on an Individual air defense mopon system(FAM and NWWI). Two models are in development

Motion Controllers for Learners to Manipulate and Interact with 3D Objects for Mental Rotation Training

ERIC Educational Resources Information Center

Yeh, Shih-Ching; Wang, Jin-Liang; Wang, Chin-Yeh; Lin, Po-Han; Chen, Gwo-Dong; Rizzo, Albert

2014-01-01

Mental rotation is an important spatial processing ability and an important element in intelligence tests. However, the majority of past attempts at training mental rotation have used paper-and-pencil tests or digital images. This study proposes an innovative mental rotation training approach using magnetic motion controllers to allow learners to…

Do the Effects of Working Memory Training Depend on Baseline Ability Level?

ERIC Educational Resources Information Center

Foster, Jeffrey L.; Harrison, Tyler L.; Hicks, Kenny L.; Draheim, Christopher; Redick, Thomas S.; Engle, Randall W.

2017-01-01

There is a debate about the ability to improve cognitive abilities such as fluid intelligence through training on tasks of working memory capacity. The question addressed in the research presented here is who benefits the most from training: people with low cognitive ability or people with high cognitive ability? Subjects with high and low working…

Working Memory Training in Typically Developing Children: A Meta-Analysis of the Available Evidence

ERIC Educational Resources Information Center

Sala, Giovanni; Gobet, Fernand

2017-01-01

The putative effectiveness of working memory (WM) training at enhancing cognitive and academic skills is still ardently debated. Several researchers have claimed that WM training fosters not only skills such as visuospatial WM and short-term memory (STM), but also abilities outside the domain of WM, such as fluid intelligence and mathematics.…

The Role of Anticipation in Intelligent Systems

NASA Astrophysics Data System (ADS)

Klir, George J.

2002-09-01

The paper explores the relationship between the area of anticipatory systems and the area of intelligent systems. After an overview of these areas, the role of anticipation in intelligent systems is discussed and it is argued that the area of intelligent systems can greatly benefit by importing the various results developed within the area of anticipatory systems. Distinctions between hard and soft systems and between hard and soft computing are then discussed. It is explained why intelligent systems are by necessity soft and why soft computing is essential for their construction. It is finally argued that the area of anticipatory systems can enlarge its scope by importing knowledge regarding soft systems and soft computing from the area of intelligent systems.

Modeling of steam distillation mechanism during steam injection process using artificial intelligence.

PubMed

Daryasafar, Amin; Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods.

Modeling of Steam Distillation Mechanism during Steam Injection Process Using Artificial Intelligence

PubMed Central

Ahadi, Arash; Kharrat, Riyaz

2014-01-01

Steam distillation as one of the important mechanisms has a great role in oil recovery in thermal methods and so it is important to simulate this process experimentally and theoretically. In this work, the simulation of steam distillation is performed on sixteen sets of crude oil data found in the literature. Artificial intelligence (AI) tools such as artificial neural network (ANN) and also adaptive neurofuzzy interference system (ANFIS) are used in this study as effective methods to simulate the distillate recoveries of these sets of data. Thirteen sets of data were used to train the models and three sets were used to test the models. The developed models are highly compatible with respect to input oil properties and can predict the distillate yield with minimum entry. For showing the performance of the proposed models, simulation of steam distillation is also done using modified Peng-Robinson equation of state. Comparison between the calculated distillates by ANFIS and neural network models and also equation of state-based method indicates that the errors of the ANFIS model for training data and test data sets are lower than those of other methods. PMID:24883365

The Impact of Emotional Intelligence on Conditions of Trust among Leaders at the Kentucky Department for Public Health

PubMed Central

Knight, Jennifer Redmond; Bush, Heather M.; Mase, William A.; Riddell, Martha Cornwell; Liu, Meng; Holsinger, James W.

2015-01-01

There has been limited leadership research on emotional intelligence and trust in governmental public health settings. The purpose of this study was to identify and seek to understand the relationship between trust and elements of emotional intelligence, including stress management, at the Kentucky Department for Public Health (KDPH). The KDPH serves as Kentucky’s state governmental health department. KDPH is led by a Commissioner and composed of seven primary divisions and 25 branches within those divisions. The study was a non-randomized cross-sectional study utilizing electronic surveys that evaluated conditions of trust among staff members and emotional intelligence among supervisors. Pearson correlation coefficients and corresponding p-values are presented to provide the association between emotional intelligence scales and the conditions of trust. Significant positive correlations were observed between supervisors’ stress management and the staff members’ trust or perception of supervisors’ loyalty (r = 0.6, p = 0.01), integrity (r = 0.5, p = 0.03), receptivity (r = 0.6, p = 0.02), promise fulfillment (r = 0.6, p = 0.02), and availability (r = 0.5, p = 0.07). This research lays the foundation for emotional intelligence and trust research and leadership training in other governmental public health settings, such as local, other state, national, or international organizations. This original research provides metrics to assess the public health workforce with attention to organizational management and leadership constructs. The survey tools could be used in other governmental public health settings in order to develop tailored training opportunities related to emotional intelligence and trust organizations. PMID:25821778

An Emotional ANN (EANN) approach to modeling rainfall-runoff process

NASA Astrophysics Data System (ADS)

Nourani, Vahid

2017-01-01

This paper presents the first hydrological implementation of Emotional Artificial Neural Network (EANN), as a new generation of Artificial Intelligence-based models for daily rainfall-runoff (r-r) modeling of the watersheds. Inspired by neurophysiological form of brain, in addition to conventional weights and bias, an EANN includes simulated emotional parameters aimed at improving the network learning process. EANN trained by a modified version of back-propagation (BP) algorithm was applied to single and multi-step-ahead runoff forecasting of two watersheds with two distinct climatic conditions. Also to evaluate the ability of EANN trained by smaller training data set, three data division strategies with different number of training samples were considered for the training purpose. The overall comparison of the obtained results of the r-r modeling indicates that the EANN could outperform the conventional feed forward neural network (FFNN) model up to 13% and 34% in terms of training and verification efficiency criteria, respectively. The superiority of EANN over classic ANN is due to its ability to recognize and distinguish dry (rainless days) and wet (rainy days) situations using hormonal parameters of the artificial emotional system.

Cultivating Mind Fitness through Mindfulness Training: Applied Neuroscience

ERIC Educational Resources Information Center

Heydenfeldt, Jo Ann; Herkenhoff, Linda; Coe, Mary

2011-01-01

Mindfulness reduces distress, promotes optimal health, improves attentional control, mental agility, emotional intelligence, and situational awareness. Stress management and cognitive performance in Marines who spent more hours practicing Mindfulness Based Mind Fitness Training were superior to those soldiers who practiced fewer hours. Students…

77 FR 51845 - Intelligent Transportation Systems Program Advisory Committee; Notice of Meeting

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-27

... DEPARTMENT OF TRANSPORTATION Intelligent Transportation Systems Program Advisory Committee; Notice.... Department of Transportation. ACTION: Notice. The Intelligent Transportation Systems (ITS) Program Advisory..., development, and implementation of intelligent transportation systems. Through its sponsor, the ITS Joint...

The effects of emotional intelligence training on the job performance of Australian aged care workers.

PubMed

Karimi, Leila; Leggat, Sandra G; Bartram, Timothy; Rada, Jiri

2018-05-09

Emotional intelligence (EI) training is popular among human resource practitioners, but there is limited evidence of the impact of such training on health care workers. In the current article, we examine the effects of EI training on quality of resident care and worker well-being and psychological empowerment in an Australian aged care facility. We use Bar-On's (1997) conceptualization of EI. We used a quasiexperimental design in 2014-2015 with experimental (training) and control (nontraining) groups of 60 participants in each group in two geographically separate facilities. Our final poststudy sample size was 27 participants for the training group and 17 participants for the control group. Over a 6-month period, we examined whether staff improved their well-being, psychological empowerment, and job performance measured as enhanced quality of care (self-rated and client-rated) by applying skills in EI. The results showed significant improvement among workers in the training group for EI scores, quality of care, general well-being, and psychological empowerment. There were no significant differences for the control group. Through examining the impact of EI training on staff and residents of an aged care facility, we demonstrate the benefits of EI training for higher quality of care delivery. This study demonstrates the practical process through which EI training can improve the work experiences of aged care workers, as well as the quality of care for residents.

Blowout Monitor

NASA Technical Reports Server (NTRS)

1994-01-01

C Language Integrated Production System (CLIPS), a NASA-developed software shell for developing expert systems, has been embedded in a PC-based expert system for training oil rig personnel in monitoring oil drilling. Oil drilling rigs if not properly maintained for possible blowouts pose hazards to human life, property and the environment may be destroyed. CLIPS is designed to permit the delivery of artificial intelligence on computer. A collection of rules is set up and, as facts become known, these rules are applied. In the Well Site Advisor, CLIPS provides the capability to accurately process, predict and interpret well data in a real time mode. CLIPS was provided to INTEQ by COSMIC.

Methodology for automating software systems

NASA Technical Reports Server (NTRS)

Moseley, Warren

1990-01-01

Applying ITS technology to the shuttle diagnostics would not require the rigor of the Petri Net representation, however it is important in providing the animated simulated portion of the interface and the demands placed on the system to support the training aspects to have a homogeneous and consistent underlying knowledge representation. By keeping the diagnostic rule base, the hardware description, the software description, user profiles, desired behavioral knowledge, and the user interface in the same notation, it is possible to reason about the all of the properties of petri nets, on any selected portion of the simulation. This reasoning provides foundation for utilization of intelligent tutoring systems technology.

28 CFR 23.3 - Applicability.

Code of Federal Regulations, 2011 CFR

2011-07-01

... Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.3 Applicability. (a) These policy standards are applicable to all criminal intelligence systems operating through support...-647). (b) As used in these policies: (1) Criminal Intelligence System or Intelligence System means the...

28 CFR 23.3 - Applicability.

Code of Federal Regulations, 2014 CFR

2014-07-01

... Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.3 Applicability. (a) These policy standards are applicable to all criminal intelligence systems operating through support...-647). (b) As used in these policies: (1) Criminal Intelligence System or Intelligence System means the...

28 CFR 23.3 - Applicability.

Code of Federal Regulations, 2012 CFR

2012-07-01

... Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.3 Applicability. (a) These policy standards are applicable to all criminal intelligence systems operating through support...-647). (b) As used in these policies: (1) Criminal Intelligence System or Intelligence System means the...

28 CFR 23.3 - Applicability.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.3 Applicability. (a) These policy standards are applicable to all criminal intelligence systems operating through support...-647). (b) As used in these policies: (1) Criminal Intelligence System or Intelligence System means the...

28 CFR 23.3 - Applicability.

Code of Federal Regulations, 2013 CFR

2013-07-01

... Administration DEPARTMENT OF JUSTICE CRIMINAL INTELLIGENCE SYSTEMS OPERATING POLICIES § 23.3 Applicability. (a) These policy standards are applicable to all criminal intelligence systems operating through support...-647). (b) As used in these policies: (1) Criminal Intelligence System or Intelligence System means the...

The relationship of certified flight instructors' emotional intelligence levels on flight student advancement

NASA Astrophysics Data System (ADS)

Hokeness, Mark Merrill

Aviation researchers estimate airline companies will require nearly 500,000 pilots in the next 20 years. The role of a Certified Flight Instructor (CFI) is to move student pilots to professional pilots with training typically conducted in one-on-one student and instructor sessions. The knowledge of aviation, professionalism as a teacher, and the CFI’s interpersonal skills can directly affect the successes and advancement of a student pilot. A new and emerging assessment of people skills is known as emotional intelligence (EI). The EI of the CFI can and will affect a flight students’ learning experiences. With knowledge of emotional intelligence and its effect on flight training, student pilot dropouts from aviation may be reduced, thus helping to ensure an adequate supply of pilots. Without pilots, the growth of the commercial aviation industry will be restricted. This mixed method research study established the correlation between a CFI’s measured EI levels and the advancement of flight students. The elements contributing to a CFI’s EI level were not found to be teaching or flight-related experiences, suggesting other life factors are drawn upon by the CFI and are reflected in their emotional intelligence levels presented to flight students. Students respond positively to CFIs with higher levels of emotional intelligence. Awareness of EI skills by both the CFI and flight student contribute to flight student successes and advancement.

Simulation-Based Cryosurgery Intelligent Tutoring System (ITS) Prototype

PubMed Central

Sehrawat, Anjali; Keelan, Robert; Shimada, Kenji; Wilfong, Dona M.; McCormick, James T.; Rabin, Yoed

2015-01-01

As a part of an ongoing effort to develop computerized training tools for cryosurgery, the current study presents a proof-of-concept for a computerized tool for cryosurgery tutoring. The tutoring system lists geometrical constraints of cryoprobes placement, simulates cryoprobe insertion, displays a rendered shape of the prostate, enables distance measurements, simulates the corresponding thermal history, and evaluates the mismatch between the target region shape and a pre-selected planning isotherm. The quality of trainee planning is measured in comparison with a computer-generated planning, created for each case study by previously developed planning algorithms. Two versions of the tutoring system have been tested in the current study: (i) an unguided version, where the trainee can practice cases in unstructured sessions, and (ii) an intelligent tutoring system (ITS), which forces the trainee to follow specific steps, believed by the authors to potentially shorten the learning curve. While the tutoring level in this study aims only at geometrical constraints on cryoprobe placement and the resulting thermal histories, it creates a unique opportunity to gain insight into the process outside of the operation room. Posttest results indicate that the ITS system maybe more beneficial than the non-ITS system, but the proof-of-concept is demonstrated with either system. PMID:25941163

Measuring Learning Potential: An Alternative to the Traditional Intelligence Test. Studies in Learning Potential, Volume 3, Number 39.

ERIC Educational Resources Information Center

Budoff, Milton

Proposed is the assessment of learning potential through a test-train-retest paradigm in addition to the traditional intelligence test with mentally handicapped or disadvantaged children. Discussed is a rationale for the approach which posits that poor and/or nonwhite children do not have equal access to school-preparatory experiences though they…

Social and Emotional Dynamics of College Students with Musical Intelligence and Musical Training: A Multiple Case Study

ERIC Educational Resources Information Center

Pelayo, Jose Maria G., III; Galang, Edgar

2013-01-01

Music has been in its formal existence for so many years now and it has also been utilized to enhance, relax and help man's meditation. This study focused on how music can or may influence an individual. The researchers investigated and described the influence of Howard Gardner's theory on Multiple Intelligence (specifically, musical…