WorldWideScience

Sample records for intelligence techniques developed

  1. Artificial Intelligence Techniques: Applications for Courseware Development.

    Science.gov (United States)

    Dear, Brian L.

    1986-01-01

    Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

  2. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  3. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    Energy Technology Data Exchange (ETDEWEB)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W. [Chosun University, Gwangju (Korea, Republic of); Ahn, K. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2010-06-15

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  4. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    International Nuclear Information System (INIS)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W.; Ahn, K. I.

    2010-06-01

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  5. Using Game Theory Techniques and Concepts to Develop Proprietary Models for Use in Intelligent Games

    Science.gov (United States)

    Christopher, Timothy Van

    2011-01-01

    This work is about analyzing games as models of systems. The goal is to understand the techniques that have been used by game designers in the past, and to compare them to the study of mathematical game theory. Through the study of a system or concept a model often emerges that can effectively educate students about making intelligent decisions…

  6. DEVELOPMENT OF A VIRTUAL INTELLIGENCE TECHNIQUE FOR THE UPSTREAM OIL INDUSTRY

    Energy Technology Data Exchange (ETDEWEB)

    Iraj A. Salehi; Shahab D. Mohaghegh; Samuel Ameri

    2004-09-01

    The objective of the research and development work reported in this document was to develop a Virtual Intelligence Technique for optimization of the Preferred Upstream Management Practices (PUMP) for the upstream oil industry. The work included the development of a software tool for identification and optimization of the most influential parameters in upstream common practices as well as geological, geophysical and reservoir engineering studies. The work was performed in cooperation with three independent producing companies--Newfield Exploration, Chesapeake Energy, and Triad Energy--operating in the Golden Trend, Oklahoma. In order to protect data confidentiality, these companies are referred to as Company One, Two, Three in a randomly selected order. These producing companies provided geological, completion, and production data on 320 wells and participated in frequent technical discussions throughout the project. Research and development work was performed by Gas Technology Institute (GTI), West Virginia University (WVU), and Intelligent Solutions Inc. (ISI). Oklahoma Independent Petroleum Association (OIPA) participated in technology transfer and data acquisition efforts. Deliverables from the project are the present final report and a user-friendly software package (Appendix D) with two distinct functions: a characterization tool that identifies the most influential parameters in the upstream operations, and an optimization tool that seeks optimization by varying a number of influential parameters and investigating the coupled effects of these variations. The electronic version of this report is also included in Appendix D. The Golden Trend data were used for the first cut optimization of completion procedures. In the subsequent step, results from soft computing runs were used as the guide for detailed geophysical and reservoir engineering studies that characterize the cause-and-effect relationships between various parameters. The general workflow and the main

  7. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  8. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  9. Computational intelligence techniques in health care

    CERN Document Server

    Zhou, Wengang; Satheesh, P

    2016-01-01

    This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

  10. Development and Experimental Evaluation of Machine-Learning Techniques for an Intelligent Hairy Scalp Detection System

    Directory of Open Access Journals (Sweden)

    Wei-Chien Wang

    2018-05-01

    Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.

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

    Science.gov (United States)

    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 (pdiagnosis. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  12. Computational Intelligence Techniques for New Product Design

    CERN Document Server

    Chan, Kit Yan; Dillon, Tharam S

    2012-01-01

    Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the com...

  13. Operator support system using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bueno, Elaine Inacio, E-mail: ebueno@ifsp.edu.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2015-07-01

    Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

  14. Operator support system using computational intelligence techniques

    International Nuclear Information System (INIS)

    Bueno, Elaine Inacio; Pereira, Iraci Martinez

    2015-01-01

    Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

  15. THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Mary Violeta Bar

    2014-01-01

    The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

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

    Science.gov (United States)

    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

  17. Intelligent techniques in engineering management theory and applications

    CERN Document Server

    Onar, Sezi

    2015-01-01

    This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

  18. Development of Semi-Automatic Lathe by using Intelligent Soft Computing Technique

    Science.gov (United States)

    Sakthi, S.; Niresh, J.; Vignesh, K.; Anand Raj, G.

    2018-03-01

    This paper discusses the enhancement of conventional lathe machine to semi-automated lathe machine by implementing a soft computing method. In the present scenario, lathe machine plays a vital role in the engineering division of manufacturing industry. While the manual lathe machines are economical, the accuracy and efficiency are not up to the mark. On the other hand, CNC machine provide the desired accuracy and efficiency, but requires a huge capital. In order to over come this situation, a semi-automated approach towards the conventional lathe machine is developed by employing stepper motors to the horizontal and vertical drive, that can be controlled by Arduino UNO -microcontroller. Based on the input parameters of the lathe operation the arduino coding is been generated and transferred to the UNO board. Thus upgrading from manual to semi-automatic lathe machines can significantly increase the accuracy and efficiency while, at the same time, keeping a check on investment cost and consequently provide a much needed escalation to the manufacturing industry.

  19. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs

  20. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  1. Artificial Intelligence techniques for big data analysis

    OpenAIRE

    Aditya Khatri

    2017-01-01

    During my stay in Salamanca (Spain), I was fortunate enough to participate in the BISITE Research Group of the University of Salamanca. The University of Salamanca is the oldest university in Spain and in 2018 it celebrates its 8th centenary. As a computer science researcher, I participated in one of the many international projects that the research group has active, especially in big data analysis using Artificial Intelligence (AI) techniques. AI is one of BISITE's main lines of rese...

  2. Express: the reliability of complex systems and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ancelin, C.; Le, P.; Saint-Quentin, S. de

    1987-01-01

    The probabilistic safety study for the Paluel nuclear power station, commissioned by EDF in 1986, involved development of data processing methods and equipment which was to be given an entirely new impetus by the use of artificial intelligence techniques. The authors describe the salient features of the approach which was adopted and the lessons learnt from the way it was applied in practice [fr

  3. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

    OpenAIRE

    Aarshay Jain; Deepansh Jagotra; Vijayant Agarwal

    2014-01-01

    The primary focus of this study is implementation of Artificial Intelligence (AI) technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN) techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind...

  4. A model for Business Intelligence Systems’ Development

    Directory of Open Access Journals (Sweden)

    Manole VELICANU

    2009-01-01

    Full Text Available Often, Business Intelligence Systems (BIS require historical data or data collected from var-ious sources. The solution is found in data warehouses, which are the main technology used to extract, transform, load and store data in the organizational Business Intelligence projects. The development cycle of a data warehouse involves lots of resources, time, high costs and above all, it is built only for some specific tasks. In this paper, we’ll present some of the aspects of the BI systems’ development such as: architecture, lifecycle, modeling techniques and finally, some evaluation criteria for the system’s performance.

  5. USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

    OpenAIRE

    KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA; Orhan ENGİN

    2005-01-01

    Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quali...

  6. Improving Energy Saving Techniques by Ambient Intelligence Scheduling

    DEFF Research Database (Denmark)

    Cristani, Matteo; Karafili, Erisa; Tomazzoli, Claudio

    2015-01-01

    Energy saving is one of the most challenging aspects of modern ambient intelligence technologies, for both domestic and business usages. In this paper we show how to combine Ambient Intelligence and Artificial Intelligence techniques to solve the problem of scheduling a set of devices under a given...... for Ambient Intelligence to a specific framework and exhibit a sample usage for a real life system, Elettra, that is in use in an industrial context....

  7. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

    Alenoghena, C. O.; Emagbetere, J. O.; Aibinu, A. M.

    2013-12-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out.

  8. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    Alenoghena, C O; Emagbetere, J O; 1 Minna (Nigeria))" data-affiliation=" (Department of Telecommunications Engineering, Federal University of Techn.1 Minna (Nigeria))" >Aibinu, A M

    2013-01-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out

  9. Discrete PID Tuning Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Petr DOLEŽEL

    2009-06-01

    Full Text Available PID controllers are widely used in industry these days due to their useful properties such as simple tuning or robustness. While they are applicable to many control problems, they can perform poorly in some applications. Highly nonlinear system control with constrained manipulated variable can be mentioned as an example. The point of the paper is to string together convenient qualities of conventional PID control and progressive techniques based on Artificial Intelligence. Proposed control method should deal with even highly nonlinear systems. To be more specific, there is described new method of discrete PID controller tuning in this paper. This method tunes discrete PID controller parameters online through the use of genetic algorithm and neural model of controlled system in order to control successfully even highly nonlinear systems. After method description and some discussion, there is performed control simulation and comparison to one chosen conventional control method.

  10. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  11. Determination of rock depth using artificial intelligence techniques

    Institute of Scientific and Technical Information of China (English)

    R. Viswanathan; Pijush Samui

    2016-01-01

    This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth.

  12. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  13. Developing Information Systems for Competitive Intelligence Support.

    Science.gov (United States)

    Hohhof, Bonnie

    1994-01-01

    Discusses issues connected with developing information systems for competitive intelligence support; defines the elements of an effective competitive information system; and summarizes issues affecting system design and implementation. Highlights include intelligence information; information needs; information sources; decision making; and…

  14. Automation of fusion first wall design using artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshimura, Shinobu; Yagawa, Genki; Mochizuki, Yoshihiko

    1990-01-01

    This paper describes the application of artificial intelligence techniques to a design automation of the fusion first wall to be operated in the complex environment where huge electromagnetic and thermal loading as well as heavy neutron irradiation occur. As a basic strategy of designing structure shape considering many coupled phenomena, an ordinary design procedure based on the generate and test strategy is adopted because of its simplicity and broad applicability. To automate the design procedure with maintaining its flexibility, extensibility and efficiency, artificial intelligence techniques are utilized in the following. An object-oriented knowledge representation technique is adopted to store knowledge modules, that is, objects, related to the first wall design, while a data-flow processing technique is utilized as an inference mechanism among the knowledge modules. These techniques realize the flexibility and extensibility of the system. Moreover, as an efficient design modification mechanism, which is essential in a design process, an empirical approach based on experts' empirical knowledge and a mathematical approach based on a kind of numerical sensitivity analysis are introduced. The developed system is applied to a simple example of the design of a two-dimensional model of the first wall with a cooling channel, and its fundamental performance is clearly demonstrated. (author)

  15. Development of intelligent system for a thermal analysis instrument

    International Nuclear Information System (INIS)

    Xu Xiaoli; Wu Guoxin; Shi Yongchao

    2005-01-01

    The key techniques for the intelligent analysis instrument developed are proposed. Based on the technique of virtual instrumentation, the intelligent PID control algorithm to control the temperature of thermal analysis instrument is described. The dynamic character and the robust performance of traditional PID controls are improved through the dynamic gain factor, temperature rate change factor, the forecast factor, and the temperature correction factor is introduced. Using the graphic development environment of LabVIEW, the design of system modularization and the graphic display are implemented. By means of multiple mathematical modules, intelligent data processing is realized

  16. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    International Nuclear Information System (INIS)

    Meier, E.; Biedron, S.G.; LeBlanc, G.; Morgan, M.J.

    2011-01-01

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI-Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  17. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Science.gov (United States)

    Meier, E.; Biedron, S. G.; LeBlanc, G.; Morgan, M. J.

    2011-03-01

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI@Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  18. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Energy Technology Data Exchange (ETDEWEB)

    Meier, E., E-mail: evelyne.meier@synchrotron.org.a [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia) and Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia) and FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); Biedron, S.G., E-mail: biedron@anl.go [Department of Defense Project Office, Argonne National Laboratory, IL 60439 (United States); FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); LeBlanc, G., E-mail: greg.leblanc@synchrotron.org.a [Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia); Morgan, M.J., E-mail: Michael.J.Morgan@monash.ed [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia)

    2011-03-11

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI-Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  19. Techniques for Intelligence Analysis of Networks

    National Research Council Canada - National Science Library

    Cares, Jeffrey R

    2005-01-01

    ...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...

  20. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    Henke, Andrea L.; Stottler, Richard H.

    1994-01-01

    Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

  1. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.W.; Lager, D.L.

    1985-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  2. Intelligent transportation systems data compression using wavelet decomposition technique.

    Science.gov (United States)

    2009-12-01

    Intelligent Transportation Systems (ITS) generates massive amounts of traffic data, which posts : challenges for data storage, transmission and retrieval. Data compression and reconstruction technique plays an : important role in ITS data procession....

  3. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  4. Inter-cooperative collective intelligence techniques and applications

    CERN Document Server

    Bessis, Nik

    2014-01-01

    This book covers the latest advances in the rapid growing field of inter-cooperative collective intelligence aiming the integration and cooperation of various computational resources, networks and intelligent processing paradigms to collectively build intelligence and advanced decision support and interfaces for end-users. The book brings a comprehensive view of the state-of-the-art in the field of integration of sensor networks, IoT and Cloud computing, massive and intelligent querying and processing of data. As a result, the book presents lessons learned so far and identifies new research issues, challenges and opportunities for further research and development agendas. Emerging areas of applications are also identified and usefulness of inter-cooperative collective intelligence is envisaged.   Researchers, software developers, practitioners and students interested in the field of inter-cooperative collective intelligence will find the comprehensive coverage of this book useful for their research, academic...

  5. Intelligent bioinformatics : the application of artificial intelligence techniques to bioinformatics problems

    National Research Council Canada - National Science Library

    Keedwell, Edward

    2005-01-01

    ... Intelligence and Computer Science 3.1 Introduction to search 3.2 Search algorithms 3.3 Heuristic search methods 3.4 Optimal search strategies 3.5 Problems with search techniques 3.6 Complexity of...

  6. The application and development of artificial intelligence in smart clothing

    Science.gov (United States)

    Wei, Xiong

    2018-03-01

    This paper mainly introduces the application of artificial intelligence in intelligent clothing. Starting from the development trend of artificial intelligence, analysis the prospects for development in smart clothing with artificial intelligence. Summarize the design key of artificial intelligence in smart clothing. Analysis the feasibility of artificial intelligence in smart clothing.

  7. New approaches in intelligent control techniques, methodologies and applications

    CERN Document Server

    Kountchev, Roumen

    2016-01-01

    This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.

  8. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  9. Multimedia techniques for device and ambient intelligence: A continuing endeavor

    NARCIS (Netherlands)

    van den Broek, Egon

    2011-01-01

    The edited volume "Multimedia techniques for device and ambient intelligence" consists of two parts: i) an introduction to a variety of basic low level image processing techniques, leaving aside other modalities, and ii) work on high level, knowledge based processing, including interesting chapters

  10. BWR shutdown analyzer using artificial intelligence (AI) techniques

    International Nuclear Information System (INIS)

    Cain, D.G.

    1986-01-01

    A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

  11. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  12. Event detection intelligent camera development

    International Nuclear Information System (INIS)

    Szappanos, A.; Kocsis, G.; Molnar, A.; Sarkozi, J.; Zoletnik, S.

    2008-01-01

    A new camera system 'event detection intelligent camera' (EDICAM) is being developed for the video diagnostics of W-7X stellarator, which consists of 10 distinct and standalone measurement channels each holding a camera. Different operation modes will be implemented for continuous and for triggered readout as well. Hardware level trigger signals will be generated from real time image processing algorithms optimized for digital signal processor (DSP) and field programmable gate array (FPGA) architectures. At full resolution a camera sends 12 bit sampled 1280 x 1024 pixels with 444 fps which means 1.43 Terabyte over half an hour. To analyse such a huge amount of data is time consuming and has a high computational complexity. We plan to overcome this problem by EDICAM's preprocessing concepts. EDICAM camera system integrates all the advantages of CMOS sensor chip technology and fast network connections. EDICAM is built up from three different modules with two interfaces. A sensor module (SM) with reduced hardware and functional elements to reach a small and compact size and robust action in harmful environment as well. An image processing and control unit (IPCU) module handles the entire user predefined events and runs image processing algorithms to generate trigger signals. Finally a 10 Gigabit Ethernet compatible image readout card functions as the network interface for the PC. In this contribution all the concepts of EDICAM and the functions of the distinct modules are described

  13. Artificial intelligence techniques for sizing photovoltaic systems. A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Department of Electronics, Faculty of Science Engineering, LAMEL Laboratory, Jijel University, P.O. Box 98, Oulad Aissa, Jijel 18000 (Algeria); Kalogirou, S.A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus); Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Electronica, E.P.S. Jaen, Universidad de Jaen, Avda., Madrid, 35, 23071 Jaen (Spain); Shaari, S. [Faculty of Applied Sciences, Universiti Teknologi MARA 40450 Shah Alam, Selangor (Malaysia)

    2009-02-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available. (author)

  14. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  15. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an Artificial Intelligence method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed.

  16. VAR control in distribution systems by using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

    2005-07-01

    This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

  17. Practical Leader Development Program Using Emotional Intelligence

    DEFF Research Database (Denmark)

    Barfod, Jakob Rømer; Bakkegaard, Bjarne

    2017-01-01

    The Danish Army has more than ten years of experience working with developing emotional intelligence in the Royal Danish Army Officers’ Academy (RDAOA), and the Academy has developed military leaders who have benefitted from emotional intelligence training. Today many of the military leaders...... are better at understanding themselves as well as their ability to build relationships whilst under great pressure e.g. during combat operations. On the basis of field experience, qualitative research and quantitative data the effects of working with emotional intelligence in a structured way is presented...

  18. Intelligence: new findings and theoretical developments.

    Science.gov (United States)

    Nisbett, Richard E; Aronson, Joshua; Blair, Clancy; Dickens, William; Flynn, James; Halpern, Diane F; Turkheimer, Eric

    2012-01-01

    We review new findings and new theoretical developments in the field of intelligence. New findings include the following: (a) Heritability of IQ varies significantly by social class. (b) Almost no genetic polymorphisms have been discovered that are consistently associated with variation in IQ in the normal range. (c) Much has been learned about the biological underpinnings of intelligence. (d) "Crystallized" and "fluid" IQ are quite different aspects of intelligence at both the behavioral and biological levels. (e) The importance of the environment for IQ is established by the 12-point to 18-point increase in IQ when children are adopted from working-class to middle-class homes. (f) Even when improvements in IQ produced by the most effective early childhood interventions fail to persist, there can be very marked effects on academic achievement and life outcomes. (g) In most developed countries studied, gains on IQ tests have continued, and they are beginning in the developing world. (h) Sex differences in aspects of intelligence are due partly to identifiable biological factors and partly to socialization factors. (i) The IQ gap between Blacks and Whites has been reduced by 0.33 SD in recent years. We report theorizing concerning (a) the relationship between working memory and intelligence, (b) the apparent contradiction between strong heritability effects on IQ and strong secular effects on IQ, (c) whether a general intelligence factor could arise from initially largely independent cognitive skills, (d) the relation between self-regulation and cognitive skills, and (e) the effects of stress on intelligence.

  19. Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

    Science.gov (United States)

    Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

    2017-09-01

    In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

  20. Developing a Cultural Intelligence Capability

    Science.gov (United States)

    2008-12-12

    information control policy in occupied Iraq.” Military Review 88, no 2 (March-April) 2008: 58-65. Goleman , Daniel . 2008. “When emotional ...measured by Intelligence Quotient (IQ)) and Emotional Quotient (measured by Emotional Quotient (EQ)). The relative values of each are combined with...

  1. E-learning systems intelligent techniques for personalization

    CERN Document Server

    Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C

    2017-01-01

    This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

  2. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    Ho, L.; Tseng, C.; Chang, S.

    1986-01-01

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  3. Towards an Intelligent Planning Knowledge Base Development Environment

    Science.gov (United States)

    Chien, S.

    1994-01-01

    ract describes work in developing knowledge base editing and debugging tools for the Multimission VICAR Planner (MVP) system. MVP uses artificial intelligence planning techniques to automatically construct executable complex image processing procedures (using models of the smaller constituent image processing requests made to the JPL Multimission Image Processing Laboratory.

  4. Artificial intelligence techniques for voltage control

    Energy Technology Data Exchange (ETDEWEB)

    Ekwue, A.; Cheng, D.T.Y.; Macqueen, J.F.

    1997-12-31

    In electric power systems, the advantages of reactive power dispatching or optimisation include improved utilisation of reactive power sources and hence reduction in reactive power flows and real losses of the system; unloading of the system and equipment as a result of reactive flow reduction; the power factors of generation are improved and system security is enhanced; reduced voltage gradients and somewhat higher voltages which result across the system from improved operation; deferred capital investment is new reactive power sources as a result of improved utilisation of existing equipment; and for the National Grid Company plc (NGC), the main advantage is reduced out-of-merit operation. The problem of reactive power control has been studied and widely reported in the literature. Non-linear programming methods as well as linear programming techniques for constraint dispatch have been described. Static optimisation of reactive power sources by the use of sensitivity analysis was described by Kishore and Hill. Long range optimum var planning has been considered and the optimum amount and location of network reactive compensation so as to maintain the system voltage within the desired limits, while operating under normal and various insecurity states, have also been studied using several methods. The objective of this chapter is therefore to review conventional methods as well as AI techniques for reactive power control. (Author)

  5. Artificial intelligence techniques for photovoltaic applications: A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, Adel [Department of Electronics, Faculty of Sciences Engineering, LAMEL Laboratory, Jijel University, Oulad-aissa, P.O. Box 98, Jijel 18000 (Algeria); Kalogirou, Soteris A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus)

    2008-10-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more popular nowadays. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with nonlinear problems and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI has been used in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting and control of complex systems. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application. Problems presented include three areas: forecasting and modeling of meteorological data, sizing of photovoltaic systems and modeling, simulation and control of photovoltaic systems. Published literature presented in this paper show the potential of AI as design tool in photovoltaic systems. (author)

  6. The Historical Development of the Turkish Intelligence

    Directory of Open Access Journals (Sweden)

    Eray GÖÇ

    2013-12-01

    Full Text Available The purpose of this study is to give information about historical development of Turkish intelligence especially from last periods of ottoman to nowadays. It has studied the effects on services in stage of history and has given information about roles played by them in forming of today’s community structure. This study contains information about a-thousand-year effect of a sequence began by secret service of ottoman and continued by union and progress, MAH (national labor service, JİTEM (gendarmes intelligence and anti terror unit, ÖHD (special operations department and MİT (national intelligence service over Anatolia lands, besides some resources such as book, magazine and article, in this study, there is an interview of Mehmet ELKATMIŞ who is the president of Susurluk commission of investigation and has several studies on this subject, of Şamil Tayyar who is the deputy of justice and development party (Ak Party and of journalist Nasuhi Güngür on this subject. The study examines. On the other hand, the problem that intelligence services give maneuver stepping out of line of law to the state. Could the state try to adopt illegality as a principle on behalf of its continuity by means of intelligence services, could it be possible? Or, could intelligence services perform unconventional behaviors occasionally by saying “in the name of the state”? These questions have been examined.

  7. Overview of Intelligent Systems and Operations Development

    Science.gov (United States)

    Pallix, Joan; Dorais, Greg; Penix, John

    2004-01-01

    To achieve NASA's ambitious mission objectives for the future, aircraft and spacecraft will need intelligence to take the correct action in a variety of circumstances. Vehicle intelligence can be defined as the ability to "do the right thing" when faced with a complex decision-making situation. It will be necessary to implement integrated autonomous operations and low-level adaptive flight control technologies to direct actions that enhance the safety and success of complex missions despite component failures, degraded performance, operator errors, and environment uncertainty. This paper will describe the array of technologies required to meet these complex objectives. This includes the integration of high-level reasoning and autonomous capabilities with multiple subsystem controllers for robust performance. Future intelligent systems will use models of the system, its environment, and other intelligent agents with which it interacts. They will also require planners, reasoning engines, and adaptive controllers that can recommend or execute commands enabling the system to respond intelligently. The presentation will also address the development of highly dependable software, which is a key component to ensure the reliability of intelligent systems.

  8. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

    Directory of Open Access Journals (Sweden)

    Thenmozhi Srinivasan

    2015-01-01

    Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.

  9. Age versus schooling effects on intelligence development.

    Science.gov (United States)

    Cahan, S; Cohen, N

    1989-10-01

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

  10. Launch vehicle operations cost reduction through artificial intelligence techniques

    Science.gov (United States)

    Davis, Tom C., Jr.

    1988-01-01

    NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

  11. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  12. Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

    Science.gov (United States)

    Lauzon, N.; Lence, B. J.

    2002-12-01

    This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be

  13. Development of intelligent supervisory control system

    International Nuclear Information System (INIS)

    Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

    1994-01-01

    The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

  14. Spiritual Intelligence: Developing Higher Consciousness Revisited

    Science.gov (United States)

    Sisk, Dorothy A.

    2016-01-01

    This article will share the intellectual journey E. Paul Torrance and I traveled in 2001, in which we explored psychology, science and ancient wisdom and traditions, including Native American and indigenous traditions, to establish a foundation for spiritual intelligence. This section will be followed by ways to develop and nurture spiritual…

  15. Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System.

    Science.gov (United States)

    Banjar, Haneen; Adelson, David; Brown, Fred; Chaudhri, Naeem

    2017-01-01

    The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice.

  16. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    Martinez, J.M.; Nomine, J.P.

    1990-01-01

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  17. Development of extraterrestrial intelligence and physical laws

    Science.gov (United States)

    Troitskij, V. S.

    This paper considers the restrictions imposed by physical laws on the development of life and intelligence in the form of extraterrestrial civilizations. For this purpose intelligence is defined as the community of intelligent beings, joined by the exchange of mass, energy and information both between themselves and with the external medium. Due to the limitation of the velocity of exchange of information and, in particular, mass and energy exchange, the dimensions of the intelligence cannot exceed some light days, i.e. they are limited by the habitable zone about their star. It is shown that the energy consumption should not exceed the energy output of their star for the sake of preserving the cosmic near-star zone of life from energetic pollution. With the above restrictions of the energy product it takes millions of years to create an omnidirectional beacon-transmitter signals from which would be received by the contemporary antennas in all our Galaxy. It is realistic to create an omnidirectional beacon operating in the range of no more than 100-1000 light years.

  18. Artificial intelligence and human development

    International Development Research Centre (IDRC) Digital Library (Canada)

    Job and tax revenue loss through automation: With the growing use of machine .... practices that support the development of inclusive AI applications. What ..... been tested in Malaysia and in Queen Elizabeth National Park in Uganda.25 ...... We need to develop global and local values and principles for AI that prioritize.

  19. Seismic activity prediction using computational intelligence techniques in northern Pakistan

    Science.gov (United States)

    Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

    2017-10-01

    Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

  20. A development framework for distributed artificial intelligence

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1989-01-01

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

  1. Development of an Intelligent Car Engine Fault Troubleshooting ...

    African Journals Online (AJOL)

    Development of an Intelligent Car Engine Fault Troubleshooting System (CEFTS) ... and also provides a troubleshooting framework for other researchers to work on. Keywords: ... inference engine, knowledge acquisition, artificial intelligence.

  2. Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

    Directory of Open Access Journals (Sweden)

    Jackson Phiri

    2011-08-01

    Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

  3. Intelligent techniques in signal processing for multimedia security

    CERN Document Server

    Santhi, V

    2017-01-01

    This book proposes new algorithms to ensure secured communications and prevent unauthorized data exchange in secured multimedia systems. Focusing on numerous applications’ algorithms and scenarios, it offers an in-depth analysis of data hiding technologies including watermarking, cryptography, encryption, copy control, and authentication. The authors present a framework for visual data hiding technologies that resolves emerging problems of modern multimedia applications in several contexts including the medical, healthcare, education, and wireless communication networking domains. Further, it introduces several intelligent security techniques with real-time implementation. As part of its comprehensive coverage, the book discusses contemporary multimedia authentication and fingerprinting techniques, while also proposing personal authentication/recognition systems based on hand images, surveillance system security using gait recognition, face recognition under restricted constraints such as dry/wet face condi...

  4. Artificial intelligence techniques for embryo and oocyte classification.

    Science.gov (United States)

    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

  5. Intelligences Developed by the Student Chess Player

    Directory of Open Access Journals (Sweden)

    Yuraima Margelis Matos De Rojas

    2018-05-01

    Full Text Available To strengthen cognitive development in students requires the use of innovative, creative and formative strategies that allow it to achieve, being one of the didactic strategies chess. For what was proposed as research purpose: Identify the intelligences developed by the student athlete of the Sports Talent Education Unit that play chess, to suggest some recommendations that can be put into practice in educational institutions. Methodologically it was approached from the qualitative paradigm through a phenomenological method that reveals the reality from the experiences and experiences of the social actors. Six key students of the institution were chess players, to whom an open interview was applied to obtain the necessary information, which was systematized to extract the categories, codifications and triangulate the information. As results, it was obtained that the students develop the intelligences: logical-mathematical, linguistic, spatial and visual, as the intrapersonal during the game of chess and in the learning processes. Configured in categories, analyzed and interpreted from the voices of social actors, theorists and researchers. Suggesting some recommendations that can be put into practice to strengthen the intelligences in the student.

  6. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  7. An intelligent content discovery technique for health portal content management.

    Science.gov (United States)

    De Silva, Daswin; Burstein, Frada

    2014-04-23

    Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective

  8. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    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.

  9. Intelligent manipulation technique for multi-branch robotic systems

    Science.gov (United States)

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

    1990-01-01

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

  10. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

  11. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

    Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

  12. The Development of an Intelligent Leadership Model for State Universities

    OpenAIRE

    Aleme Keikha; Reza Hoveida; Nour Mohammad Yaghoubi

    2017-01-01

    Higher education and intelligent leadership are considered important parts of every country’s education system, which could potentially play a key role in accomplishing the goals of society. In theories of leadership, new patterns attempt to view leadership through the prism of creative and intelligent phenomena. This paper aims to design and develop an intelligent leadership model for public universities. A qualitativequantitative research method was used to design a basic model of intellige...

  13. Design optimum frac jobs using virtual intelligence techniques

    Science.gov (United States)

    Mohaghegh, Shahab; Popa, Andrei; Ameri, Sam

    2000-10-01

    Designing optimal frac jobs is a complex and time-consuming process. It usually involves the use of a two- or three-dimensional computer model. For the computer models to perform as intended, a wealth of input data is required. The input data includes wellbore configuration and reservoir characteristics such as porosity, permeability, stress and thickness profiles of the pay layers as well as the overburden layers. Among other essential information required for the design process is fracturing fluid type and volume, proppant type and volume, injection rate, proppant concentration and frac job schedule. Some of the parameters such as fluid and proppant types have discrete possible choices. Other parameters such as fluid and proppant volume, on the other hand, assume values from within a range of minimum and maximum values. A potential frac design for a particular pay zone is a combination of all of these parameters. Finding the optimum combination is not a trivial process. It usually requires an experienced engineer and a considerable amount of time to tune the parameters in order to achieve desirable outcome. This paper introduces a new methodology that integrates two virtual intelligence techniques, namely, artificial neural networks and genetic algorithms to automate and simplify the optimum frac job design process. This methodology requires little input from the engineer beyond the reservoir characterizations and wellbore configuration. The software tool that has been developed based on this methodology uses the reservoir characteristics and an optimization criteria indicated by the engineer, for example a certain propped frac length, and provides the detail of the optimum frac design that will result in the specified criteria. An ensemble of neural networks is trained to mimic the two- or three-dimensional frac simulator. Once successfully trained, these networks are capable of providing instantaneous results in response to any set of input parameters. These

  14. Design optimum frac jobs using virtual intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Shahab Mohaghegh; Andrei Popa; Sam Ameri [West Virginia University, Morgantown, WV (United States). Petroleum and Natural Gas Engineering

    2000-10-01

    Designing optimal frac jobs is a complex and time-consuming process. It usually involves the use of a two- or three-dimensional computer model. For the computer models to perform as intended, a wealth of input data is required. The input data includes wellbore configuration and reservoir characteristics such as porosity, permeability, stress and thickness profiles of the pay layers as well as the overburden layers. Among other essential information required for the design process is fracturing fluid type and volume, proppant type and volume, injection rate, proppant concentration and frac job schedule. Some of the parameters such as fluid and proppant types have discrete possible choices. Other parameters such as fluid and proppant volume, on the other hand, assume values from within a range of minimum and maximum values. A potential frac design for a particular pay zone is a combination of all of these parameters. Finding the optimum combination is not a trivial process. It usually requires an experienced engineer and a considerable amount of time to tune the parameters in order to achieve desirable outcome. This paper introduces a new methodology that integrates two virtual intelligence techniques, namely, artificial neural networks and genetic algorithms to automate and simplify the optimum frac job design process. This methodology requires little input from the engineer beyond the reservoir characterizations and wellbore configuration. The software tool that has been developed based on this methodology uses the reservoir characteristics and an optimization criteria indicated by the engineer, for example a certain propped frac length, and provides the detail of the optimum frac design that will result in the specified criteria. An ensemble of neural networks is trained to mimic the two- or three-dimensional frac simulator. Once successfully trained, these networks are capable of providing instantaneous results in response to any set of input parameters. These

  15. Applying Artificial Intelligence and Internet Techniques in Rural Tourism Domain

    OpenAIRE

    Turcu, Cristina; Turcu, Cornel

    2017-01-01

    Society has become more dependent on automated intelligent systems, at the same time, these systems have become more and more complicated. Society's expectation regarding the capabilities and intelligence of such systems has also grown. We have become a more complicated society with more complicated problems. As the expectation of intelligent systems rises, we discover many more applications for artificial intelligence. Additionally, as the difficulty level and computational requirements of s...

  16. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

    Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

    2008-01-01

    Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

  17. Artificial intelligence techniques for automatic screening of amblyogenic factors.

    Science.gov (United States)

    Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

    2008-01-01

    To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the "gold standard" specialist examination with a "refer/do not refer" decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than -7. Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years.

  18. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  19. Development of a Danish speech intelligibility test

    DEFF Research Database (Denmark)

    Nielsen, Jens Bo; Dau, Torsten

    2009-01-01

    Abstract A Danish speech intelligibility test for assessing the speech recognition threshold in noise (SRTN) has been developed. The test consists of 180 sentences distributed in 18 phonetically balanced lists. The sentences are based on an open word-set and represent everyday language. The sente....... The test was verified with 14 normal-hearing listeners; the overall SRTN lies at a signal-to-noise ratio of -3.15 dB with a standard deviation of 1.0 dB. The list-SRTNs deviate less than 0.5 dB from the overall mean....

  20. Robot Advanced Intelligent Control developed through Versatile ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... environments of human life exposed to great dangers such as support and repair in .... intelligent control interfaces, network quality of service, shared resources and ..... Artificial Intelligence series, volume 6556, p. 336-349 ...

  1. Research and development of artificial intelligence in China

    Institute of Scientific and Technical Information of China (English)

    Jane Qiu

    2016-01-01

    This year saw several milestones in the development of artificial intelligence.In March,Alpha Go,a computer algorithm developed by Google’s London-based company,Deep Mind,beat the world champion Lee Sedol at Go,an ancient Chinese board game.In October,the same company unveiled in the journal Nature its latest technique that allows a machine to solve tasks that require logic and reasoning,such as finding its way around the London

  2. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, F.J.O. [Instituto de Engenharia Nuclear, Cidade Universitaria, Rio de Janeiro, CEP 21945-970, Caixa Postal 68550 (Brazil)], E-mail: fferreira@ien.gov.br; Crispim, V.R.; Silva, A.X. [DNC/Poli, PEN COPPE CT, UFRJ Universidade Federal do Rio de Janeiro, CEP 21941-972, Caixa Postal 68509, Rio de Janeiro (Brazil)

    2010-06-15

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  3. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ferreira, F.J.O.; Crispim, V.R.; Silva, A.X.

    2010-01-01

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  4. Development of a system for monitoring and diagnosis of steam generator tubes using artificial intelligence techniques on Eddy Current Test signals

    International Nuclear Information System (INIS)

    Mesquita, Roberto Navarro de; Ting, Daniel Kao Sun; Lopez, Luis A. Negro M.; Upadhyaya, Belle R.

    2002-01-01

    New classification and feature extraction methods for steam generator tube defects are being developed by IPEN/CNEN-SP in cooperation with UTK to improve a monitoring and diagnosis system for classification and characterization of steam generator tube defects using Eddy Current Testing (ECT) signals. The first methodology being developed uses a set of feature extraction methods applied to different tube defect type ECT signals and each obtained feature vector is projected into a bi-dimensional map obtained by a Self-Organizing Map neural network. This methodology allows an optimal feature extraction method selection for the defect type classification. Other approach is being developed using tubes with different manufactured defect types which are tested using MIZ-17ET equipment with 4 sets of probes (two different diameter). A fuzzy inference system will be used to build a knowledge base for these defects. These methodology and algorithms will be integrated into an automated diagnosis system being developed with UTK, which is designed to read both on-line acquired data, as well as stored data files. These commercial software tools are the ones usually utilized in nuclear power plants. (author)

  5. Development of a system for monitoring and diagnosis of steam generator tubes using artificial intelligence techniques on Eddy Current Test signals

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Roberto Navarro de [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil). Centro de Monitoracao e Diagnostico]|[Sao Paulo Univ., SP (Brazil); Ting, Daniel Kao Sun [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil). Centro de Monitoracao e Diagnostico; Cabral, Eduardo Lobo C. [Sao Paulo Univ., SP (Brazil); Lopez, Luis A. Negro M. [Faculdade de Engenharia Industrial, Sao Bernardo do Campo, SP (Brazil); Upadhyaya, Belle R. [Tennessee Univ., Knoxville, TN (United States)

    2002-07-01

    New classification and feature extraction methods for steam generator tube defects are being developed by IPEN/CNEN-SP in cooperation with UTK to improve a monitoring and diagnosis system for classification and characterization of steam generator tube defects using Eddy Current Testing (ECT) signals. The first methodology being developed uses a set of feature extraction methods applied to different tube defect type ECT signals and each obtained feature vector is projected into a bi-dimensional map obtained by a Self-Organizing Map neural network. This methodology allows an optimal feature extraction method selection for the defect type classification. Other approach is being developed using tubes with different manufactured defect types which are tested using MIZ-17ET equipment with 4 sets of probes (two different diameter). A fuzzy inference system will be used to build a knowledge base for these defects. These methodology and algorithms will be integrated into an automated diagnosis system being developed with UTK, which is designed to read both on-line acquired data, as well as stored data files. These commercial software tools are the ones usually utilized in nuclear power plants. (author)

  6. Application of computational intelligence techniques for load shedding in power systems: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Bakar, A.H.A.; Mohamad, Hasmaini

    2013-01-01

    Highlights: • The power system blackout history of last two decades is presented. • Conventional load shedding techniques, their types and limitations are presented. • Applications of intelligent techniques in load shedding are presented. • Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO. • The discussion and comparison between these techniques are provided. - Abstract: Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time

  7. Experimental development of power reactor intelligent control

    International Nuclear Information System (INIS)

    Edwards, R.M.; Garcia, H.E.; Lee, K.Y.

    1992-01-01

    The US nuclear utility industry initiated an ambitious program to modernize the control systems at a minimum of ten existing nuclear power plants by the year 2000. That program addresses urgent needs to replace obsolete instrumentation and analog controls with highly reliable state-of-the-art computer-based digital systems. Large increases in functionality that could theoretically be achieved in a distributed digital control system are not an initial priority in the industry program but could be logically considered in later phases. This paper discusses the initial development of an experimental sequence for developing, testing, and verifying intelligent fault-accommodating control for commercial nuclear power plant application. The sequence includes an ultra-safe university research reactor (TRIGA) and a passively safe experimental power plant (Experimental Breeder Reactor 2)

  8. Urban Big Data and the Development of City Intelligence

    Directory of Open Access Journals (Sweden)

    Yunhe Pan

    2016-06-01

    Full Text Available This study provides a definition for urban big data while exploring its features and applications of China's city intelligence. The differences between city intelligence in China and the “smart city” concept in other countries are compared to highlight and contrast the unique definition and model for China's city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intelligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China's urban big data. Considering the supporting and core role that urban big data plays in city intelligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China's urban development. In conclusion, it is imperative that China make full use of its unique advantages—including using the nation's current state of development and resources, geographical advantages, and good human relations—in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.

  9. Crack identification based on synthetic artificial intelligent technique

    International Nuclear Information System (INIS)

    Shim, Mun Bo; Suh, Myung Won

    2001-01-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising

  10. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

    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.

  11. Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Sfetsos, A. [7 Pirsou Str., Athens (Greece); Coonick, A.H. [Imperial Coll. of Science Technology and Medicine, Dept. of Electrical and Electronic Engineering, London (United Kingdom)

    2000-07-01

    This paper introduces a new approach for the forecasting of mean hourly global solar radiation received by a horizontal surface. In addition to the traditional linear methods, several artificial-intelligence-based techniques are studied. These include linear, feed-forward, recurrent Elman and Radial Basis neural networks alongside the adaptive neuro-fuzzy inference scheme. The problem is examined initially for the univariate case, and is extended to include additional meteorological parameters in the process of estimating the optimum model. The results indicate that the developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. The forecasting ability of some models can be further enhanced with the use of additional meteorological parameters. (Author)

  12. Intelligent food packaging - research and development

    OpenAIRE

    Renata Dobrucka; Ryszard Cierpiszewski; Andrzej Korzeniowski

    2015-01-01

    Packaging also fosters effective marketing of the food through distribution and sale channels. It is of the utmost importance to optimize the protection of the food, a great quality and appearance - better than typical packaged foods. In recent years, intelligent packaging became very popular. Intelligent packaging is becoming more and more widely used for food products. Application of this type of solution contributes to improvement of the quality consumer life undoubtedly. Intelligent packa...

  13. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  14. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  15. The development of advanced robotic technology. A study on the tele-existence and intelligent control of a robot system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Myung Jin; Byun, Jueng Nam; Kim, Jong Hwan; Lee, Ju Jang; Bang, Seok Won; Chu, Gil Hwan; Park, Jong Cheol; Choi, Jong Seok; Yang, Jung Min; Hong, Sun Ki [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1995-07-01

    To increase the efficiency of human intelligence it is required to develop an intelligent monitoring and system. In this research, we develop intelligent control methods related with tele-operation, tele-existence, real-time control technique, and intelligent control technique. Those are key techniques in tele-operation, especially for the repair and maintenance of nuclear power plants. The objective of this project is to develop of the tele-existence and intelligent control system for a robot used in the nuclear power plants. (author). 20 refs.

  16. Intelligent Heuristic Techniques for the Optimization of the Transshipment and Storage Operations at Maritime Container Terminals

    Directory of Open Access Journals (Sweden)

    Christopher Expósito-Izquierdo

    2017-02-01

    Full Text Available This paper summarizes the main contributions of the Ph.D. thesis of Christopher Exp\\'osito-Izquierdo. This thesis seeks to develop a wide set of intelligent heuristic and meta-heuristic algorithms aimed at solving some of the most highlighted optimization problems associated with the transshipment and storage of containers at conventional maritime container terminals. Under the premise that no optimization technique can have a better performance than any other technique under all possible assumptions, the main point of interest in the domain of maritime logistics is to propose optimization techniques superior in terms of effectiveness and computational efficiency to previous proposals found in the scientific literature when solving individual optimization problems under realistic scenarios. Simultaneously, these optimization techniques should be enough competitive to be potentially implemented in practice. }}

  17. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  18. Underwater cutting techniques developments

    International Nuclear Information System (INIS)

    Bach, F.-W.

    1990-01-01

    The primary circuit structures of different nuclear powerplants are constructed out of stainless steels, ferritic steels, plated ferritic steels and alloys of aluminium. According to the level of the specific radiation of these structures, it is necessary for dismantling to work with remote controlled cutting techniques. The most successful way to protect the working crew against exposure of radiation is to operate underwater in different depths. The following thermal cutting processes are more or less developed to work under water: For ferritic steels only - flame cutting; For ferritic steels, stainless steels, cladded steels and aluminium alloys - oxy-arc-cutting, arc-waterjet-cutting with a consumable electrode, arc-saw-cutting, plasma-arc-cutting and plasma-arc-saw. The flame cutting is a burning process, all the other processes are melt-cutting processes. This paper explains the different techniques, giving a short introduction of the theory, a discussion of the possibilities with the advantages and disadvantages of these processes giving a view into the further research work in this interesting field. (author)

  19. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  20. The development of intelligent healthcare in China.

    Science.gov (United States)

    Zheng, Xiaochen; Rodríguez-Monroy, Carlos

    2015-05-01

    Intelligent healthcare (IH) is proposed with the fast application of Internet of Things technology in the healthcare area in recent years. It is considered as an expansion of e-health and telemedicine. As the largest developing country, China is investing large amounts of resources to push forward the development of IH. It is one of the centerpieces of the country's New Healthcare Reform, and great expectation is placed on it to help solve the conflict between limited healthcare resources and the large patient population. Essential policies, milestones, standards, and specifications from the Chinese government since the 1990s were reviewed to show the brief development history of IH in China. Some typical cases and products have been analyzed to present the current situation. The main problems and future development directions have been summarized. The IH industry in China has great potential and is growing very fast, but a lot of challenges also exist. In the future both government support and the active participation of nongovernmental capital are needed to push forward the whole industry.

  1. Ultrascalable Techniques Applied to the Global Intelligence Community Information Awareness Common Operating Picture (IA COP)

    National Research Council Canada - National Science Library

    Valdes, Alfonso; Kadte, Jim

    2005-01-01

    The focus of this research is to develop detection, correlation, and representation approaches to address the needs of the Intelligence Community Information Awareness Common Operating Picture (IA COP...

  2. Artificial Intelligence (AI techniques to analyze the determinants attributes in housing prices

    Directory of Open Access Journals (Sweden)

    Julia M. Núñez Tabale

    2016-12-01

    Full Text Available The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI techniques, such as artificial neural networks (ANN, these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain.

  3. Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

    Science.gov (United States)

    Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

    2017-01-01

    Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

  4. [Development of intelligence in old age].

    Science.gov (United States)

    Rott, C

    1990-01-01

    This article attempts to find the structure of a selected spectrum of intelligence. A combination of longitudinal and cross-sectional methods is applied. Two dimensions were found, which can be named as "crystallized" and "fluid" abilities (in the sense of Horn & Cattell). Whereas, the crystallized abilities do not show any systematic variation from age 61 to 83, fluid abilities decline with age. Schaie's three-component-model is not able to describe differences and variations of crystallized intelligence. Within fluid intelligence, age changes are more important than cohort differences. There are hints that structural changes take place.

  5. Emotional Intelligence and Cognitive Moral Development in Undergraduate Business Students

    Science.gov (United States)

    McBride, Elizabeth A.

    2010-01-01

    This study examines relationships between emotional intelligence (EI) and cognitive moral development (CMD) in undergraduate business students. The ability model of emotional intelligence was used in this study, which evaluated possible relationships between EI and CMD in a sample of 82 undergraduate business students. The sample population was…

  6. Competitive intelligence and national development: the role of ...

    African Journals Online (AJOL)

    Competitive intelligence (CI) is the process of developing actionable foresight regarding competitive dynamics and non-market factors that can ... It is a relevant tool for strategic decision making which in return impacts national ... archives, resource centers, etc are yet to realize their position as Competitive Intelligent Agents.

  7. Solving Multi-Pollutant Emission Dispatch Problem Using Computational Intelligence Technique

    Directory of Open Access Journals (Sweden)

    Nur Azzammudin Rahmat

    2016-06-01

    Full Text Available Economic dispatch is a crucial process conducted by the utilities to correctly determine the satisfying amount of power to be generated and distributed to the consumers. During the process, the utilities also consider pollutant emission as the consequences of fossil-fuel consumption. Fossil-fuel includes petroleum, coal, and natural gas; each has its unique chemical composition of pollutants i.e. sulphur oxides (SOX, nitrogen oxides (NOX and carbon oxides (COX. This paper presents multi-pollutant emission dispatch problem using computational intelligence technique. In this study, a novel emission dispatch technique is formulated to determine the amount of the pollutant level. It utilizes a pre-developed optimization technique termed as differential evolution immunized ant colony optimization (DEIANT for the emission dispatch problem. The optimization results indicated high level of COX level, regardless of any type of fossil fuel consumed.

  8. An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

    Science.gov (United States)

    Li, De Z.; Wang, Wilson; Ismail, Fathy

    2017-11-01

    Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

  9. Intelligent food packaging - research and development

    Directory of Open Access Journals (Sweden)

    Renata Dobrucka

    2015-03-01

    Full Text Available Packaging also fosters effective marketing of the food through distribution and sale channels. It is of the utmost importance to optimize the protection of the food, a great quality and appearance - better than typical packaged foods. In recent years, intelligent packaging became very popular. Intelligent packaging is becoming more and more widely used for food products. Application of this type of solution contributes to improvement of the quality consumer life undoubtedly. Intelligent packaging refers to a package that can sense environmental changes, and in turn, informs the users about the changes. These packaging systems contain devices that are capable of sensing and providing information about the functions and properties of the packaged foods. Also, this paper will review intelligent packaging technologies and describe different types of indicators (time-temperature indicators, freshness indicators.

  10. Agile Development for Service Oriented Business Intelligence Solutions

    Directory of Open Access Journals (Sweden)

    Marinela MIRCEA

    2011-03-01

    Full Text Available Considering the evolution of information and communications technology, the necessity of alignment of public and private sectors to European Union requirements, the current economic crisis, and the global context, all organizations are trying to achieve major changes that would enable them to operate as intelligent organizations. For this purpose, agility and Business Intelligence are seen by most managers as a way to transform their organizations into intelligent organizations. The study highlights the importance of modern approaches (Service Oriented Architecture, Business Process Management, Business Rules, Cloud Computing, Master Data Management in developing agile Business Intelligence solutions. The paper also presents the stages of developing an agile Business Intelligence solution in the case of public procurement.

  11. Hacking web intelligence open source intelligence and web reconnaissance concepts and techniques

    CERN Document Server

    Chauhan, Sudhanshu

    2015-01-01

    Open source intelligence (OSINT) and web reconnaissance are rich topics for infosec professionals looking for the best ways to sift through the abundance of information widely available online. In many cases, the first stage of any security assessment-that is, reconnaissance-is not given enough attention by security professionals, hackers, and penetration testers. Often, the information openly present is as critical as the confidential data. Hacking Web Intelligence shows you how to dig into the Web and uncover the information many don't even know exists. The book takes a holistic approach

  12. Data Mining for Business Intelligence Concepts, Techniques, and Applications in Microsoft Office Excel(r) with XLMiner(r)

    CERN Document Server

    Shmueli, Galit; Bruce, Peter C

    2011-01-01

    Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edit

  13. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry

    International Nuclear Information System (INIS)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R.; Mendez, R.; Gallego, E.; Sousa L, M. A.

    2016-10-01

    The Taguchi methodology has proved to be highly efficient to solve inverse problems, in which the values of some parameters of the model must be obtained from the observed data. There are intrinsic mathematical characteristics that make a problem known as inverse. Inverse problems appear in many branches of science, engineering and mathematics. To solve this type of problem, researches have used different techniques. Recently, the use of techniques based on Artificial Intelligence technology is being explored by researches. This paper presents the use of a software tool based on artificial neural networks of generalized regression in the solution of inverse problems with application in high energy physics, specifically in the solution of the problem of neutron spectrometry. To solve this problem we use a software tool developed in the Mat Lab programming environment, which employs a friendly user interface, intuitive and easy to use for the user. This computational tool solves the inverse problem involved in the reconstruction of the neutron spectrum based on measurements made with a Bonner spheres spectrometric system. Introducing this information, the neural network is able to reconstruct the neutron spectrum with high performance and generalization capability. The tool allows that the end user does not require great training or technical knowledge in development and/or use of software, so it facilitates the use of the program for the resolution of inverse problems that are in several areas of knowledge. The techniques of Artificial Intelligence present singular veracity to solve inverse problems, given the characteristics of artificial neural networks and their network topology, therefore, the tool developed has been very useful, since the results generated by the Artificial Neural Network require few time in comparison to other techniques and are correct results comparing them with the actual data of the experiment. (Author)

  14. An Agent-Based Model for the Development of Intelligent Mobile Services

    NARCIS (Netherlands)

    Koch, F.L.

    2009-01-01

    The next generation of mobile services must invisible, convenient, and useful. It requires new techniques to design and develop mobile computing applications, based on user-centred, environment-aware, adaptive behaviour. I propose an alternative technology for the development of intelligent mobile

  15. The National Artificial Intelligence Research And Development Strategic Plan

    Data.gov (United States)

    Networking and Information Technology Research and Development, Executive Office of the President — Executive Summary: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous societal and economic benefit. AI has the potential...

  16. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

    K.Manimala; Dr.K.Selvi; R.Ahila

    2008-01-01

    Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge...

  17. Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

    2014-01-01

    Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

  18. Holistic Development of Adolescents for Social Intelligence ...

    African Journals Online (AJOL)

    Data was collected using the Emotional Maturity Scale (EMS), Social Intelligence Scale (SIS) and Spiritual Personality Inventory (SPI) and analyzed using t-test, product moment correlation coefficient and multiple regression tools. Results obtained indicated that there is a significant difference in the three groups of ...

  19. Design on intelligent gateway technique in home network

    Science.gov (United States)

    Hu, Zhonggong; Feng, Xiancheng

    2008-12-01

    Based on digitization, multimedia, mobility, wide band, real-time interaction and so on,family networks, because can provide diverse and personalized synthesis service in information, correspondence work, entertainment, education and health care and so on, are more and more paid attention by the market. The family network product development has become the focus of the related industry. In this paper,the concept of the family network and the overall reference model of the family network are introduced firstly.Then the core techniques and the correspondence standard related with the family network are proposed.The key analysis is made for the function of family gateway, the function module of the software,the key technologies to client side software architecture and the trend of development of the family network entertainment seeing and hearing service and so on. Product present situation of the family gateway and the future trend of development, application solution of the digital family service are introduced. The development of the family network product bringing about the digital family network industry is introduced finally.It causes the development of software industries,such as communication industry,electrical appliances industry, computer and game and so on.It also causes the development of estate industry.

  20. Research on the development of scientific and technological intelligence in big data environment

    Directory of Open Access Journals (Sweden)

    Wu Qiong

    2018-01-01

    development of scientific and technological intelligence and problems faced by the big data intelligence system. Finally, the author has predicted the opportunities and challenges for scientific and technological intelligence service agency posed by the big data.

  1. Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

    Science.gov (United States)

    Blasch, Erik

    2015-06-01

    Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

  2. Early detection and identification of anomalies in chemical regime based on computational intelligence techniques

    International Nuclear Information System (INIS)

    Figedy, Stefan; Smiesko, Ivan

    2012-01-01

    This article provides brief information about the fundamental features of a newly-developed diagnostic system for early detection and identification of anomalies being generated in water chemistry regime of the primary and secondary circuit of the VVER-440 reactor. This system, which is called SACHER (System of Analysis of CHEmical Regime), was installed within the major modernization project at the NPP-V2 Bohunice in the Slovak Republic. The SACHER system has been fully developed on MATLAB environment. It is based on computational intelligence techniques and inserts various elements of intelligent data processing modules for clustering, diagnosing, future prediction, signal validation, etc, into the overall chemical information system. The application of SACHER would essentially assist chemists to identify the current situation regarding anomalies being generated in the primary and secondary circuit water chemistry. This system is to be used for diagnostics and data handling, however it is not intended to fully replace the presence of experienced chemists to decide upon corrective actions. (author)

  3. Assessing the Value of Structured Analytic Techniques in the U.S. Intelligence Community

    Science.gov (United States)

    2016-01-01

    Analytic Techniques, and Why Do Analysts Use Them? SATs are methods of organizing and stimulating thinking about intelligence problems. These methods... thinking ; and imaginative thinking techniques encourage new perspectives, insights, and alternative scenarios. Among the many SATs in use today, the...more transparent, so that other analysts and customers can bet - ter understand how the judgments were reached. SATs also facilitate group involvement

  4. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  5. Developing an intelligent assistant for table tennis umpires

    OpenAIRE

    Wong, Patrick K. C.

    2007-01-01

    This paper outlines the idea and plan of developing an intelligent assistant for table tennis umpire in evaluating services. Table tennis is a fast sport. A service usually takes a few second to complete but there are many observations an umpire needs to take and makes a judgment before or soon after the service is complete. This is a complex task and the author believes the employment of videography, image processing and artificial intelligence (AI) technologies could help evaluating the ser...

  6. Intelligent systems in oil field development under uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco, Marco A.C.; Vellasco, Marley M.B.R. (eds.) [PUC-Rio, Rio de Janeiro (Brazil). Dept. of Electrical Engineering

    2009-07-01

    Intelligent Systems use a range of methodologies for analysis, pre-processing, storage, organization, enhancing and mining of operational data, turning it into useful information and knowledge for decision makers in business enterprises. These intelligent technologies for decision support have been used with success by companies and organizations that are looking for competitive advantages whenever the issues on forecast, optimization, risks analysis, fraud detection, and decision under uncertainties are presented. Intelligent Systems (IS) offer to managers and decision makers the best solutions for complex applications, normally considered difficult, very restrictive or even impossible. The use of such techniques leads to a revolutionary process which has a significant impact in the business management strategy, by providing on time, correct information, ready to use. Computational intelligence techniques, especially genetic algorithms, genetic programming, neural networks, fuzzy logic and neuro-fuzzy as well as modern finance theories, such as real options theory, are here presented and exemplified in oil and gas exploitation and production. This book is addressed to executives and students, directly involved or interested in intelligent management in different fields. (orig.)

  7. A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River

    Directory of Open Access Journals (Sweden)

    Ehsan Olyaie

    2017-05-01

    Full Text Available Most of the water quality models previously developed and used in dissolved oxygen (DO prediction are complex. Moreover, reliable data available to develop/calibrate new DO models is scarce. Therefore, there is a need to study and develop models that can handle easily measurable parameters of a particular site, even with short length. In recent decades, computational intelligence techniques, as effective approaches for predicting complicated and significant indicator of the state of aquatic ecosystems such as DO, have created a great change in predictions. In this study, three different AI methods comprising: (1 two types of artificial neural networks (ANN namely multi linear perceptron (MLP and radial based function (RBF; (2 an advancement of genetic programming namely linear genetic programming (LGP; and (3 a support vector machine (SVM technique were used for DO prediction in Delaware River located at Trenton, USA. For evaluating the performance of the proposed models, root mean square error (RMSE, Nash–Sutcliffe efficiency coefficient (NS, mean absolute relative error (MARE and, correlation coefficient statistics (R were used to choose the best predictive model. The comparison of estimation accuracies of various intelligence models illustrated that the SVM was able to develop the most accurate model in DO estimation in comparison to other models. Also, it was found that the LGP model performs better than the both ANNs models. For example, the determination coefficient was 0.99 for the best SVM model, while it was 0.96, 0.91 and 0.81 for the best LGP, MLP and RBF models, respectively. In general, the results indicated that an SVM model could be employed satisfactorily in DO estimation.

  8. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Naser, J.A.

    1987-01-01

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  9. Emotionally intelligent learner leadership development: a case study

    Directory of Open Access Journals (Sweden)

    CA Jansen

    2014-01-01

    Full Text Available A case study was conducted with a student leadership body of a private multicultural international secondary school in North- West Province, South Africa, to indicate that the emotional intelligence leadership development challenges of student leaders can be identified through a questionnaire as a measuring instrument, which can then be utilized in promoting training and development of student leaders. The questionnaire results were used to construct emotional intelligence leadership profiles for the 12 participating student leaders, followed by semi-structured interviews with them to verify the results qualitatively. The results of the questionnaire and two of the interviews are reported. It was established that it was possible to develop a reliable instrument to measure the emotional intelligence leadership development challenges of student leaders, which can be used in promoting their training and development.

  10. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

  11. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

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

  12. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

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

  13. A new approach to PWR power control using intelligent techniques

    International Nuclear Information System (INIS)

    Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.; Sadati, N.

    2004-01-01

    Improved load following capability is one of the main technical performances of advanced PWR(APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (A.O) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to A.o control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability

  14. Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

    Science.gov (United States)

    Stottler, D.

    There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

  15. The single chip microcomputer technique in an intelligent nuclear instrument

    International Nuclear Information System (INIS)

    Wang Tieliu; Sun Punan; Wang Ying

    1995-01-01

    The authors present that how to acquire and process the output signals from the nuclear detector adopting single chip microcomputer technique, including working principles and the designing method of the computer's software and hardware in the single chip microcomputer instrument

  16. Development of turbine cycle performance analyzer using intelligent data mining

    Energy Technology Data Exchange (ETDEWEB)

    Heo, Gyun Young

    2004-02-15

    In recent year, the performance enhancement of turbine cycle in nuclear power plants is being highlighted because of worldwide deregulation environment. Especially the first target of operating plants became the reduction of operating cost to compete other power plants. It is known that overhaul interval is closely related to operating cost Author identified that the rapid and reliable performance tests, analysis, and diagnosis play an important role in the control of overhaul interval through field investigation. First the technical road map was proposed to clearly set up the objectives. The controversial issues were summarized into data gathering, analysis tool, and diagnosis method. Author proposed the integrated solution on the basis of intelligent data mining techniques. For the reliable data gathering, the state analyzer composed of statistical regression, wavelet analysis, and neural network was developed. The role of the state analyzer is to estimate unmeasured data and to increase the reliability of the collected data. For the advanced performance analysis, performance analysis toolbox was developed. The purpose of this tool makes analysis process easier and more accurate by providing three novel heat balance diagrams. This tool includes the state analyzer and turbine cycle simulation code. In diagnosis module, the probabilistic technique based on Bayesian network model and the deterministic technique based on algebraical model are provided together. It compromises the uncertainty in diagnosis process and the pin-point capability. All the modules were validated by simulated data as well as actual test data, and some modules are used as industrial applications. We have a lot of thing to be improved in turbine cycle in order to increase plant availability. This study was accomplished to remind the concern about the importance of turbine cycle and to propose the solutions on the basis of academic as well as industrial needs.

  17. Development of turbine cycle performance analyzer using intelligent data mining

    International Nuclear Information System (INIS)

    Heo, Gyun Young

    2004-02-01

    In recent year, the performance enhancement of turbine cycle in nuclear power plants is being highlighted because of worldwide deregulation environment. Especially the first target of operating plants became the reduction of operating cost to compete other power plants. It is known that overhaul interval is closely related to operating cost Author identified that the rapid and reliable performance tests, analysis, and diagnosis play an important role in the control of overhaul interval through field investigation. First the technical road map was proposed to clearly set up the objectives. The controversial issues were summarized into data gathering, analysis tool, and diagnosis method. Author proposed the integrated solution on the basis of intelligent data mining techniques. For the reliable data gathering, the state analyzer composed of statistical regression, wavelet analysis, and neural network was developed. The role of the state analyzer is to estimate unmeasured data and to increase the reliability of the collected data. For the advanced performance analysis, performance analysis toolbox was developed. The purpose of this tool makes analysis process easier and more accurate by providing three novel heat balance diagrams. This tool includes the state analyzer and turbine cycle simulation code. In diagnosis module, the probabilistic technique based on Bayesian network model and the deterministic technique based on algebraical model are provided together. It compromises the uncertainty in diagnosis process and the pin-point capability. All the modules were validated by simulated data as well as actual test data, and some modules are used as industrial applications. We have a lot of thing to be improved in turbine cycle in order to increase plant availability. This study was accomplished to remind the concern about the importance of turbine cycle and to propose the solutions on the basis of academic as well as industrial needs

  18. An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

    Science.gov (United States)

    Su, Zhongqing; Ye, Lin

    2004-08-01

    The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

  19. Simulation and prediction for energy dissipaters and stilling basins design using artificial intelligence technique

    Directory of Open Access Journals (Sweden)

    Mostafa Ahmed Moawad Abdeen

    2015-12-01

    Full Text Available Water with large velocities can cause considerable damage to channels whose beds are composed of natural earth materials. Several stilling basins and energy dissipating devices have been designed in conjunction with spillways and outlet works to avoid damages in canals’ structures. In addition, lots of experimental and traditional mathematical numerical works have been performed to profoundly investigate the accurate design of these stilling basins and energy dissipaters. The current study is aimed toward introducing the artificial intelligence technique as new modeling tool in the prediction of the accurate design of stilling basins. Specifically, artificial neural networks (ANNs are utilized in the current study in conjunction with experimental data to predict the length of the hydraulic jumps occurred in spillways and consequently the stilling basin dimensions can be designed for adequate energy dissipation. The current study showed, in a detailed fashion, the development process of different ANN models to accurately predict the hydraulic jump lengths acquired from different experimental studies. The results obtained from implementing these models showed that ANN technique was very successful in simulating the hydraulic jump characteristics occurred in stilling basins. Therefore, it can be safely utilized in the design of these basins as ANN involves minimum computational and financial efforts and requirements compared with experimental work and traditional numerical techniques such as finite difference or finite elements.

  20. Computational intelligence techniques for biological data mining: An overview

    Science.gov (United States)

    Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

    2014-10-01

    Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

  1. Intelligent leadership and leadership competencies : developing a leadership framework for intelligent organizations

    OpenAIRE

    Sydänmaanlakka, Pentti

    2003-01-01

    The purpose of this study was to develop a leadership framework for intelligent organizations. This was done by analyzing the future working environment of managers, leadership as a phenomenon and as a process and leadership competencies. How leadership is typically learned and trained and how we could improve these activities, was also studied. One of the contentions of this thesis is that as the world is shifting from an industrial paradigm to a post-industrial paradigm, it is necessary tha...

  2. Microsoft SQL Server 2014 Business Intelligence development beginner's guide

    CERN Document Server

    Rad, Reza

    2014-01-01

    Written in an easy-to-follow, example-driven format, there are plenty of step-by-step instructions to help get you started! The book has a friendly approach, with the opportunity to learn by experimenting.If you are a BI and Data Warehouse developer new to Microsoft Business Intelligence, and looking to get a good understanding of the different components of Microsoft SQL Server for Business Intelligence, this book is for you.It's assumed that you will have some experience in databases systems and T-SQL. This book is will give you a good upshot view of each component and scenarios featuring th

  3. Fuzzy Cognitive Map for Software Testing Using Artificial Intelligence Techniques

    OpenAIRE

    Larkman , Deane; Mohammadian , Masoud; Balachandran , Bala; Jentzsch , Ric

    2010-01-01

    International audience; This paper discusses a framework to assist test managers to evaluate the use of AI techniques as a potential tool in software testing. Fuzzy Cognitive Maps (FCMs) are employed to evaluate the framework and make decision analysis easier. A what-if analysis is presented that explores the general application of the framework. Simulations are performed to show the effectiveness of the proposed method. The framework proposed is innovative and it assists managers in making e...

  4. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    International Nuclear Information System (INIS)

    Gaafar, M.S.; Abdeen, Mostafa A.M.; Marzouk, S.Y.

    2011-01-01

    Research highlights: → Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). → The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb 5+ ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. → Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. → The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb 2 O 5 -(1 - x)TeO 2 , 0.1PbO-xNb 2 O 5 -(0.9 - x)TeO 2 , 0.2PbO-xNb 2 O 5 -(0.8 - x)TeO 2 and 0.05Bi 2 O 3 -xNb 2 O 5 -(0.95 - x)TeO 2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb 2 O 5 as a network modifier provides oxygen ions to change [TeO 4 ] tbps into [TeO 3 ] tps.

  5. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    Energy Technology Data Exchange (ETDEWEB)

    Gaafar, M.S., E-mail: mohamed_s_gaafar@hotmail.com [Ultrasonic Department, National Institute for Standards, Giza (Egypt); Physics Department, Faculty of Science, Majmaah University, Zulfi (Saudi Arabia); Abdeen, Mostafa A.M., E-mail: mostafa_a_m_abdeen@hotmail.com [Dept. of Eng. Math. and Physics, Faculty of Eng., Cairo University, Giza (Egypt); Marzouk, S.Y., E-mail: samir_marzouk2001@yahoo.com [Arab Academy of Science and Technology, Al-Horria, Heliopolis, Cairo (Egypt)

    2011-02-24

    Research highlights: > Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). > The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb{sup 5+} ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. > Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. > The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb{sub 2}O{sub 5}-(1 - x)TeO{sub 2}, 0.1PbO-xNb{sub 2}O{sub 5}-(0.9 - x)TeO{sub 2}, 0.2PbO-xNb{sub 2}O{sub 5}-(0.8 - x)TeO{sub 2} and 0.05Bi{sub 2}O{sub 3}-xNb{sub 2}O{sub 5}-(0.95 - x)TeO{sub 2} were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb{sub 2}O{sub 5} as a network modifier provides oxygen ions to change [TeO{sub 4}] tbps into [TeO{sub 3}] tps.

  6. Devices development and techniques research for space life sciences

    Science.gov (United States)

    Zhang, A.; Liu, B.; Zheng, C.

    The development process and the status quo of the devices and techniques for space life science in China and the main research results in this field achieved by Shanghai Institute of Technical Physics SITP CAS are reviewed concisely in this paper On the base of analyzing the requirements of devices and techniques for supporting space life science experiments and researches one designment idea of developing different intelligent modules with professional function standard interface and easy to be integrated into system is put forward and the realization method of the experiment system with intelligent distributed control based on the field bus are discussed in three hierarchies Typical sensing or control function cells with certain self-determination control data management and communication abilities are designed and developed which are called Intelligent Agents Digital hardware network system which are consisted of the distributed Agents as the intelligent node is constructed with the normative opening field bus technology The multitask and real-time control application softwares are developed in the embedded RTOS circumstance which is implanted into the system hardware and space life science experiment system platform with characteristic of multitasks multi-courses professional and instant integration will be constructed

  7. Two intelligent spraying systems developed for tree crop production

    Science.gov (United States)

    Precision pesticide application technologies are needed to achieve efficient and effective spray deposition on target areas and minimize off-target losses. Two variable-rate intelligent sprayers were developed as an introduction of new generation sprayers for tree crop applications. The first spraye...

  8. Development of Intelligent Spray Systems for Nursery Crop Production

    Science.gov (United States)

    Two intelligent sprayer prototypes were developed to increase pesticide application efficiency in nursery production. The first prototype was a hydraulic vertical boom system using ultrasonic sensors to detect tree size and volume for liner-sized trees and the second prototype was an air-assisted sp...

  9. Emotional Intelligence Research within Human Resource Development Scholarship

    Science.gov (United States)

    Farnia, Forouzan; Nafukho, Fredrick Muyia

    2016-01-01

    Purpose: The purpose of this study is to review and synthesize pertinent emotional intelligence (EI) research within the human resource development (HRD) scholarship. Design/methodology/approach: An integrative review of literature was conducted and multiple electronic databases were searched to find the relevant resources. Using the content…

  10. Supporting Social Interaction in Intelligent Competence Development Systems

    NARCIS (Netherlands)

    Sereno, Bertrand; Boursinou, Eleni; Maxwell, Katrina; Angehrn, Albert

    2007-01-01

    Sereno, B., Boursinou, E., Maxwell, K., & Angehrn, A. A. (2007). Supporting Social Interaction in Intelligent Competence Development Systems. In D. Griffiths, R. Koper & O. Liber (Eds.), Proceedings of the 2nd TENCompetence Open Workshop (pp. 29-35). January, 11-12, 2007, Manchester, United Kingdom.

  11. Emotionally Intelligent Learner Leadership Development: A Case Study

    Science.gov (United States)

    Jansen, C. A.; Moosa, S. O.; van Niekerk, E. J.; Muller, H.

    2014-01-01

    A case study was conducted with a student leadership body of a private multicultural international secondary school in North-West Province , South Africa, to indicate that the emotional intelligence leadership development challenges of student leaders can be identified through a questionnaire as a measuring instrument, which can then be utilized…

  12. Emotionally intelligent learner leadership development: a case study ...

    African Journals Online (AJOL)

    A case study was conducted with a student leadership body of a private multicultural international secondary school in North- West Province , South Africa, to indicate that the emotional intelligence leadership development challenges of student leaders can be identified through a questionnaire as a measuring instrument, ...

  13. ATC enhancement using TCSC via artificial intelligent techniques

    International Nuclear Information System (INIS)

    Rashidinejad, M.; Gharaveisi, A.A.; Farahmand, H.; Fotuhi-Firuzabad, M.

    2008-01-01

    Procurement of optimum available transfer capability (ATC) in the restructured electricity industry is a crucial challenge with regards to open access to transmission network. This paper presents an approach to determine the optimum location and optimum capacity of TCSC in order to improve ATC as well as voltage profile. Real genetic algorithm (RGA) associated with analytical hierarchy process (AHP) and fuzzy sets are implemented as a hybrid heuristic technique in this paper to optimize such a complicated problem. The effectiveness of the proposed methodology is examined through different case studies. (author)

  14. Using intelligent clustering techniques to classify the energy performance of school buildings

    Energy Technology Data Exchange (ETDEWEB)

    Santamouris, M.; Sfakianaki, K.; Papaglastra, M.; Pavlou, C.; Doukas, P.; Geros, V.; Assimakopoulos, M.N.; Zerefos, S. [University of Athens, Department of Physics, Division of Applied Physics, Laboratory of Meteorology, Athens (Greece); Mihalakakou, G.; Gaitani, N. [University of Ioannina, Department of Environmental and Natural Resources Management, Agrinio (Greece); Patargias, P. [University of Peloponnesus, Faculty of Human Sciences and Cultural Studies, Department of History, Kalamata (Greece); Primikiri, E. [University of Patras, Department of Architecture, Patras (Greece); Mitoula, R. [Charokopion University of Athens, Athens (Greece)

    2007-07-01

    The present paper deals with the energy performance, energy classification and rating and the global environmental quality of school buildings. A new energy classification technique based on intelligent clustering methodologies is proposed. Energy rating of school buildings provides specific information on their energy consumption and efficiency relative to the other buildings of similar nature and permits a better planning of interventions to improve its energy performance. The overall work reported in the present paper, is carried out in three phases. During the first phase energy consumption data have been collected through energy surveys performed in 320 schools in Greece. In the second phase an innovative energy rating scheme based on fuzzy clustering techniques has been developed, while in the third phase, 10 schools have been selected and detailed measurements of their energy efficiency and performance as well as of the global environmental quality have been performed using a specific experimental protocol. The proposed energy rating method has been applied while the main environmental and energy problems have been identified. The potential for energy and environmental improvements has been assessed. (author)

  15. A Review and Performance Investigation of NPCC Based UPQC by Using Various Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Venkata Rami Reddy K

    2017-03-01

    Full Text Available This paper presents a comprehensive review and performance investigation of Neutral Point Clamped Converter (NPCC based Unified Power Quality Conditioner (UPQC by using Artificial Intelligent (AI techniques. A Novel application of various levels of Diode Clamped Multi-Level Inverters [DCMLI] with Anti Phase Opposition and Disposition (APOD Pulse Width Modulation (PWM Scheme to Unified Power Quality Conditioner (UPQC. The Power Quality problem became a burning issues since the starting of high voltage AC transmission system. Hence, in this article it has been discussed to mitigate the PQ issues in high voltage AC systems through a three phase four wire Unified Power Quality Conditioner (UPQC under non-linear loads. The emphasised PQ problems such as voltage and current harmonics along with voltage sags and swells have also been discussed with improved performance. Also, it proposes to control the DCMLI based UPQC through conventional control schemes. Thus application of these control technique makes the system performance in par with the standards and also compared with existing system. The simulation results based on MATLAB/Simulink are discussed in detail to support the concept developed in the paper.

  16. Process sensors characterization based on noise analysis technique and artificial intelligence

    International Nuclear Information System (INIS)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos

    2005-01-01

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  17. Process sensors characterization based on noise analysis technique and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)]. E-mail: rnavarro@ipen.br; sperillo@ipen.br; rcsantos@ipen.br

    2005-07-01

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  18. Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

    Science.gov (United States)

    Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

    2018-04-01

    Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  19. Development of NPTC-11 intelligence control instrument with digital display

    International Nuclear Information System (INIS)

    Wang Chengming; Pu Li; Yu Jiang; Xue Yuping; Zhang Bo; Chen Yong

    2007-01-01

    The accurate of the process control gauge has direct influence on the safe operation of nuclear power plants. Therefore it is necessary to accumulate experiences for the domestic development of this Instrument. In this paper, NPTC-11 intelligence control Instrument with digital display is developed based on the design code for nuclear Instrument, considering the actual application requirements and technical redundancy. Its application in nuclear power plant for almost one year indicates that this Instrument satisfies the development purpose and requirements. (authors)

  20. An Intelligent Tutoring System for Learning Android Applications UI Development

    OpenAIRE

    Al Rekhawi , Hazem Awni; Abu Naser , Samy S

    2018-01-01

    International audience; The paper describes the design of a web based intelligent tutoring system for teaching Android Applications Development to students to overcome the difficulties they face. The basic idea of this system is a systematic introduction into the concept of Android Application Development. The system presents the topic of Android Application Development and administers automatically generated problems for the students to solve. The system is automatically adapted at run time ...

  1. Development of hybrid artificial intelligent based handover decision algorithm

    Directory of Open Access Journals (Sweden)

    A.M. Aibinu

    2017-04-01

    Full Text Available The possibility of seamless handover remains a mirage despite the plethora of existing handover algorithms. The underlying factor responsible for this has been traced to the Handover decision module in the Handover process. Hence, in this paper, the development of novel hybrid artificial intelligent handover decision algorithm has been developed. The developed model is made up of hybrid of Artificial Neural Network (ANN based prediction model and Fuzzy Logic. On accessing the network, the Received Signal Strength (RSS was acquired over a period of time to form a time series data. The data was then fed to the newly proposed k-step ahead ANN-based RSS prediction system for estimation of prediction model coefficients. The synaptic weights and adaptive coefficients of the trained ANN was then used to compute the k-step ahead ANN based RSS prediction model coefficients. The predicted RSS value was later codified as Fuzzy sets and in conjunction with other measured network parameters were fed into the Fuzzy logic controller in order to finalize handover decision process. The performance of the newly developed k-step ahead ANN based RSS prediction algorithm was evaluated using simulated and real data acquired from available mobile communication networks. Results obtained in both cases shows that the proposed algorithm is capable of predicting ahead the RSS value to about ±0.0002 dB. Also, the cascaded effect of the complete handover decision module was also evaluated. Results obtained show that the newly proposed hybrid approach was able to reduce ping-pong effect associated with other handover techniques.

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

    Science.gov (United States)

    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.

  3. Automatic Satellite Telemetry Analysis for SSA using Artificial Intelligence Techniques

    Science.gov (United States)

    Stottler, R.; Mao, J.

    In April 2016, General Hyten, commander of Air Force Space Command, announced the Space Enterprise Vision (SEV) (http://www.af.mil/News/Article-Display/Article/719941/hyten-announces-space-enterprise-vision/). The SEV addresses increasing threats to space-related systems. The vision includes an integrated approach across all mission areas (communications, positioning, navigation and timing, missile warning, and weather data) and emphasizes improved access to data across the entire enterprise and the ability to protect space-related assets and capabilities. "The future space enterprise will maintain our nation's ability to deliver critical space effects throughout all phases of conflict," Hyten said. Satellite telemetry is going to become available to a new audience. While that telemetry information should be valuable for achieving Space Situational Awareness (SSA), these new satellite telemetry data consumers will not know how to utilize it. We were tasked with applying AI techniques to build an infrastructure to process satellite telemetry into higher abstraction level symbolic space situational awareness and to initially populate that infrastructure with useful data analysis methods. We are working with two organizations, Montana State University (MSU) and the Air Force Academy, both of whom control satellites and therefore currently analyze satellite telemetry to assess the health and circumstances of their satellites. The design which has resulted from our knowledge elicitation and cognitive task analysis is a hybrid approach which combines symbolic processing techniques of Case-Based Reasoning (CBR) and Behavior Transition Networks (BTNs) with current Machine Learning approaches. BTNs are used to represent the process and associated formulas to check telemetry values against anticipated problems and issues. CBR is used to represent and retrieve BTNs that represent an investigative process that should be applied to the telemetry in certain circumstances

  4. Auto-correlation based intelligent technique for complex waveform presentation and measurement

    International Nuclear Information System (INIS)

    Rana, K P S; Singh, R; Sayann, K S

    2009-01-01

    Waveform acquisition and presentation forms the heart of many measurement systems. Particularly, data acquisition and presentation of repeating complex signals like sine sweep and frequency-modulated signals introduces the challenge of waveform time period estimation and live waveform presentation. This paper presents an intelligent technique, for waveform period estimation of both the complex and simple waveforms, based on the normalized auto-correlation method. The proposed technique is demonstrated using LabVIEW based intensive simulations on several simple and complex waveforms. Implementation of the technique is successfully demonstrated using LabVIEW based virtual instrumentation. Sine sweep vibration waveforms are successfully presented and measured for electrodynamic shaker system generated vibrations. The proposed method is also suitable for digital storage oscilloscope (DSO) triggering, for complex signals acquisition and presentation. This intelligence can be embodied into the DSO, making it an intelligent measurement system, catering wide varieties of the waveforms. The proposed technique, simulation results, robustness study and implementation results are presented in this paper.

  5. Artificial intelligence techniques for modeling database user behavior

    Science.gov (United States)

    Tanner, Steve; Graves, Sara J.

    1990-01-01

    The design and development of the adaptive modeling system is described. This system models how a user accesses a relational database management system in order to improve its performance by discovering use access patterns. In the current system, these patterns are used to improve the user interface and may be used to speed data retrieval, support query optimization and support a more flexible data representation. The system models both syntactic and semantic information about the user's access and employs both procedural and rule-based logic to manipulate the model.

  6. Empowering global software development with business intelligence

    OpenAIRE

    Maté Morga, Alejandro; Trujillo Mondéjar, Juan Carlos; García, Félix; Serrano Martín, Manuel; Piattini, Mario

    2016-01-01

    Context: Global Software Development (GSD) allows companies to take advantage of talent spread across the world. Most research has been focused on the development aspect. However, little if any attention has been paid to the management of GSD projects. Studies report a lack of adequate support for management’s decisions made during software development, further accentuated in GSD since information is scattered throughout multiple factories, stored in different formats and standards. Objective...

  7. Modeling and Control of Multivariable Process Using Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Subathra Balasubramanian

    2010-10-01

    Full Text Available For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani model and the other is Takagi–Sugeno model. Of these two, Takagi-Sugeno model (TS has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.

  8. Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

  9. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Kim, Han Gon; Chang, Soon Heung; Lee, Byung Ho

    1993-01-01

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

  10. Application of artificial intelligence techniques to reliability data banks

    International Nuclear Information System (INIS)

    Carlesso, S.; Barbas, T.; Capobianchi, S.; Koletsos, A.; Mancini, G.

    1987-01-01

    This paper refers to ERDS (European Reliability Data System) which contains data on operational behaviour of nuclear power reactors in Europe and in the USA. Information outages, incidents and component failures are organized in data base structures and handled with the ADABAS Data Base Management System; the system has been built up in the last six years at the JRC of the Commission of the European Communities and offers a good example of a complex technical data bank. The effective use of ERDS is difficult and requires a skilled specific experience. A feasibility study and a preliminary design have been carried out concerning the development of an expert interface to ERDS. This paper illustrates the main results of this work focusing in the types of problems involved in the design of an expert interface to a technical data bank and on the solutions proposed. The implementation of the expert interface to ERDS is presently in progress. (orig./HSCH)

  11. Finite-element-model updating using computational intelligence techniques applications to structural dynamics

    CERN Document Server

    Marwala, Tshilidzi

    2010-01-01

    Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

  12. Developing and Understanding Intelligent Contexts for Playing and Learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel; Helms, Niels Henrik

    2009-01-01

    of tangible learning media and develop didactic approaches for teachers in primary school and furthermore to use the user experiences in a structured process where children participated in the innovation process. This has raised a fundamental question: How should we understand the relationship between......This short paper outlines experiences and reflections on the research and development project “Octopus” in order to describe and illustrate how intelligent context facilitates and embody learning. The framework is a research and development project where we have tried to work with new kinds......, embodiment, intelligent contexts, structure and flow. This paper does this through Bachtins concept of “Chronotopos” or how time and space influence and structure experience and learning....

  13. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    Science.gov (United States)

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  14. Increasing the Intelligence of Virtual Sales Assistants through Knowledge Modeling Techniques

    OpenAIRE

    Molina, Martin

    2001-01-01

    Shopping agents are web-based applications that help consumers to find appropriate products in the context of e-commerce. In this paper we argue about the utility of advanced model-based techniques that recently have been proposed in the fields of Artificial Intelligence and Knowledge Engineering, in order to increase the level of support provided by this type of applications. We illustrate this approach with a virtual sales assistant that dynamically configures a product according to the nee...

  15. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  16. Combining NDE and fracture mechanics by artifical intelligence expert systems techniques

    International Nuclear Information System (INIS)

    Mucciardi, A.N.; Riccardella, P.C.

    1986-01-01

    This paper reports on the development of a PC-based expert system for non-destructive evaluation. Software tools from the expert systems subfield of artificial intelligence are being used to combine both NDE and fracture mechanics algorithms into one, unified package. The system incorporates elements of computer-enhanced ultrasonic signal processing, featuring artificial intelligence learning capability, state-of-the-art fracture mechanics analytical tools, and all relevant metallurgical and design data necessary to emulate the decisions of the panel(s) of experts typically involved in generating and dispositioning NDE data

  17. Intelligent postoperative morbidity prediction of heart disease using artificial intelligence techniques.

    Science.gov (United States)

    Hsieh, Nan-Chen; Hung, Lun-Ping; Shih, Chun-Che; Keh, Huan-Chao; Chan, Chien-Hui

    2012-06-01

    Endovascular aneurysm repair (EVAR) is an advanced minimally invasive surgical technology that is helpful for reducing patients' recovery time, postoperative morbidity and mortality. This study proposes an ensemble model to predict postoperative morbidity after EVAR. The ensemble model was developed using a training set of consecutive patients who underwent EVAR between 2000 and 2009. All data required for prediction modeling, including patient demographics, preoperative, co-morbidities, and complication as outcome variables, was collected prospectively and entered into a clinical database. A discretization approach was used to categorize numerical values into informative feature space. Then, the Bayesian network (BN), artificial neural network (ANN), and support vector machine (SVM) were adopted as base models, and stacking combined multiple models. The research outcomes consisted of an ensemble model to predict postoperative morbidity after EVAR, the occurrence of postoperative complications prospectively recorded, and the causal effect knowledge by BNs with Markov blanket concept.

  18. Implications of intelligent, integrated microsystems for product design and development

    International Nuclear Information System (INIS)

    MYERS, DAVID R.; MCWHORTER, PAUL J.

    2000-01-01

    Intelligent, integrated microsystems combine some or all of the functions of sensing, processing information, actuation, and communication within a single integrated package, and preferably upon a single silicon chip. As the elements of these highly integrated solutions interact strongly with each other, the microsystem can be neither designed nor fabricated piecemeal, in contrast to the more familiar assembled products. Driven by technological imperatives, microsystems will best be developed by multi-disciplinary teams, most likely within the flatter, less hierarchical organizations. Standardization of design and process tools around a single, dominant technology will expedite economically viable operation under a common production infrastructure. The production base for intelligent, integrated microsystems has elements in common with the mathematical theory of chaos. Similar to chaos theory, the development of microsystems technology will be strongly dependent on, and optimized to, the initial product requirements that will drive standardization--thereby further rewarding early entrants to integrated microsystem technology

  19. Developments in functional neuroimaging techniques

    International Nuclear Information System (INIS)

    Aine, C.J.

    1995-01-01

    A recent review of neuroimaging techniques indicates that new developments have primarily occurred in the area of data acquisition hardware/software technology. For example, new pulse sequences on standard clinical imagers and high-powered, rapidly oscillating magnetic field gradients used in echo planar imaging (EPI) have advanced MRI into the functional imaging arena. Significant developments in tomograph design have also been achieved for monitoring the distribution of positron-emitting radioactive tracers in the body (PET). Detector sizes, which pose a limit on spatial resolution, have become smaller (e.g., 3--5 mm wide) and a new emphasis on volumetric imaging has emerged which affords greater sensitivity for determining locations of positron annihilations and permits smaller doses to be utilized. Electromagnetic techniques have also witnessed growth in the ability to acquire data from the whole head simultaneously. EEG techniques have increased their electrode coverage (e.g., 128 channels rather than 16 or 32) and new whole-head systems are now in use for MEG. But the real challenge now is in the design and implementation of more sophisticated analyses to effectively handle the tremendous amount of physiological/anatomical data that can be acquired. Furthermore, such analyses will be necessary for integrating data across techniques in order to provide a truly comprehensive understanding of the functional organization of the human brain

  20. Development of intelligent simulations at LLNL

    Energy Technology Data Exchange (ETDEWEB)

    Cunningham, C.T.

    1994-03-01

    The Virtual Commander Project (VCom) is developing a capability for semiautomated optimal control of simulation entities. Properties of our control paradigm are goal-directed planning, hierarchical plan generation, automated fault detection, adaptive plan repair, and optimized cooperation and coordination among units, in addition to more conventional rule-driven behaviors. VCom has been applied to planning armor engagements at the battalion level and below. We are currently investigating movement-to-contact and fire-and-movement maneuvers. These capabilities will be demonstrated in April in conjunction with the Joint Conflict Model (JCM) a large, entity-level, constructive combat simulation. Both simulations have been developed to interoperate in a distributed computing environment using Distributed Interactive Simulation (DIS) protocols. Prototype applications have been demonstrated in other civilian and military contexts. A focus of our current work is the rapid prototyping of such applications.

  1. Development and validity of mathematical learning assessment instruments based on multiple intelligence

    Directory of Open Access Journals (Sweden)

    Helmiah Suryani

    2017-06-01

    Full Text Available This study was aimed to develop and produce an assessment instrument of mathematical learning results based on multiple intelligence. The methods in this study used Borg & Gall-Research and Development approach (Research & Development. The subject of research was 289 students. The results of research: (1 Result of Aiken Analysis showed 58 valid items were between 0,714 to 0,952. (2 Result of the Exploratory on factor analysis indicated the instrument consist of three factors i.e. mathematical logical intelligence-spatial intelligence-and linguistic intelligence. KMO value was 0.661 df 0.780 sig. 0.000 with valid category. This research succeeded to developing the assessment instrument of mathematical learning results based on multiple intelligence of second grade in elementary school with characteristics of logical intelligence of mathematics, spatial intelligence, and linguistic intelligence.

  2. Identification of cataract and post-cataract surgery optical images using artificial intelligence techniques.

    Science.gov (United States)

    Acharya, Rajendra Udyavara; Yu, Wenwei; Zhu, Kuanyi; Nayak, Jagadish; Lim, Teik-Cheng; Chan, Joey Yiptong

    2010-08-01

    Human eyes are most sophisticated organ, with perfect and interrelated subsystems such as retina, pupil, iris, cornea, lens and optic nerve. The eye disorder such as cataract is a major health problem in the old age. Cataract is formed by clouding of lens, which is painless and developed slowly over a long period. Cataract will slowly diminish the vision leading to the blindness. At an average age of 65, it is most common and one third of the people of this age in world have cataract in one or both the eyes. A system for detection of the cataract and to test for the efficacy of the post-cataract surgery using optical images is proposed using artificial intelligence techniques. Images processing and Fuzzy K-means clustering algorithm is applied on the raw optical images to detect the features specific to three classes to be classified. Then the backpropagation algorithm (BPA) was used for the classification. In this work, we have used 140 optical image belonging to the three classes. The ANN classifier showed an average rate of 93.3% in detecting normal, cataract and post cataract optical images. The system proposed exhibited 98% sensitivity and 100% specificity, which indicates that the results are clinically significant. This system can also be used to test the efficacy of the cataract operation by testing the post-cataract surgery optical images.

  3. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  4. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  5. Automating Commercial Video Game Development using Computational Intelligence

    OpenAIRE

    Tse G. Tan; Jason Teo; Patricia Anthony

    2011-01-01

    Problem statement: The retail sales of computer and video games have grown enormously during the last few years, not just in United States (US), but also all over the world. This is the reason a lot of game developers and academic researchers have focused on game related technologies, such as graphics, audio, physics and Artificial Intelligence (AI) with the goal of creating newer and more fun games. In recent years, there has been an increasing interest in game AI for pro...

  6. Reviewing the development of an artificial intelligence based risk program

    International Nuclear Information System (INIS)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    A successful application of nonconventional programming methods has been achieved in computer-assisted probabilistic risk assessment (PRA). The event tree sequence importance calculator, SQUIMP, provides for prompted data entry, generic expansion, on-line pruning, boolean reductions, and importance factor selection. SQUIMP employs constructs typically found in artificial intelligence (AI) programs. The development history of SQUIMP is outlined and its internal structure described as background for a discussion on the applicability of symbolic programming methods in PRA

  7. Monitoring osseointegration and developing intelligent systems (Conference Presentation)

    Science.gov (United States)

    Salvino, Liming W.

    2017-05-01

    Effective monitoring of structural and biological systems is an extremely important research area that enables technology development for future intelligent devices, platforms, and systems. This presentation provides an overview of research efforts funded by the Office of Naval Research (ONR) to establish structural health monitoring (SHM) methodologies in the human domain. Basic science efforts are needed to utilize SHM sensing, data analysis, modeling, and algorithms to obtain the relevant physiological and biological information for human-specific health and performance conditions. This overview of current research efforts is based on the Monitoring Osseointegrated Prosthesis (MOIP) program. MOIP develops implantable and intelligent prosthetics that are directly anchored to the bone of residual limbs. Through real-time monitoring, sensing, and responding to osseointegration of bones and implants as well as interface conditions and environment, our research program aims to obtain individualized actionable information for implant failure identification, load estimation, infection mitigation and treatment, as well as healing assessment. Looking ahead to achieve ultimate goals of SHM, we seek to expand our research areas to cover monitoring human, biological and engineered systems, as well as human-machine interfaces. Examples of such include 1) brainwave monitoring and neurological control, 2) detecting and evaluating brain injuries, 3) monitoring and maximizing human-technological object teaming, and 4) closed-loop setups in which actions can be triggered automatically based on sensors, actuators, and data signatures. Finally, some ongoing and future collaborations across different disciplines for the development of knowledge automation and intelligent systems will be discussed.

  8. Intelligent fracture creation for shale gas development

    KAUST Repository

    Douglas, Craig C.

    2011-05-14

    Shale gas represents a major fraction of the proven reserves of natural gas in the United States and a collection of other countries. Higher gas prices and the need for cleaner fuels provides motivation for commercializing shale gas deposits even though the cost is substantially higher than traditional gas deposits. Recent advances in horizontal drilling and multistage hydraulic fracturing, which dramatically lower costs of developing shale gas fields, are key to renewed interest in shale gas deposits. Hydraulically induced fractures are quite complex in shale gas reservoirs. Massive, multistage, multiple cluster treatments lead to fractures that interact with existing fractures (whether natural or induced earlier). A dynamic approach to the fracturing process so that the resulting network of reservoirs is known during the drilling and fracturing process is economically enticing. The process needs to be automatic and done in faster than real-time in order to be useful to the drilling crews.

  9. The strategy for intelligent integrated instrumentation and control system development

    International Nuclear Information System (INIS)

    Kwon, Kee Choon; Ham, Chang Shik

    1995-01-01

    All of the nuclear power plants in Korea are operating with analog instrumentation and control ( I and C) equipment which are increasingly faced with frequent troubles, obsolescence and high maintenance expenses. Electrical and computer technology has improved rapidly in recent years and has been applied to other industries. So it is strongly recommended we adopt modern digital and computer technology to improve plant safety and availability. The advanced I and C system, namely, Integrated Intelligent Instrumentation and Control System (I 3 Cs) will be developed for beyond the next generation nuclear power plant. I 3 CS consists of three major parts, the advanced compact workstation, distributed digital control and protection system including Automatic Start-up/Shutdown Intelligent Control System (ASICS) and the computer-based alarm processing and operator support system, namely, Diagnosis, Response, and operator Aid Management System (DREAMS)

  10. Development of an intelligent ultrasonic welding defect classification software

    International Nuclear Information System (INIS)

    Song, Sung Jin; Kim, Hak Joon; Jeong, Hee Don

    1997-01-01

    Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments.

  11. Short-term Local Forecasting by Artificial Intelligence Techniques and Assess Related Social Effects from Heterogeneous Data

    OpenAIRE

    Gong, Bing

    2017-01-01

    This work aims to use the sophisticated artificial intelligence and statistic techniques to forecast pollution and assess its social impact. To achieve the target of the research, this study is divided into several research sub-objectives as follows: First research sub-objective: propose a framework for relocating and reconfiguring the existing pollution monitoring networks by using feature selection, artificial intelligence techniques, and information theory. Second research sub-objective: c...

  12. Utilization of artificial intelligence techniques for the Space Station power system

    Science.gov (United States)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  13. Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

  14. Northeast Artificial Intelligence Consortium Annual Report. 1988 Interference Techniques for Knowledge Base Maintenance Using Logic Programming Methodologies. Volume 11

    Science.gov (United States)

    1989-10-01

    Northeast Aritificial Intelligence Consortium (NAIC). i Table of Contents Execu tive Sum m ary...o g~nIl ’vLr COPY o~ T- RADC-TR-89-259, Vol XI (of twelve) N Interim Report SOctober 1989 NORTHEAST ARTIFICIAL INTELLIGENCE CONSORTIUM ANNUAL REPORT...ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Northeast Artificial (If applicable) Intelligence Consortium (NAIC) . Rome Air Development

  15. Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

    Science.gov (United States)

    Taylan, Osman

    2017-02-01

    High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

  16. Some developments in safeguards techniques

    International Nuclear Information System (INIS)

    Beets, C.

    1977-01-01

    The fundamental principles of safeguards and the research and development of safeguards techniques are described. Safeguard accountancy based upon the partition of the fuel cycle into suitable material balance areas will be further improved. Implementation of international safeguards in the European fuel fabrication and reprocessing facilities is described. The effectiveness of a material accounting system depends on the quality of the quantitative data. The allocation of the tasks in the framework of an integrated safeguards is concerned with R and D work only and has no bearing on the allocation of the implementation costs. Bulk measurements, sampling and destructive or non-destructive analysis of samples are described for the determination of batch data. Testing of the safeguards techniques as a keystone in relation to plant instrumentation programmes are still being developed throughout the world. In addition to accountancy and control, it also includes an effective physical security program. The system of international safeguards that prevailed in the sixties has been re-modelled to comply with the new requirements of the Non-Proliferation Treaty and with the growth of nuclear energy

  17. Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

    CERN Document Server

    Demetriadis, Stavros; Xhafa, Fatos

    2012-01-01

    Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

  18. Development of an Intelligent System to Synthesize Petrophysical Well Logs

    Directory of Open Access Journals (Sweden)

    Morteza Nouri Taleghani

    2013-07-01

    Full Text Available Porosity is one of the fundamental petrophysical properties that should be evaluated for hydrocarbon bearing reservoirs. It is a vital factor in precise understanding of reservoir quality in a hydrocarbon field. Log data are exceedingly crucial information in petroleum industries, for many of hydrocarbon parameters are obtained by virtue of petrophysical data. There are three main petrophysical logging tools for the determination of porosity, namely neutron, density, and sonic well logs. Porosity can be determined by the use of each of these tools; however, a precise analysis requires a complete set of these tools. Log sets are commonly either incomplete or unreliable for many reasons (i.e. incomplete logging, measurement errors, and loss of data owing to unsuitable data storage. To overcome this drawback, in this study several intelligent systems such as fuzzy logic (FL, neural network (NN, and support vector machine are used to predict synthesized petrophysical logs including neutron, density, and sonic. To accomplish this, the petrophysical well logs data were collected from a real reservoir in one of Iran southwest oil fields. The corresponding correlation was obtained through the comparison of synthesized log values with real log values. The results showed that all intelligent systems were capable of synthesizing petrophysical well logs, but SVM had better accuracy and could be used as the most reliable method compared to the other techniques.

  19. Developing an Intelligent Automatic Appendix Extraction Method from Ultrasonography Based on Fuzzy ART and Image Processing

    Directory of Open Access Journals (Sweden)

    Kwang Baek Kim

    2015-01-01

    Full Text Available Ultrasound examination (US does a key role in the diagnosis and management of the patients with clinically suspected appendicitis which is the most common abdominal surgical emergency. Among the various sonographic findings of appendicitis, outer diameter of the appendix is most important. Therefore, clear delineation of the appendix on US images is essential. In this paper, we propose a new intelligent method to extract appendix automatically from abdominal sonographic images as a basic building block of developing such an intelligent tool for medical practitioners. Knowing that the appendix is located at the lower organ area below the bottom fascia line, we conduct a series of image processing techniques to find the fascia line correctly. And then we apply fuzzy ART learning algorithm to the organ area in order to extract appendix accurately. The experiment verifies that the proposed method is highly accurate (successful in 38 out of 40 cases in extracting appendix.

  20. Developments in medical imaging techniques

    International Nuclear Information System (INIS)

    Kramer, Cornelis

    1979-01-01

    A review of the developments in medical imaging in the past 25 years shows a strong increase in the number of physical methods which have become available for obtaining images of diagnostic value. It is shown that despite this proliferation of methods the equipment used for obtaining the images can be based on a common structure. Also the resulting images can be characterized by a few relevant parameters which indicate their information content. On the basis of this common architecture a study is made of the potential capabilities of the large number of medical imaging techniques available now and in the future. Also the requirements and possibilities for handling the images obtained and for controlling the diagnostic systems are investigated [fr

  1. Urban Big Data and the Development of City Intelligence

    OpenAIRE

    Pan, Yunhe; Tian, Yun; Liu, Xiaolong; Gu, Dedao; Hua, Gang

    2016-01-01

    This study provides a definition for urban big data while exploring its features and applications of China's city intelligence. The differences between city intelligence in China and the “smart city” concept in other countries are compared to highlight and contrast the unique definition and model for China's city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intelligence by showing that it not only serves as the cornerstone of this trend as it...

  2. DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

    OpenAIRE

    KÖSE, Utku

    2018-01-01

    Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

  3. Ubiquitous and Ambient Intelligence Assisted Learning Environment Infrastructures Development--A Review

    Science.gov (United States)

    Kanagarajan, Sujith; Ramakrishnan, Sivakumar

    2018-01-01

    Ubiquitous Learning Environment (ULE) has been becoming a mobile and sensor based technology equipped environment that suits the modern world education discipline requirements for the past few years. Ambient Intelligence (AmI) makes much smarter the ULE by the support of optimization and intelligent techniques. Various efforts have been so far…

  4. Construction of Intelligence Knowledge Map for Complex Product Development

    Directory of Open Access Journals (Sweden)

    Yan-jie LV,

    2013-11-01

    Full Text Available The complex product design and development is an integrated discipline. A lot of knowledge overloads and knowledge trek phenomenon appeared with the raise of product complexity and the explosion of knowledge and information. To improve the utilization efficiency of the knowledge using and shorten the time and effort spent on the Knowledge screening, avoid missing the knowledge, which is required, the paper proposes a method for the intelligence knowledge map construct model based on knowledge requirements and knowledge connection. Analyzing the context information of the user and giving the method of acquiring the knowledge requirement based on the context information and the user’s personal knowledge structure. This method can get the knowledge requirements of the users to generate the knowledge retrieval expressions to obtain the knowledge points and then construct the intelligent knowledge map through the analysis of multiple dimensions and using the knowledge related to the development of aircraft landing gear as an example to verify the feasibility of this method.

  5. Development of Android Based Powered Intelligent Wheelchair for Quadriplegic Persons

    Science.gov (United States)

    Gupta, Ashutosh; Ghosh, Tathagata; Kumar, Pradeep; Bhawna, Shruthi. S.

    2017-08-01

    Several surveys give us the view that both children and adults benefit substantially from access towards independent mobility. With the inventions of technology, no individuals are satisfied with traditional manual operated machines. To accommodate population, researchers are using technology, originally developed for mobile robots to create ‘intelligent wheelchairs’. It’s a major challenge for quadriplegic persons as they really find it difficult to manipulate powered wheelchair during the activities of their daily living. As the Smartphone era has evolved with innovative android based applications, engineers are improving and trying to make such machines simple and cheap to the next level. In this paper, we present a development of android based powered intelligent wheelchair to assist the quadriplegic person by making them self sufficient in controlling the wheelchair. The wheels of the chair can be controlled by the voice or gesture movement or by touching the screen of the android app by the challenged persons. The system uses the Bluetooth communication to interface the microcontroller and the inbuilt sensors in the android Smartphone. According to the commands received from android phone, the kinematics of the wheels are controlled.

  6. The Objectives of Competitive Intelligence as a Part of Corporative Development Strategy

    Directory of Open Access Journals (Sweden)

    František Bartes

    2014-01-01

    Full Text Available This paper deals with the issue of the management cycle of Competitive Intelligence. The author describes the process of Competitive Intelligence in Czech corporate management. He concludes that in most cases, the Competitive Intelligence operations are directed by the top management, and the attention of Competitive Intelligence is being paid to Key Intelligence Topics (KIT. The Competitive Intelligence is then focused on the output of strategic analyses, complemented in some cases with a summary (synthesis of acquired intelligence plus some signal intelligence (SIGINT. The results of the Competitive Intelligence produced in such a way are actually the outputs mostly applicable in operational management and mostly unsuitable for strategic management. However, top managers abroad almost invariably need the data relevant to the future situation since their decisions are of strategic nature. The following section of the paper is devoted to the conceptual solution of Competitive Intelligence, i.e. the Competitive Intelligence objectives linked with the development strategy of the corporation. Here the author arrives at three basic development strategies: a. the corporation desires status quo, i.e. to keep its market position as it is, b. the corporation is out to expand, and c. the corporation intends not only to keep its existing and dominant market position but strives for its long-term dominance to last.

  7. REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Chitra

    2013-07-01

    Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

  8. Problem Space Matters: The Development of Creativity and Intelligence in Primary School Children

    Science.gov (United States)

    Welter, Marisete Maria; Jaarsveld, Saskia; Lachmann, Thomas

    2017-01-01

    Previous research showed that in primary school, children's intelligence develops continually, but creativity develops more irregularly. In this study, the development of intelligence, measured traditionally, i.e., operating within well-defined problem spaces (Standard Progressive Matrices) was compared with the development of intelligence…

  9. Development of brief versions of the Wechsler Intelligence Scale for schizophrenia: considerations of the structure and predictability of intelligence.

    Science.gov (United States)

    Sumiyoshi, Chika; Uetsuki, Miki; Suga, Motomu; Kasai, Kiyoto; Sumiyoshi, Tomiki

    2013-12-30

    Short forms (SF) of the Wechsler Intelligence Scale have been developed to enhance its practicality. However, only a few studies have addressed the Wechsler Intelligence Scale Revised (WAIS-R) SFs based on data from patients with schizophrenia. The current study was conducted to develop the WAIS-R SFs for these patients based on the intelligence structure and predictability of the Full IQ (FIQ). Relations to demographic and clinical variables were also examined on selecting plausible subtests. The WAIS-R was administered to 90 Japanese patients with schizophrenia. Exploratory factor analysis (EFA) and multiple regression analysis were conducted to find potential subtests. EFA extracted two dominant factors corresponding to Verbal IQ and Performance IQ measures. Subtests with higher factor loadings on those factors were initially nominated. Regression analysis was carried out to reach the model containing all the nominated subtests. The optimality of the potential subtests included in that model was evaluated from the perspectives of the representativeness of intelligence structure, FIQ predictability, and the relation with demographic and clinical variables. Taken together, the dyad of Vocabulary and Block Design was considered to be the most optimal WAIS-R SF for patients with schizophrenia, reflecting both intelligence structure and FIQ predictability. © 2013 Elsevier Ireland Ltd. All rights reserved.

  10. Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

    Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

  11. The effect of an emotional intelligence development programme on accountants

    Directory of Open Access Journals (Sweden)

    Cara S. Jonker

    2009-09-01

    Full Text Available The  objective  of  this  research was to compile and  evaluate  a development programme  aimed at emotional  intelligence (EI  in the accounting profession. A two-group design (pre- and post-test was used. An accidental  sample  (experimental and control group was taken from future employees within a financial management environment. The  BarOn-EQ-i was administered and further data were gathered qualitatively by means of diary entries. The results showed an improvement in total EI level. The specific areas of EI that were developed due to the programme included the following subscales: interpersonal, adaptability and general mood. The specific EI factors that showed improvement included self-regard, self-actualisation, interpersonal relations, reality testing, problem solving, flexibility, stress tolerance and optimism.

  12. Further development of NPP surveillance and diagnostic systems by use of intelligent technologies

    International Nuclear Information System (INIS)

    Wach, D.; Ding, Y.

    1998-01-01

    Recent development work at ISTec/GRS has been directed to more automation of surveillance techniques by utilization of the technological progress and existing tools. Neural nets, fuzzy techniques and rule-based methods were investigated for application in feature classification and automated identification of anomalies. First applications were aimed at classification of useful patterns and suppression of non-relevant signal components in order to avoid false alarms (e.g. in acoustic monitoring) and at signal validation under normal and disturbed plant conditions. Other on-going projects are aimed at the application of the successful methods to other surveillance tasks such as on-line assessment of sensor behaviour and ageing phenomena of instrumentation. The paper gives an insight in the intelligent analysis techniques and highlights their potential use for other surveillance tasks in nuclear power plants. (author)

  13. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

    Science.gov (United States)

    Poonamallee, Latha; Harrington, Alex M.; Nagpal, Manisha; Musial, Alec

    2018-01-01

    Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies. PMID:29527182

  14. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence

    Directory of Open Access Journals (Sweden)

    Latha Poonamallee

    2018-02-01

    Full Text Available Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI. The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

  15. Improving Emotional Intelligence through Personality Development: The Effect of the Smart Phone Application based Dharma Life Program on Emotional Intelligence.

    Science.gov (United States)

    Poonamallee, Latha; Harrington, Alex M; Nagpal, Manisha; Musial, Alec

    2018-01-01

    Emotional intelligence is established to predict success in leadership effectiveness in various contexts and has been linked to personality factors. This paper introduces Dharma Life Program, a novel approach to improving emotional intelligence by targeting maladaptive personality traits and triggering neuroplasticity through the use of a smart-phone application and mentoring. The program uses neuroplasticity to enable users to create a more adaptive application of their maladaptive traits, thus improving their emotional intelligence. In this study 26 participants underwent the Dharma Life Program in a leadership development setting. We assessed their emotional and social intelligence before and after the Dharma Life Program intervention using the Emotional and Social Competency Inventory (ESCI). The study found a significant improvement in the lowest three competencies and a significant improvement in almost all domains for the entire sample. Our findings suggest that the completion of the Dharma Life Program has a significant positive effect on Emotional and Social Competency scores and offers a new avenue for improving emotional intelligence competencies.

  16. The Development of Financial Information System and Business Intelligence Using Data Mining Concepts

    OpenAIRE

    PVD PRASAD

    2014-01-01

    One of the most emerging technologies is finance, becoming more amenable to data-driven modeling as large sets of financial data become available everywhere. So we are applying the data mining techniques in financial information system with Business Intelligence. A Business Intelligence System (BIS) can be described as an interactive, computer-based system designed to help decision-makers to solve unstructured problems. Using a combination of models, analytical techniques, and...

  17. Intelligent Technique for Signal Processing to Identify the Brain Disorder for Epilepsy Captures Using Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Gurumurthy Sasikumar

    2016-01-01

    Full Text Available The new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. Simultaneously for the efficient clustering method the convergence criteria are set. On the whole the proposed technique yields more accurate results and that gives an edge over other techniques. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm.

  18. The Study on the Effect of Educational Games for the Development of Students’ Logic-Mathematics of Multiple Intelligence

    Science.gov (United States)

    Li, Jing; Ma, Sujuan; Ma, Linqing

    Firstly, in this article, we expound the theory of the educational games and multiple intelligence and analyze the relationship between them. Then, further, we elaborate educational games' effect on the development of students' multiple intelligence, taking logic-mathematics intelligence for example. Also, we discuss the strategies of using educational games to improve students' intelligence. In a word, we can use the computer games to develop the students' multi-intelligence.

  19. Development of an intelligent annunciation system for nuclear power plants

    International Nuclear Information System (INIS)

    Kim, Chang-Gi; Che, Myoung-Eun

    1997-01-01

    Yonggwang Nuclear Units 1 and 2 have developed an intelligent annunciation system to replace the existing obsolete system and to enhance operator support. The new annunciation system, which is currently operating at both units, uses the distributed control technology to enhance reliability and to provide versatile function to operations and maintenance personnel. The hardware and software configuration is based on redundancy so that a component failure would not initiate system malfunction. The data base of the new system provides, through a touch screen, an automatic alarm response procedure for selected alarms, which increases availability of information for plant operation. Other KEPCO nuclear units and the fossil plants are considering installing the new system. (author). 6 figs, 2 tabs

  20. Development of an intelligent annunciation system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang-Gi; Che, Myoung-Eun [Instrumentation and Control, Yonggwang Nuclear Units 1 and 2, Korea Electric Power Corp. (Korea, Republic of)

    1997-09-01

    Yonggwang Nuclear Units 1 and 2 have developed an intelligent annunciation system to replace the existing obsolete system and to enhance operator support. The new annunciation system, which is currently operating at both units, uses the distributed control technology to enhance reliability and to provide versatile function to operations and maintenance personnel. The hardware and software configuration is based on redundancy so that a component failure would not initiate system malfunction. The data base of the new system provides, through a touch screen, an automatic alarm response procedure for selected alarms, which increases availability of information for plant operation. Other KEPCO nuclear units and the fossil plants are considering installing the new system. (author). 6 figs, 2 tabs.

  1. Developing and Understanding Intelligent Contexts for Playing and Learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel; Helms, Niels Henrik

    of tangible learning media and develop didactic approaches for teachers in a primary school and furthermore to use the user experiences in a structured process where children participated in the innovation process. This has raised a fundamental question: How should we understand the relationship between....... This paper therefore aims at illustrating how and why the “Octopus” works and functions in a learning community (school) and discus the relations between distinctions, embodiment, intelligent contexts, structure and flow. This paper introduces a new reading of pervasive learning environments as the “Octopus......” through M.M. Bachtins concept of “Chronotopos” or how time and space influence and structure experience and learning.  We have adapted this theory that originally is about literature in order to find new ways of understanding the time and place relation in learning....

  2. Flexibility in the context of intelligent plant's development

    Directory of Open Access Journals (Sweden)

    Fernando Augusto Pereira

    2008-07-01

    Full Text Available Globalization and competition among companies bring changes in the product development, reducing increasingly its life's cycle. Corporations are opting to world-wide products platforms, with global strategies. Besides the wider vision about corporative strategies, dynamic markets and strong competition are impacting in the medium and short term companies' demands. All these characteristics create turbulences in the organizations, but they can also convey opportunities. In order to take strategic advantage in this process, companies ought to innovate, changing the manner of planning and operating its plants. One possibility to achieve these goals is using flexibility in the manufacture. In this paper, flexibility aspects will be addressed in context of band, reply and dimension, and, how companies can apply this benefit to get better design in their plants and manufacture process, and eliminate waste. Key-words: Flexibility, Toyota Production System, Lean Manufacturing, Intelligent Plants, Wastes’ elimination.

  3. Artificial intelligence search techniques for optimization of the cold source geometry

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

  4. Artificial intelligence search techniques for the optimization of cold source geometry

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness that produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometric shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape, which is the unknown in such a study. An analogy is drawn between this problem and a state space search, then a simple artificial intelligence (AI) search technique is used to determine the optimum cold source shape based on a two-group, r-z diffusion model. This AI design concept was implemented in the computer program AID, which consists of two modules, a physical model module, and a search module, which can be independently modified, improved, or made more sophisticated

  5. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    Tong, S.S.; Powell, D.; Goel, S.

    1992-02-01

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  6. Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

    International Nuclear Information System (INIS)

    Pallas, Christophe

    1987-01-01

    The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author) [fr

  7. Intelligent Search Method Based ACO Techniques for a Multistage Decision Problem EDP/LFP

    Directory of Open Access Journals (Sweden)

    Mostefa RAHLI

    2006-07-01

    Full Text Available The implementation of a numerical library of calculation based optimization in electrical supply networks area is in the centre of the current research orientations, thus, our project in a form given is centred on the development of platform NMSS1. It's a software environment which will preserve many efforts as regards calculations of charge, smoothing curves, losses calculation and economic planning of the generated powers [23].The operational research [17] in a hand and the industrial practice in the other, prove that the means and processes of simulation reached a level of very appreciable reliability and mathematical confidence [4, 5, 14]. It is of this expert observation that many processes make confidence to the results of simulation.The handicaps of this approach or methodology are that it makes base its judgments and handling on simplified assumptions and constraints whose influence was deliberately neglected to be added to the cost to spend [14].By juxtaposing the methods of simulation with artificial intelligence techniques, gathering set of numerical methods acquires an optimal reliability whose assurance can not leave doubt.Software environment NMSS [23] can be a in the field of the rallying techniques of simulation and electric network calculation via a graphic interface. In the same software integrate an AI capability via a module expert system.Our problem is a multistage case where are completely dependant and can't be performed separately.For a multistage problem [21, 22], the results obtained from a credible (large size problem calculation, makes the following question: Could choice of numerical methods set make the calculation of a complete problem using more than two treatments levels, a total error which will be the weakest one possible? It is well-known according to algorithmic policy; each treatment can be characterized by a function called mathematical complexity. This complexity is in fact a coast (a weight overloading

  8. Competitive Intelligence.

    Science.gov (United States)

    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…

  9. Developing Students' Cultural Intelligence through an Experiential Learning Activity: A Cross-Cultural Consumer Behavior Interview

    Science.gov (United States)

    Kurpis, Lada Helen; Hunter, James

    2017-01-01

    Business schools can increase their competitiveness by offering students intercultural skills development opportunities integrated into the traditional curricula. This article makes a contribution by proposing an approach to developing students' cultural intelligence that is based on the cultural intelligence (CQ) model, experiential learning…

  10. The Development, Testing, and Evaluation of an Emotional Intelligence Curriculum.

    Science.gov (United States)

    Fischer, Ronald G.; Fischer, Jerome M.

    2003-01-01

    Adult students using an emotional intelligence (EI) curriculum (n=13) and 15 controls in a composition class completed the Emotional Intelligence Test and Emotional Content Quality Index. Significant pre- to posttest changes in the EI group suggest the curriculum positively increased their ability to identify, reflect on, process, and manage…

  11. Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2017-01-01

    Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds. Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Robust intelligent backstepping tracking control for uncertain non-linear chaotic systems using H∞ control technique

    International Nuclear Information System (INIS)

    Peng, Y.-F.

    2009-01-01

    The cerebellar model articulation controller (CMAC) is a non-linear adaptive system with built-in simple computation, good generalization capability and fast learning property. In this paper, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive CMAC and H ∞ control technique is proposed for a class of chaotic systems with unknown system dynamics and external disturbance. In the proposed control system, an adaptive backstepping cerebellar model articulation controller (ABCMAC) is used to mimic an ideal backstepping control (IBC), and a robust H ∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the RIBTC system are derived based on the Lyapunov stability analysis, the Taylor linearization technique and H ∞ control theory, so that the stability of the closed-loop system and H ∞ tracking performance can be guaranteed. Finally, three application examples, including a Duffing-Holmes chaotic system, a Genesio chaotic system and a Sprott circuit system, are used to demonstrate the effectiveness and performance of proposed robust control technique.

  13. Leading nurses: emotional intelligence and leadership development effectiveness.

    Science.gov (United States)

    Crowne, Kerri Anne; Young, Thomas M; Goldman, Beryl; Patterson, Barbara; Krouse, Anne M; Proenca, Jose

    2017-07-03

    Purpose The purpose of this paper is to examine the effectiveness of an emotional intelligence (EI) and leadership development education program involving 20 nurse leaders at nursing homes. Also, it investigates the relationship between EI and transformational leadership. Design/methodology/approach Three research questions are posed. Correlation analysis and t-tests were conducted to answer the questions posed. Findings The findings of this paper indicate that the EI educational development was effective, while the personal leadership development was not. The data also showed a positive significant relationship between EI and transformational leadership. Research limitations/implications This paper is limited by the small sample size; thus, a causal relationship between EI and leadership could not be investigated. Additionally, the sample was not randomly selected because of the commitment needed from the participants. Furthermore, the paper was focused on nurse leaders in nursing homes, so it may not be generalizable to other populations. Practical implications With the increasing need for nursing home facilities and the limited training generally provided to nurses who move into managerial roles in these facilities, it is critical for organizations to understand the effectiveness of educational programs that exist. Moreover, the findings of this paper may provide information that would be useful to others who wish to develop EI and/or leadership education for nurses. Originality/value While much research exists on EI and transformational leadership, little of this research focuses on nurses in nursing home facilities. Thus, this paper fills a gap in the literature.

  14. Development and Testing of Intelligent Alcohol Transportation Security System

    Directory of Open Access Journals (Sweden)

    Velaphi Msomi

    2018-01-01

    Full Text Available The development and testing of intelligent liquid transportation security system are being reported in this paper. The targeted fluid to be secured was ethanol alcohol and this was due to the theft cases occurring during the transportation of this product from the supplier to the customer. The system was developed such that only the radar level sensor (VEGAPULS 62 might be in contact with the fluid and the rest of the system remained outside the liquid carrying container to be secured. The system was developed such that it reports any abnormal liquid level drop through short message service (SMS. The functioning of the developed system was tested through the use of 1040 L Intermediate Bulk Container (IBC filled with water which was hauled for about 1.5 km. The liquid theft was simulated and the system sent two SMS. The first SMS reported the beginning of water level drop and the second one reported the ending of water level drop. The second SMS reported the amount of liquid that was taken out of the container.

  15. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

  16. Developing Emotionally Intelligent Leadership: The Need for Deliberate Practice and Collaboration across Disciplines

    Science.gov (United States)

    Allen, Scott J.; Shankman, Marcy Levy; Haber-Curran, Paige

    2016-01-01

    This chapter continues the discussion of what leadership education is and highlights the importance of emotionally intelligent leadership. The authors assert the need for deliberate practice and better collaboration between student affairs, academic affairs, and academic departments to develop emotionally intelligent leaders.

  17. Development of the Distinct Multiple Intelligences in Primary Students through Interest Centers

    Science.gov (United States)

    Dueñas Macías, Fredy Alonso

    2013-01-01

    This article reports on an action research study that focused on developing the distinct multiple intelligences of an English class of fifth graders through interest centers at a Colombian school. A multiple intelligences questionnaire, an open-ended observation form, and a student mini-report sheet were used to collect data. Findings revealed…

  18. Exploring the Impact of Sports Participation on Multiple Intelligence Development of High School Female Students

    Science.gov (United States)

    Kul, Marat

    2015-01-01

    After Gardner had introduced the Multiple Intelligence (MI) theory, many researchers tried to find out the possibilities of applying this theory in the education domain. Moreover, the effects of different kinds of athletic applications on intelligence development within the framework of this theory have also been under investigation. This study…

  19. Basic research on intelligent robotic systems operating in hostile environments: New developments at ORNL

    International Nuclear Information System (INIS)

    Barhen, J.; Babcock, S.M.; Hamel, W.R.; Oblow, E.M.; Saridis, G.N.; deSaussure, G.; Solomon, A.D.; Weisbin, C.R.

    1984-01-01

    Robotics and artificial intelligence research carried out within the Center for Engineering Systems Advanced Research (CESAR) is presented. Activities focus on the development and demonstration of a comprehensive methodological framework for intelligent machines operating in unstructured hostile environments. Areas currently being addressed include mathematical modeling of robot dynamics, real-time control, ''world'' modeling, machine perception and strategy planning

  20. Applying of artificial intelligence in the textile industry as factor of innovative development of the branch

    OpenAIRE

    Yuldashev N.; Tursunov B.

    2018-01-01

    In the article, the authors carried out a theoretical analysis of the practical applications of artificial intelligence in various fields. It is concluded that the use of artificial intelligence in the textile industry, in particular in management, will serve as a jerk to the innovative development of the industry.

  1. Analysis on the Chinese Urban Sustainable Development Demands for the Management Plan of Intelligent Transportation Systems

    Institute of Scientific and Technical Information of China (English)

    赵历男

    2002-01-01

    This article analyzes the demands of the sustainable development and Chinese urban environmental protection for the management plan of intelligent transportation systems. The article also comments on how to work out the management plan of intelligent transportation systems with China's own characteristics.

  2. Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

    2014-05-01

    This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

  3. Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions

    Science.gov (United States)

    Beskow, Samuel; de Mello, Carlos Rogério; Vargas, Marcelle M.; Corrêa, Leonardo de L.; Caldeira, Tamara L.; Durães, Matheus F.; de Aguiar, Marilton S.

    2016-10-01

    Information on stream flows is essential for water resources management. The stream flow that is equaled or exceeded 90% of the time (Q90) is one the most used low stream flow indicators in many countries, and its determination is made from the frequency analysis of stream flows considering a historical series. However, stream flow gauging network is generally not spatially sufficient to meet the necessary demands of technicians, thus the most plausible alternative is the use of hydrological regionalization. The objective of this study was to couple the artificial intelligence techniques (AI) K-means, Partitioning Around Medoids (PAM), K-harmonic means (KHM), Fuzzy C-means (FCM) and Genetic K-means (GKA), with measures of low stream flow seasonality, for verification of its potential to delineate hydrologically homogeneous regions for the regionalization of Q90. For the performance analysis of the proposed methodology, location attributes from 108 watersheds situated in southern Brazil, and attributes associated with their seasonality of low stream flows were considered in this study. It was concluded that: (i) AI techniques have the potential to delineate hydrologically homogeneous regions in the context of Q90 in the study region, especially the FCM method based on fuzzy logic, and GKA, based on genetic algorithms; (ii) the attributes related to seasonality of low stream flows added important information that increased the accuracy of the grouping; and (iii) the adjusted mathematical models have excellent performance and can be used to estimate Q90 in locations lacking monitoring.

  4. Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

    Energy Technology Data Exchange (ETDEWEB)

    Tan, C.K.; Wilcox, S.J.; Ward, J. [University of Glamorgan, Pontypridd (United Kingdom). Division of Mechanical Engineering

    2006-03-15

    The optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance. Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficiently for a large number of iterations as required by optimisation techniques based on Evolutionary Algorithms (EAs). Four operating parameters of the burner, namely the swirl angles and flow rates of the secondary and tertiary combustion air were optimised with the objective of minimising the NOx and CO emissions as well as the unburned carbon at the furnace exit. The results suggest that ANNs combined with EAs provide a useful tool for optimising co-combustion processes.

  5. Development of an intelligent controller for power generators

    International Nuclear Information System (INIS)

    Maxted, Clive; Waller, Winston

    2005-01-01

    This paper is a description of the development of an embedded controller for high power industrial diesel generators. The aim of the project was to replace the existing discrete logic design by an intelligent versatile and user configurable control system. A prototype embedded PC controlled system was developed, capable of fully replacing the existing system, with a colour TFT display and keypad. Features include fully automatic generator control as before with status and alarm display and monitoring of engine parameters, along with data logging, remote communications and a means of analysing data. The unit was tested on the bench and on diesel generators for the core controlling functionality to prove compliance with the specifications. The results of the testing proved the unit's suitability as a replacement for the existing system in its intended environment. The significance of this study is that a low cost replacement solution has been found for an industrial application by transferring modern technological knowledge to a small business. The company are now able to build on the design and take it into production, reducing servicing and production costs

  6. Developing a market-sensitive intelligent transportation systems educational program

    Science.gov (United States)

    1997-01-01

    Results of research undertaken to evaluate the educational needs of the emerging field of Intelligent Transportation Systems (ITSs) are presented, and whether course offerings in academic programs meet these needs is ascertained. A survey was conduct...

  7. Developing an intelligent transportation systems (ITS) architecture for the KIPDA region : final report.

    Science.gov (United States)

    2004-08-01

    This report describes the development of a regional Intelligent Transportation Systems (ITS) Architecture for the five-county urban area under the auspices of the Kentuckiana Regional Planning and Development Agency (KIPDA). The architecture developm...

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

    Science.gov (United States)

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

    2014-01-01

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

  9. Simulation of radionuclide chemistry and sorption characteristics in the geosphere by artificial intelligence technique

    International Nuclear Information System (INIS)

    Liu Shangjyh; National Tsing Hua Univ., Hsinchu; Wang Shigang; Ho Liwei

    1988-01-01

    An expert system operated in a personal computer is employed to simulate chemistry and sorption phenomena of radionuclides in the geosphere. The system handles both qualitative and quantitative analyses primarily for the actinides and fission products. The system also incorporates data bases of several groundwater and rock types with mineral and chemical compositions, the distribution coefficients of nuclides for minerals, etc. The decision rule base facilitates this system to carry out the reasoning procedures to predict the solubility-limiting phase, solute species, oxidation states and possible complex formations of radionuclides, as well as to calculate the distribution coefficients and retardation factors in a geological formation, provided that the essential groundwater and host rock information are available. It is concluded that this device of artificial intelligence provides a vehicle to accumulate developed human knowledge and serves as a tool not only for simulating the complicated radionuclide behaviour in the geosphere, but also for instructional or educational purpose in this field. (orig.)

  10. Intelligent environmental sensing

    CERN Document Server

    Mukhopadhyay, Subhas

    2015-01-01

    Developing environmental sensing and monitoring technologies become essential especially for industries that may cause severe contamination. Intelligent environmental sensing uses novel sensor techniques, intelligent signal and data processing algorithms, and wireless sensor networks to enhance environmental sensing and monitoring. It finds applications in many environmental problems such as oil and gas, water quality, and agriculture. This book addresses issues related to three main approaches to intelligent environmental sensing and discusses their latest technological developments. Key contents of the book include:   Agricultural monitoring Classification, detection, and estimation Data fusion Geological monitoring Motor monitoring Multi-sensor systems Oil reservoirs monitoring Sensor motes Water quality monitoring Wireless sensor network protocol  

  11. Recent developments in building diagnosis techniques

    CERN Document Server

    2016-01-01

    This book presents a collection of recent research on building diagnosis techniques related to construction pathology, hygrothermal behavior and durability, and diagnostic techniques. It highlights recent advances and new developments in the field of building physics, building anomalies in materials and components, new techniques for improved energy efficiency analysis, and diagnosis techniques such as infrared thermography. This book will be of interest to a wide readership of professionals, scientists, students, practitioners, and lecturers.

  12. Developing a civic intelligence: local involvement in HIA

    International Nuclear Information System (INIS)

    Elliott, Eva; Williams, Gareth

    2004-01-01

    Public involvement and participation in policy development and implementation is becoming an increasingly prominent feature of social life. However, as politics and policy become ever more concerned with 'evidence,' the relationship between 'expert evidence' and political judgements and decisions becomes ever more complicated. For this reason, public participation increasingly has to mean inclusion in arguments about information, evidence and knowledge as much as it means straightforward involvement in decision making. Such involvement can involve critical questioning of a kind that can challenge and sometimes debunk experts' claims to privileged understanding. One practical arena in which knowledge-based policy and politics is being expressed is in health impact assessment (HIA). This paper describes a health impact assessment of housing options in a former mining village in South Wales in order to illustrate the contributions that local people can make to both evidence and decision making. This case study exemplifies an emerging civic intelligence that challenges a traditional demarcation between different forms of expertise and creates public spaces that provide the basis for new opportunities of democratic renewal

  13. Development of SYVAC sampling techniques

    International Nuclear Information System (INIS)

    Prust, J.O.; Dalrymple, G.J.

    1985-04-01

    This report describes the requirements of a sampling scheme for use with the SYVAC radiological assessment model. The constraints on the number of samples that may be taken is considered. The conclusions from earlier studies using the deterministic generator sampling scheme are summarised. The method of Importance Sampling and a High Dose algorithm, which are designed to preferentially sample in the high dose region of the parameter space, are reviewed in the light of experience gained from earlier studies and the requirements of a site assessment and sensitivity analyses. In addition the use of an alternative numerical integration method for estimating risk is discussed. It is recommended that the method of Importance Sampling is developed and tested for use with SYVAC. An alternative numerical integration method is not recommended for investigation at this stage but should be the subject of future work. (author)

  14. PHILOSOPHICAL AND ANTHROPOLOGICAL IMPORTANCE OF DEVELOPMENT OF ARTIFICIALLY CREATED INTELLIGENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. D. Gensitskiy

    2015-12-01

    Full Text Available Purpose. Understanding the philosophical and anthropological importance of the development the artificial intelligence systems requires the analysis of the socio and anthropological content of intercomputer problems of interaction in the context of media philosophical praxis, anthropological maintenance of intellect nature, considering the specifics of the concept of artificial intelligence systems in the environment of M2M development of socio-cognitive practices of intercomputer interaction of social and humanitarian potential. Methodology. The implementation target is seen in the use of scientific and theoretical basis of the media philosophical, philosophical anthropology, the media philosophical approach to understanding society, science and technology, the use of publications on selected topics of research. Scientific novelty. The concept of artificial intelligence systems in the aspect of social and humanitarian potential of their formation and development in the environment of M2M was considered. The problems of machine learning as technology transformation M2M were analysed. The anthropological threats to the development of artificially created intelligent systems were defined. Conclusions. From the global risks point of view, one of the most critical circumstances due to the artificial intelligent system can strengthen its intelligence very quickly. The obvious reason for suspecting such an opportunity – a recursive self-improvement. Such system becomes smarter, including the intelligent writing of internal cognitive function, that the ability to rewrite their existing cognitive function to make it work better. This will make such systems more intelligent, and smarter in terms of the processing itself. The success of artificial intelligence may be the beginning of the end of the human race. Almost any technology falling into malicious hands reveals the potential for harm, but when it comes to artificial intelligent system, there is a

  15. Pathogenesis-based treatments in primary Sjogren's syndrome using artificial intelligence and advanced machine learning techniques: a systematic literature review.

    Science.gov (United States)

    Foulquier, Nathan; Redou, Pascal; Le Gal, Christophe; Rouvière, Bénédicte; Pers, Jacques-Olivier; Saraux, Alain

    2018-05-17

    Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade. An automatic bibliography screening method has been developed to perform this task. The program called BIBOT was designed to fetch and analyze articles from the pubmed database using a list of keywords and Natural Language Processing approaches. The evolution of trends in statistical approaches, sizes of cohorts and number of publications over this period were also computed in the process. In all, 44077 abstracts were screened and 1017 publications were analyzed. The mean number of selected articles was 101.0 (S.D. 19.16) by year, but increased significantly over the time (from 74 articles in 2008 to 138 in 2017). Among them only 12 focused on pSS but none of them emphasized on the aspect of pathogenesis-based treatments. To conclude, medicine progressively enters the era of big data analysis and artificial intelligence, but these approaches are not yet used to describe pSS-specific pathogenesis-based treatment. Nevertheless, large multicentre studies are investigating this aspect with advanced algorithmic tools on large cohorts of SADs patients.

  16. The development of a JCH-3a intelligent precision thickness meter

    International Nuclear Information System (INIS)

    He Fengqi; Chen Lin

    1988-12-01

    Plating and coating technique are more widely used along with the development of the material science and industry. A precision, real-time and non-distructive testing method is established and a digitized and intelligent thickness meter JCH-3a is developed for measuring the layer thickness. The JCH-3a meter consists of a high accurate probe, very large scale integrated circuits and a built-in microcomputer. Its special features are: 1. digital display of the measured data; 2. preseting the limitation of warning values and automatic storing the measured data; 3. output of printing data; 4. broad measuring range; 5. small in size and light in weight. It can be also used in the thickness measuring of the reactor components

  17. Sleep spindling and fluid intelligence across adolescent development: sex matters

    Directory of Open Access Journals (Sweden)

    Róbert eBódizs

    2014-11-01

    Full Text Available Evidence supports the intricate relationship between sleep electroencephalogram (EEG spindling and cognitive abilities in children and adults. Although sleep EEG changes during adolescence index fundamental brain reorganization, a detailed analysis of sleep spindling and the spindle-intelligence relationship was not yet provided for adolescents. Therefore, adolescent development of sleep spindle oscillations were studied in a home polysomnographic study focusing on the effects of chronological age and developmentally acquired overall mental efficiency (fluid IQ with sex as a potential modulating factor. Subjects were 24 healthy adolescents (12 males with an age range of 15–22 years (mean: 18 years and fluid IQ of 91-126 (mean: 104.12, Raven Progressive Matrices Test. Slow spindles (SSs and fast spindles (FSs were analyzed in 21 EEG derivations by using the individual adjustment method. A significant age-dependent increase in average FS density (r = .57; p = .005 was found. Moreover, fluid IQ correlated with FS density (r = .43; p = .04 and amplitude (r = .41; p = .049. The latter effects were entirely driven by particularly reliable FS-IQ correlations in females [r = .80 (p = .002 and r = .67 (p = .012, for density and amplitude, respectively]. Region-specific analyses revealed that these correlations peak in the fronto-central regions. The control of the age-dependence of FS measures and IQ scores did not considerably reduce the spindle-IQ correlations with respect to FS density. The only positive spindle-index of fluid IQ in males turned out to be the frequency of FSs (r = .60, p = .04. Increases in FS density during adolescence may index reshaped structural connectivity related to white matter maturation in the late developing human brain. The continued development over this age range of cognitive functions is indexed by specific measures of sleep spindling unravelling gender differences in adolescent brain maturation and perhaps cognitive

  18. An evolutionary algorithm technique for intelligence, surveillance, and reconnaissance plan optimization

    Science.gov (United States)

    Langton, John T.; Caroli, Joseph A.; Rosenberg, Brad

    2008-04-01

    To support an Effects Based Approach to Operations (EBAO), Intelligence, Surveillance, and Reconnaissance (ISR) planners must optimize collection plans within an evolving battlespace. A need exists for a decision support tool that allows ISR planners to rapidly generate and rehearse high-performing ISR plans that balance multiple objectives and constraints to address dynamic collection requirements for assessment. To meet this need we have designed an evolutionary algorithm (EA)-based "Integrated ISR Plan Analysis and Rehearsal System" (I2PARS) to support Effects-based Assessment (EBA). I2PARS supports ISR mission planning and dynamic replanning to coordinate assets and optimize their routes, allocation and tasking. It uses an evolutionary algorithm to address the large parametric space of route-finding problems which is sometimes discontinuous in the ISR domain because of conflicting objectives such as minimizing asset utilization yet maximizing ISR coverage. EAs are uniquely suited for generating solutions in dynamic environments and also allow user feedback. They are therefore ideal for "streaming optimization" and dynamic replanning of ISR mission plans. I2PARS uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to automatically generate a diverse set of high performing collection plans given multiple objectives, constraints, and assets. Intended end users of I2PARS include ISR planners in the Combined Air Operations Centers and Joint Intelligence Centers. Here we show the feasibility of applying the NSGA-II algorithm and EAs in general to the ISR planning domain. Unique genetic representations and operators for optimization within the ISR domain are presented along with multi-objective optimization criteria for ISR planning. Promising results of the I2PARS architecture design, early software prototype, and limited domain testing of the new algorithm are discussed. We also present plans for future research and development, as well as technology

  19. Using Intelligent Techniques in Construction Project Cost Estimation: 10-Year Survey

    Directory of Open Access Journals (Sweden)

    Abdelrahman Osman Elfaki

    2014-01-01

    Full Text Available Cost estimation is the most important preliminary process in any construction project. Therefore, construction cost estimation has the lion’s share of the research effort in construction management. In this paper, we have analysed and studied proposals for construction cost estimation for the last 10 years. To implement this survey, we have proposed and applied a methodology that consists of two parts. The first part concerns data collection, for which we have chosen special journals as sources for the surveyed proposals. The second part concerns the analysis of the proposals. To analyse each proposal, the following four questions have been set. Which intelligent technique is used? How have data been collected? How are the results validated? And which construction cost estimation factors have been used? From the results of this survey, two main contributions have been produced. The first contribution is the defining of the research gap in this area, which has not been fully covered by previous proposals of construction cost estimation. The second contribution of this survey is the proposal and highlighting of future directions for forthcoming proposals, aimed ultimately at finding the optimal construction cost estimation. Moreover, we consider the second part of our methodology as one of our contributions in this paper. This methodology has been proposed as a standard benchmark for construction cost estimation proposals.

  20. Epileptic seizure predictors based on computational intelligence techniques: a comparative study with 278 patients.

    Science.gov (United States)

    Alexandre Teixeira, César; Direito, Bruno; Bandarabadi, Mojtaba; Le Van Quyen, Michel; Valderrama, Mario; Schelter, Bjoern; Schulze-Bonhage, Andreas; Navarro, Vincent; Sales, Francisco; Dourado, António

    2014-05-01

    The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known as refractory epilepsy. This extensive study in seizure prediction considers the 278 patients from the European Epilepsy Database, collected in three epilepsy centres: Hôpital Pitié-là-Salpêtrière, Paris, France; Universitätsklinikum Freiburg, Germany; Centro Hospitalar e Universitário de Coimbra, Portugal. For a considerable number of patients it was possible to find a patient specific predictor with an acceptable performance, as for example predictors that anticipate at least half of the seizures with a rate of false alarms of no more than 1 in 6 h (0.15 h⁻¹). We observed that the epileptic focus localization, data sampling frequency, testing duration, number of seizures in testing, type of machine learning, and preictal time influence significantly the prediction performance. The results allow to face optimistically the feasibility of a patient specific prospective alarming system, based on machine learning techniques by considering the combination of several univariate (single-channel) electroencephalogram features. We envisage that this work will serve as benchmark data that will be of valuable importance for future studies based on the European Epilepsy Database. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Performance analysis of visible light communication using the STBC-OFDM technique for intelligent transportation systems

    Science.gov (United States)

    Li, Changping; Yi, Ying; Lee, Kyujin; Lee, Kyesan

    2014-08-01

    Visible light communication (VLC) applied in an intelligent transportation system (ITS) has attracted growing attentions, but it also faces challenges, for example deep path loss and optical multi-path dispersion. In this work, we modelled an actual outdoor optical channel as a Rician channel and further proposed space-time block coding (STBC) orthogonal frequency-division multiplexing (OFDM) technology to reduce the influence of severe optical multi-path dispersion associated with such a mock channel for achieving the effective BER of 10-6 even at a low signal-to-noise ratio (SNR). In this case, the optical signals transmission distance can be extended as long as possible. Through the simulation results of STBC-OFDM and single-input-single-output (SISO) counterparts in bit error rate (BER) performance comparison, we can distinctly observe that the VLC-ITS system using STBC-OFDM technique can obtain a strongly improved BER performance due to multi-path dispersion alleviation.

  2. The development report of an intelligent neutron fluence integration monitor

    International Nuclear Information System (INIS)

    Jiang Zongbing; Wei Ying

    1996-10-01

    An intelligent neutron fluence integration monitor is introduced. It is used to measure the received neutron fluence of the monocrystalline silicon in reactor radiation channel. The significance of study and specifications of the instrument are briefly described. The emphasis is on the working principle, structure and characteristics of the instrument is intelligent due to use of monolithic microcomputer. It has many advantages proved in the actual practice, such as powerful function, high accuracy, diversity of application, high level automatization, easy to operate, high reliability, etc. After using this instrument the monocrystalline silicon radiation technology is improved and the efficiency of production is raised. (1 fig.)

  3. Minimally Naturalistic Artificial Intelligence

    OpenAIRE

    Hansen, Steven Stenberg

    2017-01-01

    The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...

  4. Development of core thermal-hydraulics module for intelligent reactor design system (IRDS)

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Nakagawa, Masayuki; Fujii, Sadao.

    1994-08-01

    We have developed an innovative reactor core thermal-hydraulics module where a designer can easily and efficiently evaluate his design concept of a new type reactor in the thermal-hydraulics field. The main purpose of this module is to decide a feasible range of basic design parameters of a reactor core in a conceptual design stage of a new type reactor. The module is to be implemented in Intelligent Reactor Design System (IRDS). The module has the following characteristics; 1) to deal with several reactor types, 2) four thermal hydraulics and fuel behavior analysis codes are installed to treat different type of reactors and design detail, 3) to follow flexibly modification of a reactor concept, 4) to provide analysis results in an understandable way so that a designer can easily evaluate feasibility of his concept, and so on. The module runs on an engineering workstation (EWS) and has a user-friendly man-machine interface on a pre- and post-processing. And it is equipped with a function to search a feasible range called as Design Window, for two design parameters by artificial intelligence (AI) technique and knowledge engineering. In this report, structure, guidance for users of an usage of the module and instruction of input data for analysis modules are presented. (author)

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

    Science.gov (United States)

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

    2018-03-01

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

  6. Bio-Intelligence: A Research Program Facilitating the Development of New Paradigms for Tomorrow's Patient Care

    Science.gov (United States)

    Phan, Sieu; Famili, Fazel; Liu, Ziying; Peña-Castillo, Lourdes

    The advancement of omics technologies in concert with the enabling information technology development has accelerated biological research to a new realm in a blazing speed and sophistication. The limited single gene assay to the high throughput microarray assay and the laborious manual count of base-pairs to the robotic assisted machinery in genome sequencing are two examples to name. Yet even more sophisticated, the recent development in literature mining and artificial intelligence has allowed researchers to construct complex gene networks unraveling many formidable biological puzzles. To harness these emerging technologies to their full potential to medical applications, the Bio-intelligence program at the Institute for Information Technology, National Research Council Canada, aims to develop and exploit artificial intelligence and bioinformatics technologies to facilitate the development of intelligent decision support tools and systems to improve patient care - for early detection, accurate diagnosis/prognosis of disease, and better personalized therapeutic management.

  7. Concept development and needs identification for intelligent network flow optimization (INFLO) : concept of operations.

    Science.gov (United States)

    2012-06-01

    The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

  8. Concept development and needs identification for intelligent network flow optimization (INFLO) : test readiness assessment.

    Science.gov (United States)

    2012-11-01

    The purpose of this project is to develop for the Intelligent Network Flow Optimization (INFLO), which is one collection (or bundle) of high-priority transformative applications identified by the United States Department of Transportation (USDOT) Mob...

  9. Development of a Techno-economic Model of Intelligent Transportation System (ITS) for Deployment in Ghana

    DEFF Research Database (Denmark)

    Adjin, Daniel Michael Okwabi; Tadayoni, Reza

    2011-01-01

    The concept of Intelligent Transportation System (ITS) is about the development and deployment of advanced Traffic Management Systems, Traveler Information Systems, Commercial Vehicle Operations, Public and Private Transportation Systems, and Rural Transportation Systems. Several key technologies....... The results show that deployment of Intelligent Vehicle Tracking Technology (IVTT) will address the problems of inefficiencies experienced in the Ghanaian road transport haulage tracking industry. Research for ITS development and eployment in these countries should be cost effective....

  10. Intelligence and gender (in)equality: empirical evidence from developing countries

    OpenAIRE

    Salahodjaev, Raufhon; Azam, Sardor

    2015-01-01

    This paper makes an attempt to explore whether intelligence of nations is related to gender inequality, measured by Social Institutions and Gender Index (SIGI), in developing countries. Related literature robustly links intelligence to economic development, poverty, quality of institutions and informal economic activity. Controlling for conventional antecedents of gender inequality (i.e. religion, political regime, legal origins and trade openness), this paper finds that, on average, a 10-poi...

  11. ARGUMENTS ON USING COMPUTER-ASSISTED AUDIT TECHNIQUES (CAAT AND BUSINESS INTELLIGENCE TO IMPROVE THE WORK OF THE FINANCIAL AUDITOR

    Directory of Open Access Journals (Sweden)

    Ciprian-Costel, MUNTEANU

    2014-11-01

    Full Text Available In the 21st century, one of the most efficient ways to achieve an independent audit and quality opinion is by using information from the organization database, mainly documents in electronic format. With the help of Computer-Assisted Audit Techniques (CAAT, the financial auditor analyzes part or even all the data about a company in reference to other information within or outside the entity. The main purpose of this paper is to show the benefits of evolving from traditional audit techniques and tools to modern and , why not, visionary CAAT, which are supported by business intelligence systems. Given the opportunity to perform their work in IT environments, the auditors would start using the tools of business intelligence, a key factor which contributes to making successful business decisions . CAAT enable auditors to test large amount of data quickly and accurately and therefore increase the confidence they have in their opinion.

  12. A Multiagent Platform for Developments of Accounting Intelligent Applications

    Directory of Open Access Journals (Sweden)

    Adrian LUPAŞC

    2008-01-01

    Full Text Available AOP – Agent Oriented Programming – is a new software paradigm thatbrings many concepts from the artificial intelligence. This paper provides a shortoverview of the JADE software platform and the principal’s componentsconstituting its distributed architecture. Furthermore, it describes how to launch theplatform with the command–line options and how to experiment with the maingraphical tools of this platform.

  13. University Students' Development of Emotional Intelligence Skills for Leadership

    Science.gov (United States)

    Ramos-Villarreal, Joseph; Holland, Glenda

    2011-01-01

    The study was conducted to add to the knowledge base and further the understanding of Emotional Intelligence and leadership theory. Freshmen business students enrolled in BUAD 1201: Principles of Business Administration and graduating senior business students enrolled in MGMT 4325: Decision Making and Business Policy class provided the data for…

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

    Science.gov (United States)

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

    1993-06-01

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

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

    International Nuclear Information System (INIS)

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

    1993-01-01

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

  16. New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Bio-inspired intelligence is in the spotlight in the field of international artificial intelligence,and unmanned combat aerial vehicle(UCAV),owing to its potential to perform dangerous,repetitive tasks in remote and hazardous,is very promising for the technological leadership of the nation and essential for improving the security of society.On the basis of introduction of bioinspired intelligence and UCAV,a series of new development thoughts on UCAV control are proposed,including artificial brain based high-level autonomous control for UCAV,swarm intelligence based cooperative control for multiple UCAVs,hy-brid swarm intelligence and Bayesian network based situation assessment under complicated combating environments, bio-inspired hardware based high-level autonomous control for UCAV,and meta-heuristic intelligence based heterogeneous cooperative control for multiple UCAVs and unmanned combat ground vehicles(UCGVs).The exact realization of the proposed new development thoughts can enhance the effectiveness of combat,while provide a series of novel breakthroughs for the intelligence,integration and advancement of future UCAV systems.

  17. THE PSYCHODIAGNOSTICS OF THE EMOTIONAL INTELLIGENCE DEVELOPMENT OF INDIVIDUALS AT THE SENIOR SCHOOL AGE

    Directory of Open Access Journals (Sweden)

    I. V. Opanasyuk

    2015-03-01

    Full Text Available Background. The article deals with the phenomenon of “emotional intelligence” and its characteristic features at the senior school age. It is proved that the emotional intelligence enables senior pupils to reduce the impact of negative feelings with the help of the control over the situation and their emotions. The topicality of the problem is determined by the fact that the emotional intelligence is one of the prerequisites to the formation of the senior pupils’ personality, their ability to ensure and regulate the acquired experience, as well as the ability of self-identi?cation. Objective. The purpose of the study is to determine the level of the senior pupils’ emotional intelligence development, as well as to analyze the nature of the interrelation of its components. The set aim presupposes the ful?llment of the following tasks: 1 to analyze the content characteristic feature of the phenomenon of “emotional intelligence” and the levels of its development among the senior pupils; 2 to carry out the diagnostics of the development of the senior pupils’ emotional intelligence; 3 to identify the relationships between the emotional intelligence and its components on the basis of the empirical researches. Method. The research tasks have determined the sample of 420 pupils (15-17 years old representing various schools of the Ivano-Frankivsk region. The diagnostics of emotional barriers in interpersonal communication (V.V. Boyko; the diagnostics of emotional intelligence (N. Hall; the diagnostics of the emotional orientation of the individual (B.I. Dodonov; the emotional intelligence questionnaire “EmIn” (D.V. Lyusin. The mathematical processing of the above-mentioned test methods was conducted with the help of the correlation and factor analysis. Results. The research identi?es signi?cant relationships between the emotional intelligence components. The emotional intelligence correlates with understanding one’s own and others

  18. An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

    Science.gov (United States)

    Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

    2010-01-01

    Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use "flat" computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial confirmed to a large degree that

  19. Sleep spindling and fluid intelligence across adolescent development: sex matters.

    Science.gov (United States)

    Bódizs, Róbert; Gombos, Ferenc; Ujma, Péter P; Kovács, Ilona

    2014-01-01

    Evidence supports the intricate relationship between sleep electroencephalogram (EEG) spindling and cognitive abilities in children and adults. Although sleep EEG changes during adolescence index fundamental brain reorganization, a detailed analysis of sleep spindling and the spindle-intelligence relationship was not yet provided for adolescents. Therefore, adolescent development of sleep spindle oscillations were studied in a home polysomnographic study focusing on the effects of chronological age and developmentally acquired overall mental efficiency (fluid IQ) with sex as a potential modulating factor. Subjects were 24 healthy adolescents (12 males) with an age range of 15-22 years (mean: 18 years) and fluid IQ of 91-126 (mean: 104.12, Raven Progressive Matrices Test). Slow spindles (SSs) and fast spindles (FSs) were analyzed in 21 EEG derivations by using the individual adjustment method (IAM). A significant age-dependent increase in average FS density (r = 0.57; p = 0.005) was found. Moreover, fluid IQ correlated with FS density (r = 0.43; p = 0.04) and amplitude (r = 0.41; p = 0.049). The latter effects were entirely driven by particularly reliable FS-IQ correlations in females [r = 0.80 (p = 0.002) and r = 0.67 (p = 0.012), for density and amplitude, respectively]. Region-specific analyses revealed that these correlations peak in the fronto-central regions. The control of the age-dependence of FS measures and IQ scores did not considerably reduce the spindle-IQ correlations with respect to FS density. The only positive spindle-index of fluid IQ in males turned out to be the frequency of FSs (r = 0.60, p = 0.04). Increases in FS density during adolescence may index reshaped structural connectivity related to white matter maturation in the late developing human brain. The continued development over this age range of cognitive functions is indexed by specific measures of sleep spindling unraveling gender differences in adolescent brain maturation and perhaps

  20. A Three Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents

    Science.gov (United States)

    2006-10-01

    Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents. In Visualising Network...University at the start of each fall semester, when numerous new students arrive on campus and begin downloading extensive amounts of audio and...SIGGRAPH ’92 • C. Cruz-Neira, D.J. Sandin, T.A. DeFanti, R.V. Kenyon and J.C. Hart, "The CAVE: Audio Visual Experience Automatic Virtual Environment

  1. Intelligent techniques applied in identifying fraudsters industrial consumers of electricity; Tecnicas inteligentes aplicadas na identificacao de consumidores industriais fraudadores de energia eletrica

    Energy Technology Data Exchange (ETDEWEB)

    Ramos, Caio C.O.; Souza, Andre N. de; Pereira, Lucas I.; Gastaldello, Danilo S. [Universidade Estadual Paulista (UNESP), Bauru, SP (Brazil). Dept. de Engenharia Eletrica], Emails: caioramos@gmail.com, andrejau@feb.unesp.br, ra510611@feb.unesp.br, danilosg@feb.unesp.br; Zago, Maria G. [Universidade de Sao Paulo (EP/USP), SP (Brazil) Escola Politecnica], Email: mgzago@usp.br; Papa, Joao P. [Universidade Estadual Paulista (UNESP), Bauru, SP (Brazil). Dept. da Computacao], Email: papa.joaopaulo@gmail.com

    2009-07-01

    The development of a computational intelligent tools based on neural network to identify commercial losses or fraud (theft energy), considering information from a database electric utility, is presented.

  2. An analysis of the application of AI to the development of intelligent aids for flight crew tasks

    Science.gov (United States)

    Baron, S.; Feehrer, C.

    1985-01-01

    This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research.

  3. Application of data mining and artificial intelligence techniques to mass spectrometry data for knowledge discovery

    Directory of Open Access Journals (Sweden)

    Hugo López-Fernández

    2016-05-01

    Full Text Available Mass spectrometry using matrix assisted laser desorption ionization coupled to time of flight analyzers (MALDI-TOF MS has become popular during the last decade due to its high speed, sensitivity and robustness for detecting proteins and peptides. This allows quickly analyzing large sets of samples are in one single batch and doing high-throughput proteomics. In this scenario, bioinformatics methods and computational tools play a key role in MALDI-TOF data analysis, as they are able handle the large amounts of raw data generated in order to extract new knowledge and useful conclusions. A typical MALDI-TOF MS data analysis workflow has three main stages: data acquisition, preprocessing and analysis. Although the most popular use of this technology is to identify proteins through their peptides, analyses that make use of artificial intelligence (AI, machine learning (ML, and statistical methods can be also carried out in order to perform biomarker discovery, automatic diagnosis, and knowledge discovery. In this research work, this workflow is deeply explored and new solutions based on the application of AI, ML, and statistical methods are proposed. In addition, an integrated software platform that supports the full MALDI-TOF MS data analysis workflow that facilitate the work of proteomics researchers without advanced bioinformatics skills has been developed and released to the scientific community.

  4. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  5. Developing Intelligent System Dynamic Management Instruments on Water-Food-Energy Nexus in Response to Urbanization

    Science.gov (United States)

    Tsai, W. P.; Chang, F. J.; Lur, H. S.; Fan, C. H.; Hu, M. C.; Huang, T. L.

    2016-12-01

    Water, food and energy are the most essential natural resources needed to sustain life. Water-Food-Energy Nexus (WFE Nexus) has nowadays caught global attention upon natural resources scarcity and their interdependency. In the past decades, Taiwan's integrative development has undergone drastic changes due to population growth, urbanization and excessive utilization of natural resources. The research intends to carry out interdisciplinary studies on WFE Nexus based on data collection and analysis as well as technology innovation, with a mission to develop a comprehensive solution to configure the synergistic utilization of WFE resources in an equal and secure manner for building intelligent dynamic green cities. This study aims to establish the WFE Nexus through interdisciplinary research. This study will probe the appropriate and secure resources distribution and coopetition relationship by applying and developing techniques of artificial intelligence, system dynamics, life cycle assessment, and synergy management under data mining, system analysis and scenario analysis. The issues of synergy effects, economic benefits and sustainable social development will be evaluated as well. First, we will apply the system dynamics to identify the interdependency indicators of WFE Nexus in response to urbanization and build the dynamic relationship among food production, irrigation water resource and energy consumption. Then, we conduct comparative studies of WFE Nexus between the urbanization and the un-urbanization area (basin) to provide a referential guide for optimal resource-policy nexus management. We expect to the proposed solutions can help achieve the main goals of the research, which is the promotion of human well-being and moving toward sustainable green economy and prosperous society.

  6. Investigation and study on each technique and example of intelligent planning; Intelligent planning no kakushu shuho to jirei ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-11

    Various problems on intelligent planning (IP) and the tendency of basic technology were investigated. For each technique of IP, a Petri net and mark graph have been widely used as the modeling and analysis methods of a discrete event system. Moreover, various planning problems were modeled by a traveling salesman problem, and the efficient solution of the traveling salesman problem has been studied simultaneously. The tendency of the basic technology and application system viewed from an example of intelligent plant planning was investigated as an applied field of planning technology, with importance attached to the production system and robot planning. In the scheduling technology of the production system, the activation of an AI study and a new theory (i.e., architecture study) based on natural science information was investigated with the transition in the world as a trigger. A robot system has been planned in a wide range such as the environmental information acquisition planning of a robot. 202 refs., 69 figs., 4 tabs.

  7. Development of An Intelligent Flight Propulsion Control System

    Science.gov (United States)

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

    1999-01-01

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

  8. A Alternative Analog Circuit Design Methodology Employing Integrated Artificial Intelligence Techniques

    Science.gov (United States)

    Tuttle, Jeffery L.

    In consideration of the computer processing power now available to the designer, an alternative analog circuit design methodology is proposed. Computer memory capacities no longer require the reduction of the transistor operational characteristics to an imprecise formulation. Therefore, it is proposed that transistor modelling be abandoned in favor of fully characterized transistor data libraries. Secondly, availability of the transistor libraries would facilitate an automated selection of the most appropriate device(s) for the circuit being designed. More specifically, a preprocessor computer program to a more sophisticated circuit simulator (e.g. SPICE) is developed to assist the designer in developing the basic circuit topology and the selection of the most appropriate transistor. Once this is achieved, the circuit topology and selected transistor data library would be downloaded to the simulator for full circuit operational characterization and subsequent design modifications. It is recognized that the design process is enhanced by the use of heuristics as applied to iterative design results. Accordingly, an artificial intelligence (AI) interface is developed to assist the designer in applying the preprocessor results. To demonstrate the retrofitability of the AI interface to established programs, the interface is specifically designed to be as non-intrusive to the host code as possible. Implementation of the proposed methodology offers the potential to speed the design process, since the preprocessor both minimizes the required number of simulator runs and provides a higher acceptance potential of the initial and subsequent simulator runs. Secondly, part count reductions may be realizable since the circuit topologies are not as strongly driven by transistor limitations. Thirdly, the predicted results should more closely match actual circuit operations since the inadequacies of the transistor models have been virtually eliminated. Finally, the AI interface

  9. The development of working memory capacity and fluid intelligence in children

    OpenAIRE

    Engel de Abreu, Pascale; Gathercole, S; Conway, A

    2010-01-01

    A longitudinal study was conducted to investigate the relationship between working memory capacity and fluid intelligence and how this relationship develops in early childhood. The major aim was to determine which aspect of the working memory system – short-term storage or executive attention – drives the relationship with fluid intelligence. A sample of 119 children was followed from kindergarten to second grade and completed multiple assessments of short-term memory, wor...

  10. Developing technology intelligence strategy to access knowledge of innovation clusters.

    OpenAIRE

    Rani Jeanne Dang; Letizia Mortara; Ruth Thomson; Tim Minshall

    2010-01-01

    Current times are characterised by a knowledge-based economy and fast technological change. In this difficult environment, companies compete to maintain a relevant position through innovation. In response to these challenges, many companies are currently adopting an open approach to innovation, pursuing innovation by combining internal and external resources. Technology intelligence (TI) activities support the implementation of open innovation with the systematic capture and delivery of infor...

  11. Development and applications of microanalytical techniques

    International Nuclear Information System (INIS)

    Cholewa, M.

    2005-05-01

    The development of new analytical techniques is an essential part of our everyday life and is dictated by strong progress in modern science and technology. Both these areas require more precise information about materials and processes involved. Due to these requirements we have been observing a rapid growth in the development of techniques that require both a high spatial resolution and high sensitivity. Modern analytical techniques provide an important interface between science and applications. The works presented in this habilitation thesis span the period of almost 20 years. During this time the author has been leading the development and applications of several new analytical and micro analytical techniques which have been documented in this thesis. This development has required development of ideas, strong leadership, organisational skills, organisation of funds and groups to carry out the necessary work. In chapter 3 the use of the PIXE and XANES techniques described an investigation of permeability for selected elements inside cells. It was important to develop new protocols for sample preparation and analysis and a large number of cells were necessary in order to obtain meaningful data. This development was closely associated with work presented in chapter 4 where the role of sample damage under the MeV ion beam bombardment was investigated. At that time we were the leading group in the world to perform such studies. Chapter 5 describes development of new analytical techniques and its possible applications. Development of the SIHF has been probably the most demanding and difficult project and was described in chapter 6 and it was closely related with development of a diamond detector described in chapter 7. A great part of these works were performed by the author at the Micro Analytical Research Centre (MARC) in the School of Physics at the University of Melbourne in Australia. However, some works were performed at GSI in Germany and BNL in USA. (author)

  12. Developing and using artificial intelligence related to nuclear energy in Romania

    International Nuclear Information System (INIS)

    Ion, R.

    1995-01-01

    The artificial intelligence (AI) (including Expert Systems (ES), its most important branch) could have a certain place in the future developing of nuclear energy with impact on decision aids techniques and support systems, especially for nuclear safety and radiation protection area. First steps -some based on the Canadian experience - were already done in Romania, in developing AI techniques related to nuclear energy. Newcomers are recommended to start with modest and isolate problems in order to build up the necessary hand-on experience. The moment of the large scale AI implementation in the nuclear energy field will be decided by the balance between conventional computing and Ai computing and also between the advantages and disadvantages of AI. In this frame, the opportunity for research developing and using AI in the nuclear energy field is inherent and must be sustained by the research, design and plant operation authorities and also by the high education universities which are recommended to focus their interest towards the AI field for the next specialists in nuclear energy. (Author) 2 Figs., 2 Tabs., 7 Refs

  13. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  14. Techniques for incorporating operator expertise into intelligent decision aids and training

    International Nuclear Information System (INIS)

    Blackman, H.S.; Nelson, W.R.

    1988-01-01

    An experiment is presented that was designed to investigate the use of protocol analysis, during task performance, as a technique for knowledge engineering that provides a direct tie between knowledge and performance. The technique is described and problem solving strategies are presented that were found to correlate with optimal performance. The results indicate that protocol analysis adds a dimension to the more standard knowledge engineering approaches by providing a more complete picture of the expert's knowledge and a performance yardstick to determine the most optimal problem solving strategies. Implications for the developers of expert systems and training programs are discussed. (author)

  15. Developments in operator assistance techniques for nuclear power plant control and operation

    International Nuclear Information System (INIS)

    Poujol, A.; Papin, B.; Beltranda, G.; Soldermann, R.

    1989-01-01

    This paper describes an approach which has been developed in order to improve nuclear power plants control and monitoring in normal and abnormal situations. These developments take full advantage of the trend towards the computerization of control rooms in industrial continuous processes. This research program consists in a thorough exploration of different information processing techniques, ranking from the rather simple visual synthetization of informations on graphic displays to sophisticated Artificial Intelligence (AI) techniques. These techniques are put into application for the solving of man-machine interface problems in the different domains of plant operation

  16. Comparing the Effects of Two Facets of Multiple Intelligences Theory on Developing EFL Learners’ Listening

    Directory of Open Access Journals (Sweden)

    Ma’ssoumeh Bemani Naeini

    2015-08-01

    Full Text Available Gardner’s Multiple Intelligences Theory (MIT, however having been embraced in the field of language acquisition, has apparently failed to play a role in research on learning styles as an alternative construct.  This study aims at examining the potential effects of MI-based activities, as learning styls, on the listening proficiency of Iranian TEFL university students.  Based on two assumptions derived from MIT, one of the experimental groups (EG1; N=30 worked on activities across intelligences while the other experimental group (EG2; N=30 focused on the activities related to their most developed intelligence.  McKenzie’s (1999 MI Inventory was used to identify the subjects’ preferred intelligences. There was a significant difference between listening scores on TOEFL before and after the intervention of MI-based activities as well as between the two experimental groups, indicating EG1 outperforming EG2.  So, as the findings reveal, integration of MIT can significantly contribute to the enhancement of EFL learners’ listening comprehension and the effect is even more significant if teachers practice an integration of all intelligences rather than the most developed ones, only.    Keywords: Multiple Intelligences Theory, learning styles, listening proficiency, Iranian EFL context

  17. An Intelligent Consumables Management System Development Framework based on Artificial Intelligence Techniques, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation, called the Management of consumables Adaptive Execution, SynchronizaTion, Replanning/rescheduling, Optimization system (MAESTRO), would...

  18. Development of intelligent photomultipliers for the JUNO detector

    Energy Technology Data Exchange (ETDEWEB)

    Lenz, Florian; Meloni, Marta; Soiron, Michael; Stahl, Achim; Steinmann, Jochen; Wiebusch, Christopher [III. Physikalisches Institut B, RWTH Aachen University, 52056 Aachen (Germany)

    2016-07-01

    The JUNO experiment will be a 20kt liquid scintillator neutrino detector near Kaiping, China, 50km from two nuclear power plants. Its main goal is the determination of the neutrino mass hierarchy from a precise measurement of the energy spectrum of neutrinos. Due to the detector size it is not possible to digitize the signal outside the detector cavern. Therefore FPGAs with a low-level reconstruction combined with a fast ADC mounted on the base will convert the PMTs into intelligent sensors. Advantages and disadvantages of this design are be discussed,and first measurements are shown.

  19. Policing Toward a De-Clawed Jihad: Antiterrorism Intelligence Techniques for Law Enforcement

    Science.gov (United States)

    2006-12-01

    intelligence that has been analyzed and interpreted halal (Arabic) n., Islamic dietary strictures; adj., of or relating to halal HUMINT n., acronym...tax markets; production and distribution of counterfeit goods or bootlegged music and videos; resale of expired food products at small grocery or...to 113 Halal constitutes Islamic dietary strictures, similar to Kosher in Judaism. 44 an ethnic

  20. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    E.H. Gerding (Enrico); D.D.B. van Bragt; J.A. La Poutré (Han)

    2000-01-01

    textabstractDue to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI).

  1. Developing emotional intelligence ability in oncology nurses: a clinical rounds approach.

    Science.gov (United States)

    Codier, Estelle; Freitas, Beth; Muneno, Lynn

    2013-01-01

    To explore the feasibility and impact of an emotional intelligence ability development program on staff and patient care. A mixed method, pre/post-test design. A tertiary care hospital in urban Honolulu, HI. Rounds took place on a 24-bed inpatient oncology unit. 33 RNs in an oncology unit. After collection of baseline data, the emotional intelligence rounds were conducted in an inpatient oncology nursing unit on all shifts during a 10-month period. Demographic information, emotional intelligence scores, data from rounds, chart reviews of emotional care documentation, and unit-wide satisfaction and safety data. The ability to identify emotions in self and others was demonstrated less frequently than expected in this population. The low test response rate prevented comparison of scores pre- and postintervention. The staff's 94% participation in rounds, the positive (100%) evaluation of rounds, and poststudy improvements in emotional care documentation and emotional care planning suggest a positive effect from the intervention. Additional research is recommended over a longer period of time to evaluate the impact emotional intelligence specifically has on the staff's identification of emotions. Because the intervention involved minimal time and resources, feasibility for continuation of the intervention poststudy was rated "high" by the research team. Research in other disciplines suggests that improvement in emotional intelligence ability in clinical staff nurses may improve retention, performance, and teamwork in nursing, which would be of particular significance in high-risk clinical practice environments. Few research studies have explored development of emotional intelligence abilities in clinical staff nurses. Evidence from this study suggests that interventions in the clinical environment may be used to develop emotional intelligence ability. Impact from such development may be used in the future to not only improve the quality of nursing care, but also

  2. [Development and effects of emotional intelligence program for undergraduate nursing students: mixed methods research].

    Science.gov (United States)

    Lee, Oi Sun; Gu, Mee Ock

    2014-12-01

    This study was conducted to develop and test the effects of an emotional intelligence program for undergraduate nursing students. The study design was a mixed method research. Participants were 36 nursing students (intervention group: 17, control group: 19). The emotional intelligence program was provided for 4 weeks (8 sessions, 20 hours). Data were collected between August 6 and October 4, 2013. Quantitative data were analyzed using Chi-square, Fisher's exact test, t-test, repeated measure ANOVA, and paired t-test with SPSS/WIN 18.0. Qualitative data were analyzed using content analysis. Quantitative results showed that emotional intelligence, communication skills, resilience, stress coping strategy, and clinical competence were significantly better in the experimental group compared to the control group. According to the qualitative results, the nursing students experienced improvement in emotional intelligence, interpersonal relationships, and empowerment, as well as a reduction in clinical practice stress after participation in the emotional intelligence program. Study findings indicate that the emotional intelligence program for undergraduate nursing students is effective and can be recommended as an intervention for improving the clinical competence of undergraduate students in a nursing curriculum.

  3. Intelligence in childhood and chronic widespread pain in middle age: the National Child Development Survey.

    Science.gov (United States)

    Gale, Catharine R; Deary, Ian J; Cooper, Cyrus; Batty, G David

    2012-12-01

    Psychological factors are thought to play a part in the aetiology of chronic widespread pain. We investigated the relationship between intelligence in childhood and risk of chronic widespread pain in adulthood in 6902 men and women from the National Child Development Survey (1958 British Birth Cohort). Participants took a test of general cognitive ability at age 11 years; and chronic widespread pain, defined according to the American College of Rheumatology criteria, was assessed at age 45 years. Risk ratios (RRs) and 95% confidence intervals (CIs) were estimated using log-binomial regression, adjusting for sex and potential confounding or mediating factors. Risk of chronic widespread pain, defined according to the American College of Rheumatology criteria, rose in a stepwise fashion as intelligence fell (P for linear trend intelligence quotient, the RR of chronic widespread pain was 1.26 (95% CI 1.17-1.35). In multivariate backwards stepwise regression, lower childhood intelligence remained as an independent predictor of chronic widespread pain (RR 1.10; 95% CI 1.01-1.19), along with social class, educational attainment, body mass index, smoking status, and psychological distress. Part of the effect of lower childhood intelligence on risk of chronic widespread pain in midlife was significantly mediated through greater body mass index and more disadvantaged socioeconomic position. Men and women with higher intelligence in childhood are less likely as adults to report chronic widespread pain. Copyright © 2012 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

  4. Three-dimensional techniques and artificial intelligence in thallium-201 cardiac imaging

    International Nuclear Information System (INIS)

    DePuey, E.G.; Garcia, E.V.; Ezquerra, N.F.

    1989-01-01

    Three-dimensional reconstruction techniques including bull's-eye polar-coordinate maps, surface rendering, and surface modeling have been developed that help interpreting physicians assimilate complex 3-D tomographic data. Comparison of patient data with normal files highlights myocardial perfusion abnormalities, thus facilitating their recognition. In addition, AI systems that use heuristically defined rules derived from an expert knowledge base assist inexperienced observers in drawing conclusions regarding scan abnormalities.24 references

  5. The development of intelligent expert system with SAT for semiconductor

    International Nuclear Information System (INIS)

    Kim, Jae Yeol; Shim, Jae Gi; Jeong, Hyun Jo; Cho, Young Tae; Kim, Chang Hyun; Ko, Myung Soo

    2001-01-01

    In this study, the researches classifying the artificial flaws in semiconductor packages are performed using pattern recognition technology. For this purposes image pattern recognition package including the user made software was developed and total procedure including ultrasonic image acquisition, equalization filtering, binary processing, edge detection and classifier selection is treated by BP(backpropagation). Specially, it is compared IP(image processing) and SOM(self-organizing map) as preprocessing method for dimensionality reduction for entrance into multi-layer perceptron(backpropagation). Also, the pattern recognition techniques is applied to the classification problem of semiconductor flaws as crack, delamination. According to this results, it is possible to acquire the recognition rate of 83.4% about delamination, 75.7% about crack for SOM, and to acquire the recognition rate of 100% for BP.

  6. Developing energy forecasting model using hybrid artificial intelligence method

    Institute of Scientific and Technical Information of China (English)

    Shahram Mollaiy-Berneti

    2015-01-01

    An important problem in demand planning for energy consumption is developing an accurate energy forecasting model. In fact, it is not possible to allocate the energy resources in an optimal manner without having accurate demand value. A new energy forecasting model was proposed based on the back-propagation (BP) type neural network and imperialist competitive algorithm. The proposed method offers the advantage of local search ability of BP technique and global search ability of imperialist competitive algorithm. Two types of empirical data regarding the energy demand (gross domestic product (GDP), population, import, export and energy demand) in Turkey from 1979 to 2005 and electricity demand (population, GDP, total revenue from exporting industrial products and electricity consumption) in Thailand from 1986 to 2010 were investigated to demonstrate the applicability and merits of the present method. The performance of the proposed model is found to be better than that of conventional back-propagation neural network with low mean absolute error.

  7. Individual Differences in Moral Development: Does Intelligence Really Affect Children's Moral Reasoning and Moral Emotions?

    Science.gov (United States)

    Beißert, Hanna M; Hasselhorn, Marcus

    2016-01-01

    This study investigates the relationship between intelligence and individual differences in children's moral development across a range of different moral transgressions. Taking up prior research that showed morality and intelligence to be related in adolescents and adults, the current study wants to test if these findings can be extended to younger children. The study was designed to address some of the shortcomings in prior research by examining young children aged between 6 years; 4 months and 8 years; 10 months, using a broad concept of moral development including emotional aspects and applying an approach that is closely connected to children's daily lives. Participants ( N = 129) completed a standardized intelligence test and were presented four moral transgression stories to assess moral development. Results demonstrated that findings from prior research with adolescents or adults cannot simply be extended to younger participants. No significant correlations of moral development and intelligence were found for any of the presented stories. This provides first evidence that - at least in middle childhood - moral developmental status seems to be independent from children's general intelligence assessed by figural inductive reasoning tests.

  8. The development of digital monitoring technique

    International Nuclear Information System (INIS)

    Koo, In Soo; Kim, D. H.; Kim, J. S.; Kim, C. H.; Kim, G. O.; Park, H. Y.; Suh, S. Y.; Sung, S. H.; Song, S. J.; Lee, C. K.; Jang, G. S.; Hur, S.

    1997-08-01

    A study has been performed for advanced DSP technology for the digital nuclear I and C systems for the monitoring and diagnosis techniques for high-pressurized structures integrity in NSSS. In the development of advanced DSP technology, real time process, communication network and signal validation were selected as the essential technologies of the digital signal process, and the requirements and methodology for the application of these technologies in NPP were established through technical analysis. Based on its results, the DPIS and the signal validation algorithm were developed. For the real-time process, the necessary requirements were define and the methodology of real-time software modeling was developed. For the communication network, the methodology of selection of the communication technique and developing procedure were established with an extraction of requirements. Functions, requirements, structure and technical specification were developed for the DPIS, and a real-time signal validation algorithm was developed and implemented for the signal validation. In a study on monitoring techniques for abnormal conditions, test and experimental facilities have been set up in order to carry out the required tests during research activities. Studies concentrated on how to acquire proper vibration or emission signals from mechanical structures and equipments, and to diagnose effectively the abnormal conditions of high pressure structure integrity. The algorithms of automatic signal analysis and diagnosis for abnormal conditions have been developed in this study to assist the operator's monitoring and diagnosis activities on structure integrity using new technologies. (author). 23 refs., 68 tabs., 196 figs

  9. The development of digital monitoring technique

    Energy Technology Data Exchange (ETDEWEB)

    Koo, In Soo; Kim, D. H.; Kim, J. S.; Kim, C. H.; Kim, G. O.; Park, H. Y.; Suh, S. Y.; Sung, S. H.; Song, S. J.; Lee, C. K.; Jang, G. S.; Hur, S.

    1997-08-01

    A study has been performed for advanced DSP technology for the digital nuclear I and C systems for the monitoring and diagnosis techniques for high-pressurized structures integrity in NSSS. In the development of advanced DSP technology, real time process, communication network and signal validation were selected as the essential technologies of the digital signal process, and the requirements and methodology for the application of these technologies in NPP were established through technical analysis. Based on its results, the DPIS and the signal validation algorithm were developed. For the real-time process, the necessary requirements were define and the methodology of real-time software modeling was developed. For the communication network, the methodology of selection of the communication technique and developing procedure were established with an extraction of requirements. Functions, requirements, structure and technical specification were developed for the DPIS, and a real-time signal validation algorithm was developed and implemented for the signal validation. In a study on monitoring techniques for abnormal conditions, test and experimental facilities have been set up in order to carry out the required tests during research activities. Studies concentrated on how to acquire proper vibration or emission signals from mechanical structures and equipments, and to diagnose effectively the abnormal conditions of high pressure structure integrity. The algorithms of automatic signal analysis and diagnosis for abnormal conditions have been developed in this study to assist the operator`s monitoring and diagnosis activities on structure integrity using new technologies. (author). 23 refs., 68 tabs., 196 figs.

  10. Design and Development of Intelligent Electrodes for Future Digital Health Monitoring: A Review

    Science.gov (United States)

    Khairuddin, A. M.; Azir, K. N. F. Ku; Kan, P. Eh

    2018-03-01

    Electrodes are sensors used in electrocardiography (ECG) monitoring system to diagnose heart diseases. Over the years, diverse types of electrodes have been designed and developed to improve ECG monitoring system. However, more recently, with the technological advances and capabilities from the Internet of Things (IoT), cloud computing and data analytics in personalized healthcare, researchers are attempting to design and develop more effective as well as flexible ECG devices by using intelligent electrodes. This paper reviews previous works on electrodes used in electrocardiography (ECG) monitoring devices to identify the key ftures for designing and developing intelligent electrodes in digital health monitoring devices.

  11. The developing technique for automated UT system

    International Nuclear Information System (INIS)

    Kim, Y. S.; Baek, C. H.

    1994-01-01

    This paper presents an experiential summary of the developing technique for automated ultrasonic testing system that consists of an ultrasonic tester, mechanical moving and fixing parts, controller and testing software. The application knowledges and limitations on these items are helpful to prevent the misoperation, the unadequate test result analysis and to build up the own test system.

  12. New Developments and special NDT techniques

    International Nuclear Information System (INIS)

    Mundry, E.

    1978-01-01

    New developments in measuring methods using non-destructive testing are reported. The following are discussed in various chapters: a) Mechanical and acoustic methods, b) thermal and optical methods, c) electric and magnetic methods, d) X-ray and gamma radiation methods, e) particle methods or particle radiation. Finally, method techniques are explained. An extensive bibliography (210 quotations) supplement the work. (RW) [de

  13. Techniques for incorporating operator expertise into intelligent decision aids and training

    International Nuclear Information System (INIS)

    Blackman, H.S.; Nelson, W.R.

    1987-01-01

    The objective of this work is to evaluate the potential for developing a complete model for training novices based upon a combination of rules for operation, and heuristics for application of the rules. The method used to investigate this potential is based upon the experimental evaluation of the response tree expert system. The present study used the low pressure injection system (LPIS) simulation developed for the response tree expert system evaluation, so that the rules of operation were already developed, and only the expert heuristics needed to be identified. The heuristics were abstracted from concurrent and recall protocols, taken from expert operators while attempting to solve transients on the LPIS, using protocol analysis techniques previously developed. This paper describes the experiment, and identifies the mental processes used by expert operators

  14. A framework for development of an intelligent system for design and manufacturing of stamping dies

    Science.gov (United States)

    Hussein, H. M. A.; Kumar, S.

    2014-07-01

    An integration of computer aided design (CAD), computer aided process planning (CAPP) and computer aided manufacturing (CAM) is required for development of an intelligent system to design and manufacture stamping dies in sheet metal industries. In this paper, a framework for development of an intelligent system for design and manufacturing of stamping dies is proposed. In the proposed framework, the intelligent system is structured in form of various expert system modules for different activities of design and manufacturing of dies. All system modules are integrated with each other. The proposed system takes its input in form of a CAD file of sheet metal part, and then system modules automate all tasks related to design and manufacturing of stamping dies. Modules are coded using Visual Basic (VB) and developed on the platform of AutoCAD software.

  15. A framework for development of an intelligent system for design and manufacturing of stamping dies

    International Nuclear Information System (INIS)

    Hussein, H M A; Kumar, S

    2014-01-01

    An integration of computer aided design (CAD), computer aided process planning (CAPP) and computer aided manufacturing (CAM) is required for development of an intelligent system to design and manufacture stamping dies in sheet metal industries. In this paper, a framework for development of an intelligent system for design and manufacturing of stamping dies is proposed. In the proposed framework, the intelligent system is structured in form of various expert system modules for different activities of design and manufacturing of dies. All system modules are integrated with each other. The proposed system takes its input in form of a CAD file of sheet metal part, and then system modules automate all tasks related to design and manufacturing of stamping dies. Modules are coded using Visual Basic (VB) and developed on the platform of AutoCAD software

  16. Educational Programs for Intelligence Professionals.

    Science.gov (United States)

    Miller, Jerry P.

    1994-01-01

    Discusses the need for education programs for competitive intelligence professionals. Highlights include definitions of intelligence functions, focusing on business intelligence; information utilization by decision makers; information sources; competencies for intelligence professionals; and the development of formal education programs. (38…

  17. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    OpenAIRE

    Daniel-Petru GHENCEA; Miron ZAPCIU; Claudiu-Florinel BISU; Elena-Iuliana BOTEANU; Elena-Luminiţa OLTEANU

    2017-01-01

    The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic). The paper presents a prediction mode obtaining valid range of values f...

  18. A Smart Sensor Data Transmission Technique for Logistics and Intelligent Transportation Systems

    OpenAIRE

    Kyunghee Sun; Intae Ryoo

    2018-01-01

    When it comes to Internet of Things systems that include both a logistics system and an intelligent transportation system, a smart sensor is one of the key elements to collect useful information whenever and wherever necessary. This study proposes the Smart Sensor Node Group Management Medium Access Control Scheme designed to group smart sensor devices and collect data from them efficiently. The proposed scheme performs grouping of portable sensor devices connected to a system depending on th...

  19. Event classification and optimization methods using artificial intelligence and other relevant techniques: Sharing the experiences

    Science.gov (United States)

    Mohamed, Abdul Aziz; Hasan, Abu Bakar; Ghazali, Abu Bakar Mhd.

    2017-01-01

    Classification of large data into respected classes or groups could be carried out with the help of artificial intelligence (AI) tools readily available in the market. To get the optimum or best results, optimization tool could be applied on those data. Classification and optimization have been used by researchers throughout their works, and the outcomes were very encouraging indeed. Here, the authors are trying to share what they have experienced in three different areas of applied research.

  20. PRINTING TECHNIQUES: RECENT DEVELOPMENTS IN PHARMACEUTICAL TECHNOLOGY.

    Science.gov (United States)

    Jamroz, Witold; Kurek, Mateusz; Lyszczarz, Ewelina; Brniak, Witold; Jachowicz, Renata

    2017-05-01

    In the last few years there has been a huge progress in a development of printing techniques and their application in pharmaceutical sciences and particularly in the pharmaceutical technology. The variety of printing methods makes it necessary to systemize them, explain the principles of operation, and specify the possibilities of their use in pharmaceutical technology. This paper aims to review the printing techniques used in a drug development process. The growing interest in 2D and 3D printing methods results in continuously increasing number of scientific papers. Introduction of the first printed drug Spritam@ to the market seems to be a milestone of the 3D printing development. Thus, a particular aim of this review is to show the latest achievements of the researchers in the field of the printing medicines.

  1. Developing cultural intelligence: assessing the effect of the Ecotonos cultural simulation game for international business students

    NARCIS (Netherlands)

    Bücker, J.J.L.E.; Korzilius, H.P.L.M.

    2015-01-01

    In this study, we test the strength of a cross-cultural simulation game, Ecotonos, in the development of cultural intelligence (CQ) and self-efficacy amongst business students. Cross-cultural training is perceived as an important tool to help develop cross-cultural competence in international

  2. Development of mechanoluminescence technique for impact studies

    International Nuclear Information System (INIS)

    Chandra, B.P.

    2011-01-01

    A new technique called, mechanoluminescence technique, is developed for measuring the parameters of impact. This technique is based on the phenomenon of mechanoluminescence (ML), in which light emission takes place during any mechanical action on solids. When a small solid ball makes an impact on the mechanoluminescent thin film coated on a solid, then initially the elastico ML (EML) intensity increases with time, attains a maximum value I m at a particular time t m , and later on it decreases with time. The contact time T c of ball, can be determined from the relation T c =2t c , where t c is the time at which the EML emission due to compression of the sample becomes negligible. The area from where the EML emission occurs can be taken as the contact area A c . The maximum compression h is given by h=A c /(πr), where r is the radius of the impacting ball, and thus, h can be determined from the known values of A c and r. The maximum force at contact is given by F m =(2mU 0 )/T c , where m is the mass of the impacting ball and U 0 is the velocity of the ball at impact. The maximum impact stress σ m can be obtained from the relation, σ m =F m /A c =(2mU 0 )/(T c A c ). Thus, ML provides a real-time technique for determining the impact parameters such as T c , A c , h, F m and σ m . Using the ML technique, the impact parameters of the SrAl 2 O 4 :Eu film and ZnS:Mn coating are determined. The ML technique can be used to determine the impact parameters in the elastic region and plastic region as well as fracture. ML can also be used to determine the impact parameters for the collision between solid and liquid, if the mechanoluminescent material is coated on the surface of the solid. The measurement of fracto ML in microsecond and nanosecond range may provide a tool for studying the fragmentations in solids by the impact. Using the fast camera the contact area and the depth of compression can be determined for different intervals of time. - Research highlights: → A

  3. Development of charged particle nuclear reaction data retrieval system on IntelligentPad

    International Nuclear Information System (INIS)

    Ohbayashi, Yosihide; Masui, Hiroshi; Aoyama, Shigeyoshi; Kato, Kiyoshi; Chiba, Masaki

    1999-01-01

    An newly designed database retrieval system of charged particle nuclear reaction database system is developed with IntelligentPad architecture. We designed the network-based (server-client) data retrieval system, and a client system constructs on Windows95, 98/NT with IntelligentPad. We set the future aim of our database system toward the 'effective' use of nuclear reaction data: I. 'Re-produce, Re-edit, Re-use', II. 'Circulation, Evolution', III. 'Knowledge discovery'. Thus, further developments are under way. (author)

  4. Advanced Techniques in Web Intelligence-2 Web User Browsing Behaviour and Preference Analysis

    CERN Document Server

    Palade, Vasile; Jain, Lakhmi

    2013-01-01

    This research volume focuses on analyzing the web user browsing behaviour and preferences in traditional web-based environments, social  networks and web 2.0 applications,  by using advanced  techniques in data acquisition, data processing, pattern extraction and  cognitive science for modeling the human actions.  The book is directed to  graduate students, researchers/scientists and engineers  interested in updating their knowledge with the recent trends in web user analysis, for developing the next generation of web-based systems and applications.

  5. Body satisfaction, emotional intelligence, and the development of disturbed eating: a survey of Taiwanese students.

    Science.gov (United States)

    Wong, Yueching; Lin, Jing-Shan; Chang, Yu-Jhen

    2014-01-01

    This study explored the relationship between adolescents' emotional intelligence and the tendency to develop an eating disorder. Senior high school students in Taiwan were recruited for the study. A 3- part anonymous questionnaire measured demographic information, body weight satisfaction, and expectation of body weight. Students also completed the Adolescent Emotional Intelligence Scale and the Eating Disorders Attitude- 26 Test (EAT-26). Height and weight were also measured. The mean of EAT-26 score was 8.66 ± 7.36, and 8.6% students were at high risk to develop eating disorders. Gender, body weight, body dissatisfaction and the expected body shape were significantly related to disturbed eating attitudes and behaviours. Scores of EAT-26 were positively correlated with emotional perception, emotional expression, and emotional application. Disturbed eating behaviours exist among adolescents in Taiwan, and these behaviours may be related to emotional intelligence. However further studies with larger samples are needed.

  6. Development of Radiotracer Techniques in Industry

    International Nuclear Information System (INIS)

    Wardono

    2000-01-01

    Contribution of radiotracer techniques to solve problems in industrial process plants have been recognized since a long time. Radiotracer application was governed by three main components, namely radioisotopes, radiation detection and data interpretation of an experiment. The three main components mentioned above have been continually developed to overcome problems relating to the operation of industrial process plants. The availability of isotope generator is one of the development aspect in radiotracer technique. Radiation hazard in radiotracer experiment may be reduced by applying isotope generator and on the other hand the delivery of radiotracer to the plant site from the radioisotopes producer was made easier. The development of microprocessor in computer system has facilitated data recording, storing and retrieving. Development in mathematical model supported by radiotracer experiment enhance data interpretation and shed light on various phenomena of flow process. Generally a flow dynamic in a process plant in all kind of industries can be studied using radiotracer technique. However the main challenge coming from petroleum, petrochemical and mineral processing industries

  7. Artificial-intelligence-based optimization of the management of snow removal assets and resources.

    Science.gov (United States)

    2002-10-01

    Geographic information systems (GIS) and artificial intelligence (AI) techniques were used to develop an intelligent : snow removal asset management system (SRAMS). The system has been evaluated through a case study examining : snow removal from the ...

  8. Recent developments in monoclonal antibody radiolabeling techniques

    Energy Technology Data Exchange (ETDEWEB)

    Srivastava, S.C.; Mease, R.C.

    1989-01-01

    Monoclonal antibodies (MAbs) have shown the potential to serve as selective carriers of radionuclides to specific in vivo antigens. Accordingly, there has been an intense surge of research activity in an effort to develop and evaluate MAb-based radiopharmaceuticals for tumor imaging (radioimmunoscintigraphy) and therapy (radioimmunotherapy), as well as for diagnosing nonmalignant diseases. A number of problems have recently been identified, related to the MAbs themselves and to radiolabeling techniques, that comprise both the selectivity and the specificity of the in vivo distribution of radiolabeled MAbs. This paper will address some of these issues and primarily discuss recent developments in the techniques for radiolabeling monoclonal antibodies that may help resolve problems related to the poor in vivo stability of the radiolabel and may thus produce improved biodistribution. Even though many issues are identical with therapeutic radionuclides, the discussion will focus mainly on radioimmunoscintigraphic labels. 78 refs., 6 tabs.

  9. Development of tritium-handling technique

    International Nuclear Information System (INIS)

    Ohmura, Hiroshi; Hosaka, Akio; Okamoto, Takahumi

    1988-01-01

    The overview of developing activities for tritium-handling techniques in IHI are presented. To establish a fusion power plant, tritium handling is one of the key technologies. Recently in JAERI, conceptual design of FER (Fusion Experimental Reactor) has been carried out, and the FER system requires a processing system for a large amount of tritium. IHI concentrate on investigation of fuel gas purification, isotope separation and storage systems under contract with Toshiba Corporation. Design results of the systems and each components are reviewed. IHI has been developing fundamental handling techniques which are the ZrNi bed for hydrogen isotope storage and isotope separation by laser. The ZrNi bed with a tritium storage capacity of 1000 Ci has been constructed and recovery capability of the hydrogen isotope until 10 -4 Torr {0.013 Pa} was confirmed. In laser isotope separation, the optimum laser wave length has been determined. (author)

  10. Recent developments in monoclonal antibody radiolabeling techniques

    International Nuclear Information System (INIS)

    Srivastava, S.C.; Mease, R.C.

    1989-01-01

    Monoclonal antibodies (MAbs) have shown the potential to serve as selective carriers of radionuclides to specific in vivo antigens. Accordingly, there has been an intense surge of research activity in an effort to develop and evaluate MAb-based radiopharmaceuticals for tumor imaging (radioimmunoscintigraphy) and therapy (radioimmunotherapy), as well as for diagnosing nonmalignant diseases. A number of problems have recently been identified, related to the MAbs themselves and to radiolabeling techniques, that comprise both the selectivity and the specificity of the in vivo distribution of radiolabeled MAbs. This paper will address some of these issues and primarily discuss recent developments in the techniques for radiolabeling monoclonal antibodies that may help resolve problems related to the poor in vivo stability of the radiolabel and may thus produce improved biodistribution. Even though many issues are identical with therapeutic radionuclides, the discussion will focus mainly on radioimmunoscintigraphic labels. 78 refs., 6 tabs

  11. Towards the Development of Web-based Business intelligence Tools

    DEFF Research Database (Denmark)

    Georgiev, Lachezar; Tanev, Stoyan

    2011-01-01

    This paper focuses on using web search techniques in examining the co-creation strategies of technology driven firms. It does not focus on the co-creation results but describes the implementation of a software tool using data mining techniques to analyze the content on firms’ websites. The tool...

  12. The development of human behavior analysis techniques

    International Nuclear Information System (INIS)

    Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang.

    1997-07-01

    In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator's physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs

  13. The development of human behavior analysis techniques

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jung Woon; Lee, Yong Hee; Park, Geun Ok; Cheon, Se Woo; Suh, Sang Moon; Oh, In Suk; Lee, Hyun Chul; Park, Jae Chang

    1997-07-01

    In this project, which is to study on man-machine interaction in Korean nuclear power plants, we developed SACOM (Simulation Analyzer with a Cognitive Operator Model), a tool for the assessment of task performance in the control rooms using software simulation, and also develop human error analysis and application techniques. SACOM was developed to assess operator`s physical workload, workload in information navigation at VDU workstations, and cognitive workload in procedural tasks. We developed trip analysis system including a procedure based on man-machine interaction analysis system including a procedure based on man-machine interaction analysis and a classification system. We analyzed a total of 277 trips occurred from 1978 to 1994 to produce trip summary information, and for 79 cases induced by human errors time-lined man-machine interactions. The INSTEC, a database system of our analysis results, was developed. The MARSTEC, a multimedia authoring and representation system for trip information, was also developed, and techniques for human error detection in human factors experiments were established. (author). 121 refs., 38 tabs., 52 figs.

  14. Computational Intelligence for Engineering Systems

    CERN Document Server

    Madureira, A; Vale, Zita

    2011-01-01

    "Computational Intelligence for Engineering Systems" provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences. The contributions are written by international experts, who provide up-to-date aspects of the topics discussed and present recent, original insights into their own experien

  15. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

    1994-01-01

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. To investigate the capabilities of this two-level hierarchical knowledge structure, Commonwealth Research Corporation (CRC) and Argonne National Laboratory (ANL)are collaborating on a DOE-sponsored Cooperative Research and Development Agreement (CRADA) project to perform feasibility studies on the proposed diagnostic system. Investigations are being performed in the construction of a physics-based plant level process diagnostic ES and the characterization of component-level fault project is to develop a computer-based system using this Al approach to assist process plant operators during off-normal plant conditions. The proposed computer-based system will use T-H signals complemented by other non-T-H signals available in the data stream to provide the process operator with the component which most likely caused the observed process disturbance. To demonstrate the scale-up feasibility of the proposed diagnostic system it is being developed for use with the Chemical Volume Control System (CVCS) of a nuclear power plant. This is an ongoing multi-year project and the remainder of this paper presents a mid-term status report

  16. Development of an advanced intelligent robot navigation system

    International Nuclear Information System (INIS)

    Hai Quan Dai; Dalton, G.R.; Tulenko, J.; Crane, C.C. III

    1992-01-01

    As part of the US Department of Energy's Robotics for Advanced Reactors Project, the authors are in the process of assembling an advanced intelligent robotic navigation and control system based on previous work performed on this project in the areas of computer control, database access, graphical interfaces, shared data and computations, computer vision for positions determination, and sonar-based computer navigation systems. The system will feature three levels of goals: (1) high-level system for management of lower level functions to achieve specific functional goals; (2) intermediate level of goals such as position determination, obstacle avoidance, and discovering unexpected objects; and (3) other supplementary low-level functions such as reading and recording sonar or video camera data. In its current phase, the Cybermotion K2A mobile robot is not equipped with an onboard computer system, which will be included in the final phase. By that time, the onboard system will play important roles in vision processing and in robotic control communication

  17. Application of artificial intelligence (AI) concepts to the development of space flight parts approval model

    Science.gov (United States)

    Krishnan, G. S.

    1997-01-01

    A cost effective model which uses the artificial intelligence techniques in the selection and approval of parts is presented. The knowledge which is acquired from the specialists for different part types are represented in a knowledge base in the form of rules and objects. The parts information is stored separately in a data base and is isolated from the knowledge base. Validation, verification and performance issues are highlighted.

  18. An intelligent approach for cooling radiator fault diagnosis based on infrared thermal image processing technique

    International Nuclear Information System (INIS)

    Taheri-Garavand, Amin; Ahmadi, Hojjat; Omid, Mahmoud; Mohtasebi, Seyed Saeid; Mollazade, Kaveh; Russell Smith, Alan John; Carlomagno, Giovanni Maria

    2015-01-01

    This research presents a new intelligent fault diagnosis and condition monitoring system for classification of different conditions of cooling radiator using infrared thermal images. The system was adopted to classify six types of cooling radiator faults; radiator tubes blockage, radiator fins blockage, loose connection between fins and tubes, radiator door failure, coolant leakage, and normal conditions. The proposed system consists of several distinct procedures including thermal image acquisition, image pre-processing, image processing, two-dimensional discrete wavelet transform (2D-DWT), feature extraction, feature selection using a genetic algorithm (GA), and finally classification by artificial neural networks (ANNs). The 2D-DWT is implemented to decompose the thermal images. Subsequently, statistical texture features are extracted from the original images and are decomposed into thermal images. The significant selected features are used to enhance the performance of the designed ANN classifier for the 6 types of cooling radiator conditions (output layer) in the next stage. For the tested system, the input layer consisted of 16 neurons based on the feature selection operation. The best performance of ANN was obtained with a 16-6-6 topology. The classification results demonstrated that this system can be employed satisfactorily as an intelligent condition monitoring and fault diagnosis for a class of cooling radiator. - Highlights: • Intelligent fault diagnosis of cooling radiator using thermal image processing. • Thermal image processing in a multiscale representation structure by 2D-DWT. • Selection features based on a hybrid system that uses both GA and ANN. • Application of ANN as classifier. • Classification accuracy of fault detection up to 93.83%

  19. THE DEVELOPMENT OF TELEPON KALENG GAME AS A MEDIA TO STIMULATE LINGUISTIC INTELLIGENCE OF EARLY CHILDHOOD

    Directory of Open Access Journals (Sweden)

    Betty Yulia Wulansari

    2018-03-01

    Full Text Available The aim of this research is to determine the validity of telepon kaleng game as a medium to stimulate the linguistic intelligence of early childhood, as well as to know the merits and drawbacks of telepon kaleng game as learning media. The research method used is research and development (R & D. Development procedures include planning, design, and development. Product validation is done by alpha test, beta test, and final evaluation. Apha test is validated by an expert in material development and an expert in teaching-media development. Meanwhile, the subjects in beta test are students BA Aisyiah Yanggong and BA Aisyiah Wonoasri Jenangan District, Ponorogo Regency. The result of this research is the development of telepon kaleng game as a media to stimulate linguistic intelligence of early child. The tools and materials used in this development are used-can, thread / rope, flannel, scissors, and double tape. Material experts and media experts have validated telepon kaleng products developed. From validation, the results need to improve the use of tin cans and the improvement of learning materials. In the next stage, feasibility testing for users in BA 'Aisyiah Yanggong and BA' Aisyiah Wonoasri Jenang Subdistrict of Ponorogo Regency, from the result of the experiment showed that telepon kaleng could be used to stimulate the linguistic intelligence of early child. These telepon kalengs, when used in unlimited form by children, stimulate linguistic intelligence more than IN structured-form. The merit of telepon kaleng as a linguistic intelligence stimulus medium is an attractive form of the child compared totelepon kaleng without any accessories. Children tend to prefer things that are bright and engaging. The drawback of this telepon kaleng, if it is used continuously, is that it will lead to monotonous learning process so it needs to alternate with other game equipment.

  20. 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

    Science.gov (United States)

    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…

  1. Research and development of intelligent controller for high-grade sanitary ware

    Science.gov (United States)

    Bao, Kongjun; Shen, Qingping

    2013-03-01

    With the social and economic development and people's living standards improve, more and more emphasis on modern society, people improve the quality of family life, the use of intelligent controller applications in high-grade sanitary ware physiotherapy students. Analysis of high-grade sanitary ware physiotherapy common functions pointed out in the production and use of the possible risks, proposed implementation of the system hardware and matching, given the system software implementation process. High-grade sanitary ware physiotherapy intelligent controller not only to achieve elegant and beautiful, simple, physical therapy, water power, deodorant, multi-function, intelligent control, to meet the consumers, the high-end sanitary ware market, strong demand, Accelerate the enterprise product Upgrade and improve the competitiveness of enterprises.

  2. The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

    OpenAIRE

    Wolff, J Gerard

    2016-01-01

    This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

  3. Development of radioactive waste treatment technique

    International Nuclear Information System (INIS)

    Kikuchi, Makoto; Amamiya, Shigeru; Yusa, Hideo.

    1984-01-01

    The techniques of radioactive waste treatment are generally reviewed, placing emphasis on volume reduction and solidification techniques. After a brief description on the general process of radioactive waste treatment, some special technologies being developed by Hitachi Ltd. are explained. From the viewpoints of the volume reduction, long term management and final disposal of wastes, the pelletization of dried waste and the solidification with inorganic substances are considered. One of the features of the pelletization system is to treat various kinds of wastes such as concentrated liquid wastes and used resins by the same system. The flow diagram of the system and its special features are shown. The volume reduction achieved by this system as compared to the conventional method is about 1/7. The first commercial plant for the treatment of concentrated liquid waste is scheduled to begin operation in June, 1984. As for the solidification technique for waste disposal, the use of cement glass is considered. The solidification system being developed is shortly described. (Aoki, K.)

  4. Space Flight Software Development Software for Intelligent System Health Management

    Science.gov (United States)

    Trevino, Luis C.; Crumbley, Tim

    2004-01-01

    The slide presentation examines the Marshall Space Flight Center Flight Software Branch, including software development projects, mission critical space flight software development, software technical insight, advanced software development technologies, and continuous improvement in the software development processes and methods.

  5. The Relationship between a Business Simulator, Constructivist Practices, and Motivation toward Developing Business Intelligence Skills

    Science.gov (United States)

    Lee, Hsun-Ming; Long, Ju; Visinescu, Lucian L.

    2016-01-01

    Developing Business Intelligence (BI) has been a top priority for enterprise executives in recent years. To meet these demands, universities need to prepare students to work with BI in enterprise settings. In this study, we considered a business simulator that offers students opportunities to apply BI and make top-management decisions in a system…

  6. Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

    Science.gov (United States)

    Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

    2008-01-01

    Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

  7. Effects of Multiple Intelligences Activities on Writing Skill Development in an EFL Context

    Science.gov (United States)

    Gündüz, Zennure Elgün; Ünal, Ismail Dogan

    2016-01-01

    This study aims at exploring the effects of multiple intelligences activities versus traditional method on English writing development of the sixth grade students in Turkey. A quasi-experimental research method with a pre-test post-test design was applied. The participants were 50 sixth grade students at a state school in Ardahan in Turkey. The…

  8. A Multidisciplinary Model for Development of Intelligent Computer-Assisted Instruction.

    Science.gov (United States)

    Park, Ok-choon; Seidel, Robert J.

    1989-01-01

    Proposes a schematic multidisciplinary model to help developers of intelligent computer-assisted instruction (ICAI) identify the types of required expertise and integrate them into a system. Highlights include domain types and expertise; knowledge acquisition; task analysis; knowledge representation; student modeling; diagnosis of learning needs;…

  9. Education-Related Factors in Cultural Intelligence Development: A Colombian Study

    Science.gov (United States)

    Robledo-Ardila, Cristina; Aguilar-Barrientos, Sara; Román-Calderón, Juan Pablo

    2016-01-01

    This article reports the results of a study inquiring about the role of education-related factors in the development of cultural intelligence. Five hundred fifty-seven students of a Colombian international business (IB) undergraduate program participated in the study. The psychometric properties of the measures were assessed by conducting…

  10. The Individual Regulation Component of Group Emotional Intelligence: Measure Development and Validation

    Science.gov (United States)

    Peterson, Christina Hamme

    2012-01-01

    Counseling work is increasingly conducted in team format. The methods counseling teams use to manage the emotional component of their group life, or their group emotional intelligence, have been proposed as significantly contributing to group member trust, cooperation, and ultimate performance. Item development, exploratory factor analysis, and…

  11. Example-Tracing Tutors: Intelligent Tutor Development for Non-Programmers

    Science.gov (United States)

    Aleven, Vincent; McLaren, Bruce M.; Sewall, Jonathan; van Velsen, Martin; Popescu, Octav; Demi, Sandra; Ringenberg, Michael; Koedinger, Kenneth R.

    2016-01-01

    In 2009, we reported on a new Intelligent Tutoring Systems (ITS) technology, example-tracing tutors, that can be built without programming using the Cognitive Tutor Authoring Tools (CTAT). Creating example-tracing tutors was shown to be 4-8 times as cost-effective as estimates for ITS development from the literature. Since 2009, CTAT and its…

  12. Integrating human factors and artificial intelligence in the development of human-machine cooperation

    NARCIS (Netherlands)

    Maanen, P.P. van; Lindenberg, J.; Neericx, M.A.

    2005-01-01

    Increasing machine intelligence leads to a shift from a mere interactive to a much more complex cooperative human-machine relation requiring a multidisciplinary development approach. This paper presents a generic multidisciplinary cognitive engineering method CE+ for the integration of human factors

  13. An Artificially Intelligent Technique to Generate Synthetic Geomechanical Well Logs for the Bakken Formation

    Directory of Open Access Journals (Sweden)

    George Parapuram

    2018-03-01

    Full Text Available Artificially intelligent and predictive modelling of geomechanical properties is performed by creating supervised machine learning data models utilizing artificial neural networks (ANN and will predict geomechanical properties from basic and commonly used conventional well logs such as gamma ray, and bulk density. The predictive models were created by following the approach on a large volume of data acquired from 112 wells containing the Bakken Formation in North Dakota. The studied wells cover a large surface area of the formation containing the five main producing counties in North Dakota: Burke, Mountrail, McKenzie, Dunn, and Williams. Thus, with a large surface area being analyzed in this research, there is confidence with a high degree of certainty that an extensive representation of the Bakken Formation is modelled, by training neural networks to work on varying properties from the different counties containing the Bakken Formation in North Dakota. Shear wave velocity of 112 wells is also analyzed by regression methods and neural networks, and a new correlation is proposed for the Bakken Formation. The final goal of the research is to achieve supervised artificial neural network models that predict geomechanical properties of future wells with an accuracy of at least 90% for the Upper and Middle Bakken Formation. Thus, obtaining these logs by generating it from statistical and artificially intelligent methods shows a potential for significant improvements in performance, efficiency, and profitability for oil and gas operators.

  14. Cooperative research and development for artificial intelligence based reactor diagnostic system

    International Nuclear Information System (INIS)

    Reifman, J.; Wei, T.Y.C.; Abboud, R.G.; Chasensky, T.M.

    1994-01-01

    Artificial Intelligence (AI) techniques in the form of knowledge-based Expert Systems (ESs) have been proposed to provide on-line decision-making support for plant operators during both normal and emergency conditions. However, in spite of the great interest in these advanced techniques, their application in the diagnosis of large-scale processes has not yet reached its full potential because of limitations of the knowledge base. These limitations include problems with knowledge acquisition and the use of an event-oriented approach for process diagnosis. The knowledge base of process diagnosis ESs is generally acquired in a heuristic fashion through empirical associations between plant symptoms and component malfunctions with no reliance on fundamental physical principles. This nonsystematic construction of the knowledge base causes, among other problems, the encoded information to be biased and limited towards the developer's own experience and judgmental knowledge. The use of an event-oriented approach for process diagnosis requires the developer of the knowledge base to anticipate and formulate rules to cover every conceivable plant situation. In addition to yielding a large knowledge base, an undesirable characteristic for an on-line real-time advisory system, an event-oriented approach for diagnosis of large and complex thermal-hydraulic (T-H) based processes cannot guarantee functional completeness and is likely to fail under unanticipated circumstances. Hence, these limitations preclude an effective verification and validation of the knowledge base which is required in industrial applications. In contrast to the heuristic construction of a rigid knowledge base that uses an event-oriented approach for process diagnosis, the authors propose a different approach that involves the systematic construction of a hierarchical knowledge base with two levels

  15. Isotope techniques in water resources development 1991

    International Nuclear Information System (INIS)

    1992-01-01

    Water resources are scarce in many parts of the world. Often, the only water resource is groundwater. Overuse usually invites a rapid decline in groundwater resources which are recharged insufficiently, or not at all, by prevailing climatic conditions. These and other problems currently encountered in hydrology and associated environmental fields have prompted an increasing demand for the utilization of isotope methods. Such methods have been recognized as being indispensable for solving problems such as the identification of pollution sources, characterization of palaeowater resources, evaluation of recharge and evaporative discharge under arid and semi-arid conditions, reconstruction of past climates, study of the interrelationships between surface and groundwater, dating of groundwater and validation of contaminant transport models. Moreover, in combination with other hydrogeological and geochemical methods, isotope techniques can provide useful hydrological information, such as data on the origin, replenishment and dynamics of groundwater. It was against this background that the International Atomic Energy Agency, in co-operation with the United Nations Educational, Scientific and Cultural Organization and the International Association of Hydrological Sciences, organized this symposium on the Use of Isotope Techniques in Water Resources Development, which took place in Vienna from 11 to 15 March 1991. The main themes of the symposium were the use of isotope techniques in solving practical problems of water resources assessment and development, particularly with respect to groundwater protection, and in studying environmental problems related to water, including palaeohydrological and palaeoclimatological problems. A substantial part of the oral presentations was concerned with the present state and trends in groundwater dating, and with some methodological aspects. These proceedings contain the papers of 37 oral and the extended synopses of 47 poster

  16. Accuracy and Uncertainty Analysis of Intelligent Techniques for Predicting the Longitudinal Dispersion Coefficient in Rivers

    Directory of Open Access Journals (Sweden)

    Abbas Akbarzadeh

    2010-09-01

    Full Text Available Accurate prediction of longitudinal dispersion coefficient (LDC can be useful for the determination of pollutants concentration distribution in natural rivers. However, the uncertainty associated with the results obtained from forecasting models has a negative effect on pollutant management in water resources. In this research, appropriate models are first developed using ANN and ANFIS techniques to predict the LDC in natural streams. Then, an uncertainty analysis is performed for ANN and ANFIS models based on Monte-Carlo simulation. The input parameters of the models are related to hydraulic variables and stream geometry. Results indicate that ANN is a suitable model for predicting the LDC, but it is also associated with a high level of uncertainty. However, results of uncertainty analysis show that ANFIS model has less uncertainty; i.e. it is the best model for forecasting satisfactorily the LDC in natural streams.

  17. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Malvache, P.; Mourlevat, J.L.

    1993-01-01

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  18. Intelligent Flexible Materials for Space Structures: Expandable Habitat Engineering Development Unit

    Science.gov (United States)

    Hinkle, Jon; Sharpe, George; Lin, John; Wiley, Cliff; Timmers, Richard

    2010-01-01

    Expandable habitable elements are an enabling technology for human exploration in space and on planetary surfaces. Large geometries can be deployed from a small launch volume, allowing greater mission capability while reducing mass and improving robustness over traditional rigid shells. This report describes research performed by ILC Dover under the Intelligent Flexible Materials for Space Structures program on the design and manufacture of softgoods for LaRC's Expandable Habitat Engineering Development Unit (EDU). The EDU is a full-scale structural test article of an expandable hybrid habitat, integrating an expandable softgoods center section with two rigid end caps. The design of the bladder, restraint layer and a mock-up Thermal Micrometeoroid Cover is detailed together with the design of the interface hardware used to attach them to the end caps. The integration and design of two windows and a floor are also covered. Analysis was performed to study the effects of the open weave design, and to determine the correct webbing and fabric configuration. Stress analyses were also carried out on the interfaces between the softgoods and the end caps and windows. Testing experimentally determined the strength of the fabric and straps, and component testing was used to proof several critical parts of the design. This program established new manufacturing and design techniques that can be applied to future applications in expandable structures.

  19. Artificial Intelligence.

    Science.gov (United States)

    Wash, Darrel Patrick

    1989-01-01

    Making a machine seem intelligent is not easy. As a consequence, demand has been rising for computer professionals skilled in artificial intelligence and is likely to continue to go up. These workers develop expert systems and solve the mysteries of machine vision, natural language processing, and neural networks. (Editor)

  20. Measurement technique developments for LBE flows

    Energy Technology Data Exchange (ETDEWEB)

    Buchenau, D., E-mail: d.buchenau@fzd.de [Forschungszentrum Dresden-Rossendorf (FZD), 01314 Dresden (Germany); Eckert, S.; Gerbeth, G. [Forschungszentrum Dresden-Rossendorf (FZD), 01314 Dresden (Germany); Stieglitz, R. [Karlsruhe Institute of Technology (KIT), 76344 Eggenstein-Leopoldshafen (Germany); Dierckx, M. [SCK-CEN, Belgian Nuclear Research Centre, 2400 Mol (Belgium)

    2011-08-31

    We report on the development of measurement techniques for flows in lead-bismuth eutectic alloys (LBE). This paper covers the test results of newly developed contactless flow rate sensors as well as the development and test of the LIDAR technique for operational free surface level detection. The flow rate sensors are based on the flow-induced disturbance of an externally applied AC magnetic field which manifests itself by a modified amplitude or a modified phase of the AC field. Another concept of a force-free contactless flow meter uses a single cylindrical permanent magnet. The electromagnetic torque on the magnet caused by the liquid metal flow sets the magnet into rotation. The operation of those sensors has been demonstrated at liquid metal test loops for which comparative flow rate measurements are available, as well as at the LBE loops THESYS at KIT and WEBEXPIR at SCK-CEN. For the level detection a commercial LIDAR system was successfully tested at the WEBEXPIR facility in Mol and the THEADES loop in Karlsruhe.

  1. Developing critical thinking disposition and emotional intelligence of nursing students: a longitudinal research.

    Science.gov (United States)

    Kaya, Hülya; Şenyuva, Emine; Bodur, Gönül

    2017-01-01

    Emotional Intelligence is considered as an important characteristic of nurses that can affect the quality of their work including clinical decision-making, critical thinking, evidence and knowledge use in practice. The study is aimed to determine nursing students' critical thinking disposition and emotional intelligence in an academic year. A longitudinal design. The focus population of this longitudinal study consists of 197 freshman students studying at a faculty of nursing. Asymmetrical cluster sampling method was used to determine sample group and all the students registered in the first year were included in scope of the study. Information Form, California Critical Thinking Disposition Scale and Emotional Intelligence Assessment Scale were used for data collection. SPSS version 11.5 was used for data analysis. Nursing students have a low level of critical thinking disposition and intermediate level of emotional intelligence both at the beginning and end of academic year. There was no statistically significant difference in both skills at the beginning and end of year. There was a statistically significant difference between students' critical thinking disposition and emotional intelligence at the beginning of academic year. There was a positive correlation at a medium level between students' critical thinking disposition and emotional intelligence at the beginning and end of academic year. In light of these results, it is that suggested the study should be prolonged as longitudinal because development of both skills require a long time. The current study holds importance that it sheds light on other relevant studies and nursing education programs. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Study on virtual instrument developing system based on intelligent virtual control

    International Nuclear Information System (INIS)

    Tang Baoping; Cheng Fabin; Qin Shuren

    2005-01-01

    The paper introduces a non-programming developing system of a virtual instrument (VI), i.e., a virtual measurement instrument developing system (VMIDS) based on intelligent virtual control (IVC). The background of the IVC-based VMIDS is described briefly, and the hierarchical message bus (HMB)-based software architecture of VMIDS is discussed in detail. The three parts and functions of VMIDS are introduced, and the process of non-programming developing VI is further described

  3. Study on virtual instrument developing system based on intelligent virtual control

    Energy Technology Data Exchange (ETDEWEB)

    Tang Baoping; Cheng Fabin; Qin Shuren [Test Center, College of Mechanical Engineering, Chongqing University , Chongqing 400030 (China)

    2005-01-01

    The paper introduces a non-programming developing system of a virtual instrument (VI), i.e., a virtual measurement instrument developing system (VMIDS) based on intelligent virtual control (IVC). The background of the IVC-based VMIDS is described briefly, and the hierarchical message bus (HMB)-based software architecture of VMIDS is discussed in detail. The three parts and functions of VMIDS are introduced, and the process of non-programming developing VI is further described.

  4. Medical applications of artificial intelligence

    CERN Document Server

    Agah, Arvin

    2013-01-01

    Enhanced, more reliable, and better understood than in the past, artificial intelligence (AI) systems can make providing healthcare more accurate, affordable, accessible, consistent, and efficient. However, AI technologies have not been as well integrated into medicine as predicted. In order to succeed, medical and computational scientists must develop hybrid systems that can effectively and efficiently integrate the experience of medical care professionals with capabilities of AI systems. After providing a general overview of artificial intelligence concepts, tools, and techniques, Medical Ap

  5. Surgical robotics beyond enhanced dexterity instrumentation: a survey of machine learning techniques and their role in intelligent and autonomous surgical actions.

    Science.gov (United States)

    Kassahun, Yohannes; Yu, Bingbin; Tibebu, Abraham Temesgen; Stoyanov, Danail; Giannarou, Stamatia; Metzen, Jan Hendrik; Vander Poorten, Emmanuel

    2016-04-01

    Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical

  6. ANALYSIS DATA SETS USING HYBRID TECHNIQUES APPLIED ARTIFICIAL INTELLIGENCE BASED PRODUCTION SYSTEMS INTEGRATED DESIGN

    Directory of Open Access Journals (Sweden)

    Daniel-Petru GHENCEA

    2017-06-01

    Full Text Available The paper proposes a prediction model of behavior spindle from the point of view of the thermal deformations and the level of the vibrations by highlighting and processing the characteristic equations. This is a model analysis for the shaft with similar electro-mechanical characteristics can be achieved using a hybrid analysis based on artificial intelligence (genetic algorithms - artificial neural networks - fuzzy logic. The paper presents a prediction mode obtaining valid range of values for spindles with similar characteristics based on measured data sets from a few spindles test without additional measures being required. Extracting polynomial functions of graphs resulting from simultaneous measurements and predict the dynamics of the two features with multi-objective criterion is the main advantage of this method.

  7. A Smart Sensor Data Transmission Technique for Logistics and Intelligent Transportation Systems

    Directory of Open Access Journals (Sweden)

    Kyunghee Sun

    2018-03-01

    Full Text Available When it comes to Internet of Things systems that include both a logistics system and an intelligent transportation system, a smart sensor is one of the key elements to collect useful information whenever and wherever necessary. This study proposes the Smart Sensor Node Group Management Medium Access Control Scheme designed to group smart sensor devices and collect data from them efficiently. The proposed scheme performs grouping of portable sensor devices connected to a system depending on the distance from the sink node and transmits data by setting different buffer thresholds to each group. This method reduces energy consumption of sensor devices located near the sink node and enhances the IoT system’s general energy efficiency. When a sensor device is moved and, thus, becomes unable to transmit data, it is allocated to a new group so that it can continue transmitting data to the sink node.

  8. Algorithms in ambient intelligence

    NARCIS (Netherlands)

    Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.

    2004-01-01

    In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.

  9. ARDENT to develop advanced dosimetric techniques

    CERN Document Server

    Antonella Del Rosso

    2012-01-01

    Earlier this week, the EU-supported Marie Curie training network ARDENT kicked off at a meeting held at CERN. The overall aim of the project is the development of advanced instrumentation for radiation dosimetry. The applications range from radiation measurements around particle accelerators, onboard commercial flights and in space, to the characterization of radioactive waste and medicine, where accurate dosimetry is of vital importance.   The ARDENT (Advanced Radiation Dosimetry European Network Training) project is both a research and a training programme, which aims at developing new dosimetric techniques while providing 15 Early-Stage Researchers (ESR) with state-of-the-art training. The project, coordinated by CERN, is funded by the European Union with a contribution of about 3.9 million euros over four years. The ARDENT initiative will focus on three main technologies: gas detectors, in particular Gas Electron Multipliers (GEM) and Tissue Equivalent Proportional Counters (TEPC); solid stat...

  10. A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture.

    Science.gov (United States)

    Chen, Yen-Lin; Chiang, Hsin-Han; Chiang, Chuan-Yen; Liu, Chuan-Ming; Yuan, Shyan-Ming; Wang, Jenq-Haur

    2012-01-01

    This study proposes a vision-based intelligent nighttime driver assistance and surveillance system (VIDASS system) implemented by a set of embedded software components and modules, and integrates these modules to accomplish a component-based system framework on an embedded heterogamous dual-core platform. Therefore, this study develops and implements computer vision and sensing techniques of nighttime vehicle detection, collision warning determination, and traffic event recording. The proposed system processes the road-scene frames in front of the host car captured from CCD sensors mounted on the host vehicle. These vision-based sensing and processing technologies are integrated and implemented on an ARM-DSP heterogamous dual-core embedded platform. Peripheral devices, including image grabbing devices, communication modules, and other in-vehicle control devices, are also integrated to form an in-vehicle-embedded vision-based nighttime driver assistance and surveillance system.

  11. Applying predictive analytics to develop an intelligent risk detection application for healthcare contexts.

    Science.gov (United States)

    Moghimi, Fatemeh Hoda; Cheung, Michael; Wickramasinghe, Nilmini

    2013-01-01

    Healthcare is an information rich industry where successful outcomes require the processing of multi-spectral data and sound decision making. The exponential growth of data and big data issues coupled with a rapid increase of service demands in healthcare contexts today, requires a robust framework enabled by IT (information technology) solutions as well as real-time service handling in order to ensure superior decision making and successful healthcare outcomes. Such a context is appropriate for the application of real time intelligent risk detection decision support systems using predictive analytic techniques such as data mining. To illustrate the power and potential of data science technologies in healthcare decision making scenarios, the use of an intelligent risk detection (IRD) model is proffered for the context of Congenital Heart Disease (CHD) in children, an area which requires complex high risk decisions that need to be made expeditiously and accurately in order to ensure successful healthcare outcomes.

  12. The Multiple Intelligence Based Enrichment Module on the Development of Human Potential: Examining Its Impact and the Views of Teachers

    Science.gov (United States)

    Azid, Nurulwahida Hj; Yaacob, Aizan; Shaik-Abdullah, Sarimah

    2016-01-01

    Purpose: Howard Gardners' concept of multiple intelligence (MI) offers an alternative perspective on intelligence which highlights the importance of acknowledging learner diversity, individual talents and the development of human potentials. MI has been used as a basis for the construction of modular enrichment activities to facilitate the…

  13. Psychovisual masks and intelligent streaming RTP techniques for the MPEG-4 standard

    Science.gov (United States)

    Mecocci, Alessandro; Falconi, Francesco

    2003-06-01

    In today multimedia audio-video communication systems, data compression plays a fundamental role by reducing the bandwidth waste and the costs of the infrastructures and equipments. Among the different compression standards, the MPEG-4 is becoming more and more accepted and widespread. Even if one of the fundamental aspects of this standard is the possibility of separately coding video objects (i.e. to separate moving objects from the background and adapt the coding strategy to the video content), currently implemented codecs work only at the full-frame level. In this way, many advantages of the flexible MPEG-4 syntax are missed. This lack is due both to the difficulties in properly segmenting moving objects in real scenes (featuring an arbitrary motion of the objects and of the acquisition sensor), and to the current use of these codecs, that are mainly oriented towards the market of DVD backups (a full-frame approach is enough for these applications). In this paper we propose a codec for MPEG-4 real-time object streaming, that codes separately the moving objects and the scene background. The proposed codec is capable of adapting its strategy during the transmission, by analysing the video currently transmitted and setting the coder parameters and modalities accordingly. For example, the background can be transmitted as a whole or by dividing it into "slightly-detailed" and "highly detailed" zones that are coded in different ways to reduce the bit-rate while preserving the perceived quality. The coder can automatically switch in real-time, from one modality to the other during the transmission, depending on the current video content. Psychovisual masks and other video-content based measurements have been used as inputs for a Self Learning Intelligent Controller (SLIC) that changes the parameters and the transmission modalities. The current implementation is based on the ISO 14496 standard code that allows Video Objects (VO) transmission (other Open Source Codes

  14. Towards Intelligent Interpretation of Low Strain Pile Integrity Testing Results Using Machine Learning Techniques.

    Science.gov (United States)

    Cui, De-Mi; Yan, Weizhong; Wang, Xiao-Quan; Lu, Lie-Min

    2017-10-25

    Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT's turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts' interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology's effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction.

  15. The Development of Multiple Intelligence Capabilities for Early Childhood Development Center, Local Administration Organization in Chaiyaphum Province

    Science.gov (United States)

    Siphai, Sunan; Supandee, Terdsak; Raksapuk, Chunpit; Poopayang, Piangkhae; Kratoorerk, Sangsan

    2017-01-01

    The aim of this research is to promote multiple intelligence capabilities for Early Childhood Care Center of a Sub-district Administration Organization in Chaiyaphum Province. The sample applied were 61 children aging between 3 and 5 years old at Child Development Center, Tambon Ban Kok, Amphoe Chaturus, Chaiyaphum Province, who were selected…

  16. Development for advanced materials and testing techniques

    Energy Technology Data Exchange (ETDEWEB)

    Hishinuma, Akimichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1998-03-01

    Recent studies using a JMTR and research reactors of JRR-2 and JRR-3 are briefly summarized. Small specimen testing techniques (SSTT) required for an effective use of irradiation volume and also irradiated specimens have been developed focussing on tensile test, fatigue test, Charpy test and small punch test. By using the small specimens of 0.1 - several mm in size, similar values of tensile and fatigue properties to those by standard size specimens can be taken, although the ductile-brittle transition temperature (DBTT) depends strongly on Charpy specimen size. As for advanced material development, R and D about low activation ferritic steels have been done to investigate irradiation response. The low activation ferritic steel, so-called F82H jointly-developed by JAERI and NKK for fusion, has been confirmed to have good irradiation resistance within a limited dose and now selected as a standard material in the fusion material community. It is also found that TiAi intermetallic compounds, which never been considered for nuclear application in the past, have an excellent irradiation resistance under an irradiation condition. Such knowledge can bring about a large expectation for developing advanced nuclear materials. (author)

  17. Development and evaluation of intelligent machine tools based on knowledge evolution in M2M environment

    International Nuclear Information System (INIS)

    Kim, Dong Hoon; Song, Jun Yeob; Lee, Jong Hyun; Cha, Suk Keun

    2009-01-01

    In the near future, the foreseen improvement in machine tools will be in the form of a knowledge evolution-based intelligent device. The goal of this study is to develop intelligent machine tools having knowledge-evolution capability in Machine to Machine (M2M) wired and wireless environment. The knowledge evolution-based intelligent machine tools are expected to be capable of gathering knowledge autonomously, producing knowledge, understanding knowledge, applying reasoning to knowledge, making new decisions, dialoguing with other machines, etc. The concept of the knowledge-evolution intelligent machine originated from the process of machine control operation by the sense, dialogue and decision of a human expert. The structure of knowledge evolution in M2M and the scheme for a dialogue agent among agent-based modules such as a sensory agent, a dialogue agent and an expert system (decision support agent) are presented in this paper, and work-offset compensation from thermal change and recommendation of cutting condition are performed on-line for knowledge-evolution verification

  18. Development of an intelligent system for ultrasonic flaw classification in weldments

    International Nuclear Information System (INIS)

    Song, Sung-Jin; Kim, Hak-Joon; Cho, Hyeon

    2002-01-01

    Even though ultrasonic pattern recognition is considered as the most effective and promising approach to flaw classification in weldments, its application to the realistic field inspection is still very limited due to the crucial barriers in cost, time and reliability. To reduce such barriers, previously we have proposed an intelligent system approach that consisted of the following four ingredients: (1) a PC-based ultrasonic testing (PC-UT) system; (2) an effective invariant ultrasonic flaw classification algorithm; (3) an intelligent flaw classification software; and (4) a database with abundant experimental flaw signals. In the present work, for performing the ultrasonic flaw classification in weldments in a real-time fashion in many real word situations, we develop an intelligent system, which is called the 'Intelligent Ultrasonic Evaluation System (IUES)' by the integration of the above four ingredients into a single, unified system. In addition, for the improvement of classification accuracy of flaws, especially slag inclusions, we expand the feature set by adding new informative features, and demonstrate the enhanced performance of the IUES with flaw signals in the database constructed previously. And then, to take care of the increased redundancy in the feature set due to the addition of features, we also propose two efficient schemes for feature selection: the forward selection with trial and error, and the forward selection with criteria of the error probability and the linear correlation coefficients of individual features

  19. From Management Information Systems to Business Intelligence: The Development of Management Information Needs

    Directory of Open Access Journals (Sweden)

    Gėlytė Kazakevičienė

    2013-09-01

    Full Text Available Despite the advances in IT, information systems intended for management informing did not uniformly fulfil the increased expectations of users; this can be said mostly about complex information needs. Although some of the technologies for supporting complicated insights, like management decision support systems and technologies, experienced reduction in interest both from researchers and practitioners, this did not reduce the importance of well-supported business informing and decision making. Being attributed to the group of intelligent systems and technologies, decision support (DS technologies have been largely supplemented by business intelligence (BI technologies. Both types of technologies are supported by respective information technologies, which often appear to be quite closely related. The objective of this paper is to define relations between simple and complex informing intended to satisfy different sets of needs and provided by different sets of support tools. The paper attempts to put together decision support and business intelligence technologies, based on common goals of sense-making and use of advanced analytical tools. A model of two interconnected cycles has been developed to relate the activities of decision support and business intelligence. Empirical data from earlier research is used to direct possible further insights into this area.

  20. Intelligent Frameworks for Instructional Design.

    Science.gov (United States)

    Spector, J. Michael; And Others

    1992-01-01

    Presents a taxonomy describing various uses of artificial intelligence techniques in automated instructional development systems. Instructional systems development is discussed in relation to the design of computer-based instructional courseware; two systems being developed at the Air Force Armstrong Laboratory are reviewed; and further research…

  1. Growth, behavior, development and intelligence in rural children between 1-3 years of life.

    Science.gov (United States)

    Agarwal, D K; Awasthy, A; Upadhyay, S K; Singh, P; Kumar, J; Agarwal, K N

    1992-04-01

    In a rural cohort of 625 children registered from 1981 to 1983 in 10 villages of K.V. Block, Varanasi, 196 children were assessed for physical growth, development, intelligence and concept development between 1 and 3 years of age. Home environment was also assessed using Caldwell Home inventory. These rural children remained below 3rd centile of NCHS standard for weight, height, skull and mid-arm circumferences throughout the study. Malnourished children scored poorly in all the areas of development, i.e., motor, adaptive, language and personal social, 9% in Grade I and 16.6% children in Grade II + III had IQ less than 79 (inferior). Concept for color shape and size was poorly developed in malnourished children. Maternal involvement and stimulation was strongly associated with better behavior development and intelligence. Multiple regression analysis showed that the effect of home environment on development and intelligence was of a higher magnitude as compared to status and family variables and nutritional status during 1-3 years of age.

  2. ITS-NANO - Prioritising nanosafety research to develop a stakeholder driven intelligent testing strategy

    DEFF Research Database (Denmark)

    Stone, V.; Pozzi-Mucelli, S.; Tran, L.

    2014-01-01

    of the current and future risk assessment of NMs. RESULTS: The framework for future research has been developed from the opinions of over 80 stakeholders, that describes the research priorities for effective development of an intelligent testing strategy (ITS) to allow risk evaluation of NMs. In this context......BACKGROUND: To assess the risk of all nanomaterials (NMs) on a case-by-case basis is challenging in terms of financial, ethical and time resources. Instead a more intelligent approach to knowledge gain and risk assessment is required. METHODS: A framework of future research priorities was developed......-priority research areas are described via a series of stepping stones, or hexagon diagrams structured into a time perspective. Importantly, this framework is flexible, allowing individual stakeholders to identify where their own activities and expertise are positioned within the prioritisation pathway...

  3. On the Development of Intelligent Railway Information and Safety Systems: An Overview of Current Research

    Directory of Open Access Journals (Sweden)

    Dániel Tokody

    2018-03-01

    Full Text Available The present article focuses on the research and development planning for innovative railway systems. Within such a general framework, the specific objectives of the research have been defined within the framework of a large Intelligent Railway System project in Hungary. Our theoretical research work at the university is combined with practical experience gained at the Hungarian State Railways. In the course of this research work, the development of an intelligent railway system has been investigated by leveraging on the fruitful cooperation between academic and industrial partners, in order to promote the application and integration possibilities of the development results, as well as the introduction of innovative components in the railway system. In such a context, this article discusses the research plan, preliminary and long-term expected results, sharing objectives and experiences with the aim of providing novel views in an extremely current and challenging field of research.

  4. The Association Between Maternal Subclinical Hypothyroidism and Growth, Development, and Childhood Intelligence: A Meta-analysis

    Science.gov (United States)

    Liu, Yahong; Chen, Hui; Jing, Chen; Li, FuPin

    2018-06-01

    To explore the association between maternal subclinical hypothyroidism (SCH) in pregnancy and the somatic and intellectual development of their offspring. Using RevMan 5.3 software, a meta-analysis of cohort studies published from inception to May 2017, focusing on the association between maternal SCH in pregnancy and childhood growth, development and intelligence, was performed. Sources included the Cochrane Library, Pub-Med, Web of Science, China National Knowledge Infrastructure and Wan Fang Data. Analysis of a total of 15 cohort studies involving 1.896 pregnant women with SCH revealed that SCH in pregnancy was significantly associated with the intelligence (p=0.0007) and motor development (pdevelopment, low birth weight, premature delivery, fetal distress and fetal growth restriction.

  5. Pay attention to the enterprise competitive intelligence analysis research promotion enterprise scientific research production and product development

    International Nuclear Information System (INIS)

    Yang Yan

    2014-01-01

    This article covers the competitive intelligence content and five characteristics, and on the American Competitive intelligence Outstanding Company's place situation, shows fully the competitive intelligence constructs the core competitive power regarding the enterprise to have the significant function, Its contribution has already hold the pivotal status in the world famous enterprise. It is an important cornerstone for enterprises which construct the core competitive power. Along with the enterprise competition environment rapid change, the competitive intelligence importance suddenly to reveal day by day. Just like the world richest family Microsoft Corporation president Bill. Gates asserted that, How to collect, How to analysis, how to manage and how to use information, lt will decide the enterprise victory and loss. And unified the enterprise scientific research production the special details, take 'To develop the SF_6 New Product' to introduce as the example how did the enterprise competition intelligence, as well as how did the information development and using in it. (author)

  6. An intelligent knowledge-based and customizable home care system framework with ubiquitous patient monitoring and alerting techniques.

    Science.gov (United States)

    Chen, Yen-Lin; Chiang, Hsin-Han; Yu, Chao-Wei; Chiang, Chuan-Yen; Liu, Chuan-Ming; Wang, Jenq-Haur

    2012-01-01

    This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

  7. An Intelligent Knowledge-Based and Customizable Home Care System Framework with Ubiquitous Patient Monitoring and Alerting Techniques

    Directory of Open Access Journals (Sweden)

    Yen-Lin Chen

    2012-08-01

    Full Text Available This study develops and integrates an efficient knowledge-based system and a component-based framework to design an intelligent and flexible home health care system. The proposed knowledge-based system integrates an efficient rule-based reasoning model and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures based on software modules, video camera sensors, communication devices, and physiological sensor information. This knowledge-based system offers high flexibility for improving and extending the system further to meet the monitoring demands of new patient and caregiver health care by updating the knowledge rules in the inference mechanism. All of the proposed functional components in this study are reusable, configurable, and extensible for system developers. Based on the experimental results, the proposed intelligent homecare system demonstrates that it can accomplish the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions.

  8. Optimization of fuel exchange machine operation for boiling water reactors using an artificial intelligence technique

    International Nuclear Information System (INIS)

    Sekimizu, K.; Araki, T.; Tatemichi, S.I.

    1987-01-01

    Optimization of fuel assembly exchange machine movements during periodic refueling outage is discussed. The fuel assembly movements during a fuel shuffling were examined, and it was found that the fuel assembly movements consist of two different movement sequences;one is the ''PATH,'' which begins at a discharged fuel assembly and terminates at a fresh fuel assembly, and the other is the ''LOOP,'' where fuel assemblies circulate in the core. It is also shown that fuel-loading patterns during the fuel shuffling can be expressed by the state of each PATH, which is the number of elements already accomplished in the PATH actions. Based on this fact, a scheme to determine a fuel assembly movement sequence within the constraint was formulated using the artificial intelligence language PROLOG. An additional merit to the scheme is that it can simultaneously evaluate fuel assembly movement, due to the control rods and local power range monitor exchange, in addition to normal fuel shuffling. Fuel assembly movements, for fuel shuffling in a 540-MW(electric) boiling water reactor power plant, were calculated by this scheme. It is also shown that the true optimization to minimize the fuel exchange machine movements would be costly to obtain due to the number of alternatives that would need to be evaluated. However, a method to obtain a quasi-optimum solution is suggested

  9. Intelligent Traffic Quantification System

    Science.gov (United States)

    Mohanty, Anita; Bhanja, Urmila; Mahapatra, Sudipta

    2017-08-01

    Currently, city traffic monitoring and controlling is a big issue in almost all cities worldwide. Vehicular ad-hoc Network (VANET) technique is an efficient tool to minimize this problem. Usually, different types of on board sensors are installed in vehicles to generate messages characterized by different vehicle parameters. In this work, an intelligent system based on fuzzy clustering technique is developed to reduce the number of individual messages by extracting important features from the messages of a vehicle. Therefore, the proposed fuzzy clustering technique reduces the traffic load of the network. The technique also reduces congestion and quantifies congestion.

  10. Development of an Intelligent Car Engine Fault Troubleshooting ...

    African Journals Online (AJOL)

    2016-12-01

    mechanic ... The method of fact-finding called knowledge acquisition which is an .... decision making so far is the development of Decision ..... “An Expert System for Planning Landfill Restoration”, Water Scienceand Technology, Vol.

  11. Emotionally intelligent learner leadership development: a case study

    African Journals Online (AJOL)

    seldom ideal places to develop leadership skills because policies and regulations ..... componentof leadership (vision-focus, vision-communication, value ..... reported a low self-esteem for L. L seemed to be unsure of himself / herself, hesitant,.

  12. Profiling nonhuman intelligence: An exercise in developing unbiased tools for describing other "types" of intelligence on earth

    Science.gov (United States)

    Herzing, Denise L.

    2014-02-01

    Intelligence has historically been studied by comparing nonhuman cognitive and language abilities with human abilities. Primate-like species, which show human-like anatomy and share evolutionary lineage, have been the most studied. However, when comparing animals of non-primate origins our abilities to profile the potential for intelligence remains inadequate. Historically our measures for nonhuman intelligence have included a variety of tools: (1) physical measurements - brain to body ratio, brain structure/convolution/neural density, presence of artifacts and physical tools, (2) observational and sensory measurements - sensory signals, complexity of signals, cross-modal abilities, social complexity, (3) data mining - information theory, signal/noise, pattern recognition, (4) experimentation - memory, cognition, language comprehension/use, theory of mind, (5) direct interfaces - one way and two way interfaces with primates, dolphins, birds and (6) accidental interactions - human/animal symbiosis, cross-species enculturation. Because humans tend to focus on "human-like" attributes and measures and scientists are often unwilling to consider other "types" of intelligence that may not be human equated, our abilities to profile "types" of intelligence that differ on a variety of scales is weak. Just as biologists stretch their definitions of life to look at extremophiles in unusual conditions, so must we stretch our descriptions of types of minds and begin profiling, rather than equating, other life forms we may encounter.

  13. Computational Intelligence in Image Processing

    CERN Document Server

    Siarry, Patrick

    2013-01-01

    Computational intelligence based techniques have firmly established themselves as viable, alternate, mathematical tools for more than a decade. They have been extensively employed in many systems and application domains, among these signal processing, automatic control, industrial and consumer electronics, robotics, finance, manufacturing systems, electric power systems, and power electronics. Image processing is also an extremely potent area which has attracted the atten­tion of many researchers who are interested in the development of new computational intelligence-based techniques and their suitable applications, in both research prob­lems and in real-world problems. Part I of the book discusses several image preprocessing algorithms; Part II broadly covers image compression algorithms; Part III demonstrates how computational intelligence-based techniques can be effectively utilized for image analysis purposes; and Part IV shows how pattern recognition, classification and clustering-based techniques can ...

  14. Enabling South-Africa: development of an intelligent gateway

    CSIR Research Space (South Africa)

    Evans, ED

    1993-08-01

    Full Text Available are catered for on all host protocols. The resulting gateway is operated on a sound business footing for the benefit of end-users and expert searchers in Southern Africa. The development of the system and the business are described in the paper....

  15. Development of Two Intelligent Spray Systems for Ornamental Nurseries

    Science.gov (United States)

    Current application technology for floral, nursery, and other specialty crop production wastes significant amounts of pesticides. Two different real-time variable-rate sprayer prototypes for ornamental nursery and tree crops were developed to deliver chemicals on target areas as needed. The first pr...

  16. Intelligent Tools for Planning Knowledge base Development and Verification

    Science.gov (United States)

    Chien, Steve A.

    1996-01-01

    A key obstacle hampering fielding of AI planning applications is the considerable expense of developing, verifying, updating, and maintaining the planning knowledge base (KB). Planning systems must be able to compare favorably in terms of software lifecycle costs to other means of automation such as scripts or rule-based expert systems.

  17. Developing Cultural Intelligence for Global Leadership through Mindfulness

    Science.gov (United States)

    Tuleja, Elizabeth A.

    2014-01-01

    Understanding how businesses function in relation to cultural and societal influences is critical for today's business leader who wants to interact competently across borders. However, developing and evaluating such competence is a challenge. One concept that provides a holistic conceptualization of intercultural competence is the notion of…

  18. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Cognitive reliability analysis technique: [Technical report, May 1986-June 1987

    International Nuclear Information System (INIS)

    Woods, D.D.; Roth, E.M.

    1987-11-01

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 34 refs., 7 figs., 1 tab

  19. Development of intelligent semantic search system for rubber research data in Thailand

    Science.gov (United States)

    Kaewboonma, Nattapong; Panawong, Jirapong; Pianhanuruk, Ekkawit; Buranarach, Marut

    2017-10-01

    The rubber production of Thailand increased not only by strong demand from the world market, but was also stimulated strongly through the replanting program of the Thai Government from 1961 onwards. With the continuous growth of rubber research data volume on the Web, the search for information has become a challenging task. Ontologies are used to improve the accuracy of information retrieval from the web by incorporating a degree of semantic analysis during the search. In this context, we propose an intelligent semantic search system for rubber research data in Thailand. The research methods included 1) analyzing domain knowledge, 2) ontologies development, and 3) intelligent semantic search system development to curate research data in trusted digital repositories may be shared among the wider Thailand rubber research community.

  20. A development framework for artificial intelligence based distributed operations support systems

    Science.gov (United States)

    Adler, Richard M.; Cottman, Bruce H.

    1990-01-01

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

  1. Development of intelligent Eddy Current Testing (ECT) system for PWR steam generator tube inspection

    International Nuclear Information System (INIS)

    Kawata, K.; Kawase, N.; Kurokawa, M.; Asada, Y.

    2005-01-01

    The intelligent ECT system was developed for the inspection of heat transfer tubes of the steam generator of the PWR plant. It consists of intelligent probe, data acquisition unit and data analysis system. The probe combines 24 channels inclined lay out drive coils and thin film pick-up coils with built-in electric circuits to provide high inspection capability equivalent to rotating coil ECT and high-speed inspection equivalent to conventional bobbin coil ECT. The advanced data analysis system that has filtering and automatic analysis functions is also developed to enable fast and precise analysis of large volume inspection data. The system was qualified by confirmation tests in FY 2003 to show thinned thickness sizing accuracy within ± 5%. (T. Tanaka)

  2. Intelligent feature selection techniques for pattern classification of Lamb wave signals

    International Nuclear Information System (INIS)

    Hinders, Mark K.; Miller, Corey A.

    2014-01-01

    Lamb wave interaction with flaws is a complex, three-dimensional phenomenon, which often frustrates signal interpretation schemes based on mode arrival time shifts predicted by dispersion curves. As the flaw severity increases, scattering and mode conversion effects will often dominate the time-domain signals, obscuring available information about flaws because multiple modes may arrive on top of each other. Even for idealized flaw geometries the scattering and mode conversion behavior of Lamb waves is very complex. Here, multi-mode Lamb waves in a metal plate are propagated across a rectangular flat-bottom hole in a sequence of pitch-catch measurements corresponding to the double crosshole tomography geometry. The flaw is sequentially deepened, with the Lamb wave measurements repeated at each flaw depth. Lamb wave tomography reconstructions are used to identify which waveforms have interacted with the flaw and thereby carry information about its depth. Multiple features are extracted from each of the Lamb wave signals using wavelets, which are then fed to statistical pattern classification algorithms that identify flaw severity. In order to achieve the highest classification accuracy, an optimal feature space is required but it’s never known a priori which features are going to be best. For structural health monitoring we make use of the fact that physical flaws, such as corrosion, will only increase over time. This allows us to identify feature vectors which are topologically well-behaved by requiring that sequential classes “line up” in feature vector space. An intelligent feature selection routine is illustrated that identifies favorable class distributions in multi-dimensional feature spaces using computational homology theory. Betti numbers and formal classification accuracies are calculated for each feature space subset to establish a correlation between the topology of the class distribution and the corresponding classification accuracy

  3. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    Science.gov (United States)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  4. INTELLIGENT NETWORKS, SMART GRIDS CONCEPT, CRUCIAL TECHNOLOGIES FOR SUSTAINABLE DEVELOPMENT

    Directory of Open Access Journals (Sweden)

    Constantin RADU

    2011-05-01

    Full Text Available In this article is presented the concept of smart grids, a very important technology for sustainable development. In the context of globalization of the world lives in an increasingly complex security environment, with rapid changes, some obvious, others less obvious implications in the short, medium or long term, international, national, local and up to every citizen. All countries in the globalized world economy is facing energy problems in terms of climate change have intensified in the twentieth century.

  5. Optimization of freeform surfaces using intelligent deformation techniques for LED applications

    Science.gov (United States)

    Isaac, Annie Shalom; Neumann, Cornelius

    2018-04-01

    For many years, optical designers have great interests in designing efficient optimization algorithms to bring significant improvement to their initial design. However, the optimization is limited due to a large number of parameters present in the Non-uniform Rationaly b-Spline Surfaces. This limitation was overcome by an indirect technique known as optimization using freeform deformation (FFD). In this approach, the optical surface is placed inside a cubical grid. The vertices of this grid are modified, which deforms the underlying optical surface during the optimization. One of the challenges in this technique is the selection of appropriate vertices of the cubical grid. This is because these vertices share no relationship with the optical performance. When irrelevant vertices are selected, the computational complexity increases. Moreover, the surfaces created by them are not always feasible to manufacture, which is the same problem faced in any optimization technique while creating freeform surfaces. Therefore, this research addresses these two important issues and provides feasible design techniques to solve them. Finally, the proposed techniques are validated using two different illumination examples: street lighting lens and stop lamp for automobiles.

  6. Development of a method of continuous improvement of services using the Business Intelligence tools

    Directory of Open Access Journals (Sweden)

    Svetlana V. Kulikova

    2018-01-01

    Full Text Available The purpose of the study was to develop a method of continuous improvement of services using the Business Intelligence tools.Materials and methods: the materials are used on the concept of the Deming Cycle, methods and Business Intelligence technologies, Agile methodology and SCRUM.Results: the article considers the problem of continuous improvement of services and offers solutions using methods and technologies of Business Intelligence. In this case, the purpose of this technology is to solve and make the final decision regarding what needs to be improved in the current organization of services. In other words, Business Intelligence helps the product manager to see what is hidden from the “human eye” on the basis of received and processed data. Development of a method based on the concept of the Deming Cycle and Agile methodologies, and SCRUM.The article describes the main stages of development of method based on activity of the enterprise. It is necessary to fully build the Business Intelligence system in the enterprise to identify bottlenecks and justify the need for their elimination and, in general, for continuous improvement of the services. This process is represented in the notation of DFD. The article presents a scheme for the selection of suitable agile methodologies.The proposed concept of the solution of the stated objectives, including methods of identification of problems through Business Intelligence technology, development of the system for troubleshooting and analysis of results of the introduced changes. The technical description of the project is given.Conclusion: following the work of the authors there was formed the concept of the method for the continuous improvement of the services, using the Business Intelligence technology with the specifics of the enterprises, offering SaaS solutions. It was also found that when using this method, the recommended development methodology is SCRUM. The result of this scientific

  7. Microgrid central controller development and hierarchical control implemetation in the intelligent microgrid lab of Aalborg University

    OpenAIRE

    Meng, Lexuan; Savaghebi, Mehdi; Andrade, Fabio; Vasquez Quintero, Juan Carlos; Guerrero, Josep M.; Graells Sobré, Moisès

    2015-01-01

    This paper presents the development of a microgrid central controller in an inverter-based intelligent microgrid (iMG) lab in Aalborg University, Denmark. The iMG lab aims to provide a flexible experimental platform for comprehensive studies of microgrids. The complete control system applied in this lab is based on the hierarchical control scheme for microgrids and includes primary, secondary and tertiary control. The structure of the lab, including the lab facilities, configurations and comm...

  8. Development of a utility system for charged particle nuclear reaction data by using intelligentPad

    International Nuclear Information System (INIS)

    Aoyama, Shigeyoshi; Ohbayashi, Yoshihide; Masui, Hiroshi; Kato, Kiyoshi; Chiba, Masaki

    2000-01-01

    We have developed a utility system, WinNRDF2, for a nuclear charged particle reaction data of NRDF (Nuclear Reaction Data File) on the IntelligentPad architecture. By using the system, we can search the experimental data of a charged particle reaction of NRDF. Furthermore, we also see the experimental data by using graphic pads which was made through the CONTIP project. (author)

  9. Development of a National Repository of Digital Forensic Intelligence

    Directory of Open Access Journals (Sweden)

    Mark Weiser

    2006-06-01

    Full Text Available Many people do all of their banking online, we and our children communicate with peers through computer systems, and there are many jobs that require near continuous interaction with computer systems. Criminals, however, are also “connected”, and our online interaction provides them a conduit into our information like never before. Our credit card numbers and other fiscal information are at risk, our children's personal information is exposed to the world, and our professional reputations are on the line.The discipline of Digital Forensics in law enforcement agencies around the nation and world has grown to match the increased risk and potential for cyber crimes. Even crimes that are not themselves computer-based, may be solved or prosecuted based on digital evidence left behind by the perpetrator. However, no widely accepted mechanism to facilitate sharing of ideas and methodologies has emerged. Different agencies re-develop approaches that have been tested in other jurisdictions. Even within a single agency, there is often significant redundant work. There is great potential efficiency gain in sharing information from digital forensic investigations.This paper describes an on-going design and development project between Oklahoma State University’s Center for Telecommunications and Network Security and the Defense Cyber Crimes Center to develop a Repository of Digital Forensic Knowledge. In its full implementation, the system has potential to provide exceptional gains in efficiency for examiners and investigators. It provides a better conduit to share relevant information between agencies and a structure through which cases can be cross-referenced to have the most impact on a current investigation.

  10. Application of the SP theory of intelligence to the understanding of natural vision and the development of computer vision.

    Science.gov (United States)

    Wolff, J Gerard

    2014-01-01

    The SP theory of intelligence aims to simplify and integrate concepts in computing and cognition, with information compression as a unifying theme. This article is about how the SP theory may, with advantage, be applied to the understanding of natural vision and the development of computer vision. Potential benefits include an overall simplification of concepts in a universal framework for knowledge and seamless integration of vision with other sensory modalities and other aspects of intelligence. Low level perceptual features such as edges or corners may be identified by the extraction of redundancy in uniform areas in the manner of the run-length encoding technique for information compression. The concept of multiple alignment in the SP theory may be applied to the recognition of objects, and to scene analysis, with a hierarchy of parts and sub-parts, at multiple levels of abstraction, and with family-resemblance or polythetic categories. The theory has potential for the unsupervised learning of visual objects and classes of objects, and suggests how coherent concepts may be derived from fragments. As in natural vision, both recognition and learning in the SP system are robust in the face of errors of omission, commission and substitution. The theory suggests how, via vision, we may piece together a knowledge of the three-dimensional structure of objects and of our environment, it provides an account of how we may see things that are not objectively present in an image, how we may recognise something despite variations in the size of its retinal image, and how raster graphics and vector graphics may be unified. And it has things to say about the phenomena of lightness constancy and colour constancy, the role of context in recognition, ambiguities in visual perception, and the integration of vision with other senses and other aspects of intelligence.

  11. Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique.

    Science.gov (United States)

    Mukunthan, B; Nagaveni, N

    2014-01-01

    In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy.

  12. Intelligent (Autonomous) Power Controller Development for Human Deep Space Exploration

    Science.gov (United States)

    Soeder, James; Raitano, Paul; McNelis, Anne

    2016-01-01

    As NASAs Evolvable Mars Campaign and other exploration initiatives continue to mature they have identified the need for more autonomous operations of the power system. For current human space operations such as the International Space Station, the paradigm is to perform the planning, operation and fault diagnosis from the ground. However, the dual problems of communication lag as well as limited communication bandwidth beyond GEO synchronous orbit, underscore the need to change the operation methodology for human operation in deep space. To address this need, for the past several years the Glenn Research Center has had an effort to develop an autonomous power controller for human deep space vehicles. This presentation discusses the present roadmap for deep space exploration along with a description of conceptual power system architecture for exploration modules. It then contrasts the present ground centric control and management architecture with limited autonomy on-board the spacecraft with an advanced autonomous power control system that features ground based monitoring with a spacecraft mission manager with autonomous control of all core systems, including power. It then presents a functional breakdown of the autonomous power control system and examines its operation in both normal and fault modes. Finally, it discusses progress made in the development of a real-time power system model and how it is being used to evaluate the performance of the controller and well as using it for verification of the overall operation.

  13. Architecture for Business Intelligence in the Healthcare Sector

    Science.gov (United States)

    Lee, Sang Young

    2018-03-01

    Healthcare environment is growing to include not only the traditional information systems, but also a business intelligence platform. For executive leaders, consultants, and analysts, there is no longer a need to spend hours in design and develop of typical reports or charts, the entire solution can be completed through using Business Intelligence software. The current paper highlights the advantages of big data analytics and business intelligence in the healthcare industry. In this paper, In this paper we focus our discussion around intelligent techniques and methodologies which are recently used for business intelligence in healthcare.

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

    Science.gov (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

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

  15. Application of artificial intelligence techniques to the acceleration of Monte Carlo transport calculations

    International Nuclear Information System (INIS)

    Maconald, J.L.; Cashwell, E.D.

    1978-09-01

    The techniques of learning theory and pattern recognition are used to learn splitting surface locations for the Monte Carlo neutron transport code MCN. A study is performed to determine default values for several pattern recognition and learning parameters. The modified MCN code is used to reduce computer cost for several nontrivial example problems

  16. Developing a fluid intelligence scale through a combination of Rasch modeling and cognitive psychology.

    Science.gov (United States)

    Primi, Ricardo

    2014-09-01

    Ability testing has been criticized because understanding of the construct being assessed is incomplete and because the testing has not yet been satisfactorily improved in accordance with new knowledge from cognitive psychology. This article contributes to the solution of this problem through the application of item response theory and Susan Embretson's cognitive design system for test development in the development of a fluid intelligence scale. This study is based on findings from cognitive psychology; instead of focusing on the development of a test, it focuses on the definition of a variable for the creation of a criterion-referenced measure for fluid intelligence. A geometric matrix item bank with 26 items was analyzed with data from 2,797 undergraduate students. The main result was a criterion-referenced scale that was based on information from item features that were linked to cognitive components, such as storage capacity, goal management, and abstraction; this information was used to create the descriptions of selected levels of a fluid intelligence scale. The scale proposed that the levels of fluid intelligence range from the ability to solve problems containing a limited number of bits of information with obvious relationships through the ability to solve problems that involve abstract relationships under conditions that are confounded with an information overload and distraction by mixed noise. This scale can be employed in future research to provide interpretations for the measurements of the cognitive processes mastered and the types of difficulty experienced by examinees. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  17. Intelligent Information Retrieval: Diagnosing Information Need. Part I. The Theoretical Framework for Developing an Intelligent IR Tool.

    Science.gov (United States)

    Cole, Charles

    1998-01-01

    Suggests that the principles underlying the procedure used by doctors to diagnose a patient's disease are useful in the design of intelligent information-retrieval systems because the task of the doctor is conceptually similar to the computer or human intermediary's task in information retrieval: to draw out the user's query/information need.…

  18. Intelligent playgrounds

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2009-01-01

    This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...

  19. Designing with computational intelligence

    CERN Document Server

    Lopes, Heitor; Mourelle, Luiza

    2017-01-01

    This book discusses a number of real-world applications of computational intelligence approaches. Using various examples, it demonstrates that computational intelligence has become a consolidated methodology for automatically creating new competitive solutions to complex real-world problems. It also presents a concise and efficient synthesis of different systems using computationally intelligent techniques.

  20. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  1. Development of an Intelligent Ultrasonic Signature Classification Software for Discrimination of Flaws in Weldments

    International Nuclear Information System (INIS)

    Kim, H. J.; Song, S. J.; Jeong, H. D.

    1997-01-01

    Ultrasonic pattern recognition is the most effective approach to the problem of discriminating types of flaws in weldments based on ultrasonic flaw signals. In spite of significant progress in the research on this methodology, it has not been widely used in many practical ultrasonic inspections of weldments in industry. Hence, for the convenient application of this approach in many practical situations, we develop an intelligent ultrasonic signature classification software which can discriminate types of flaws in weldments based on their ultrasonic signals using various tools in artificial intelligence such as neural networks. This software shows the excellent performance in an experimental problem where flaws in weldments are classified into two categories of cracks and non-cracks. This performance demonstrates the high possibility of this software as a practical tool for ultrasonic flaw classification in weldments

  2. Development and application of intelligent CAE system for cyclotron main magnet

    International Nuclear Information System (INIS)

    Zhang Tianjue; Chen Yong; Fan Mingwu

    1993-01-01

    The main magnet that represents the feature of the cyclotron is the most important part in a cyclotron construction. Though there are many codes devoted to solve magnetic field computation problems, the results from them are depended on user's skill and experience very much. To help cyclotron magnet designer get acceptable result an intelligent CAE system for cyclotron main magnet design and machining has been developed. A reasonable good results in design could be get even the designer is a beginner with the help from an expert knowledge library installed in the program. The codes include following functions: 1. Intelligent CAD; 2. 2D and 3D magnetic field computation; 3. Beam dynamics analysis; 4. CAM for main magnet

  3. Development of Intelligent Auxiliary System for Customized Physical Fitness and Healthcare

    Directory of Open Access Journals (Sweden)

    Huang Chung-Chi

    2016-01-01

    Full Text Available With the advent of global high-tech industry and commerce era, the sedentary reduces opportunities of physical activity. And physical fitness and health of people is getting worse and worse. At present, the shortage of physical fitness instructors greatly affected the effectiveness of health promotion. Therefore, it is necessary to develop an auxiliary system which can reduce the workload of instructors and enhance physical fitness and health for people. But current general physical fitness and healthcare system is hard to meet individualized needs. The main purpose of this research is to develop an intelligent auxiliary system for customized physical fitness and healthcare. It records all processes of physical fitness and healthcare system by wireless sensors network. The results of intelligent auxiliary systems for customized physical fitness and healthcare will be generated by fuzzy logic Inference. It will improve individualized physical fitness and healthcare. Finally, we will demonstrate the advantages of the intelligent auxiliary system for customized physical fitness and healthcare.

  4. Mathematical Model and Artificial Intelligent Techniques Applied to a Milk Industry through DSM

    Science.gov (United States)

    Babu, P. Ravi; Divya, V. P. Sree

    2011-08-01

    The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. The main objective of this chapter is to discuss about the Peak load management and overcome the problems associated with it in processing industries such as Milk industry with the help of DSM techniques. The chapter presents a generalized mathematical model for minimizing the total operating cost of the industry subject to the constraints. The work presented in this chapter also deals with the results of application of Neural Network, Fuzzy Logic and Demand Side Management (DSM) techniques applied to a medium scale milk industrial consumer in India to achieve the improvement in load factor, reduction in Maximum Demand (MD) and also the consumer gets saving in the energy bill.

  5. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  6. The role of soft computing in intelligent machines.

    Science.gov (United States)

    de Silva, Clarence W

    2003-08-15

    An intelligent machine relies on computational intelligence in generating its intelligent behaviour. This requires a knowledge system in which representation and processing of knowledge are central functions. Approximation is a 'soft' concept, and the capability to approximate for the purposes of comparison, pattern recognition, reasoning, and decision making is a manifestation of intelligence. This paper examines the use of soft computing in intelligent machines. Soft computing is an important branch of computational intelligence, where fuzzy logic, probability theory, neural networks, and genetic algorithms are synergistically used to mimic the reasoning and decision making of a human. This paper explores several important characteristics and capabilities of machines that exhibit intelligent behaviour. Approaches that are useful in the development of an intelligent machine are introduced. The paper presents a general structure for an intelligent machine, giving particular emphasis to its primary components, such as sensors, actuators, controllers, and the communication backbone, and their interaction. The role of soft computing within the overall system is discussed. Common techniques and approaches that will be useful in the development of an intelligent machine are introduced, and the main steps in the development of an intelligent machine for practical use are given. An industrial machine, which employs the concepts of soft computing in its operation, is presented, and one aspect of intelligent tuning, which is incorporated into the machine, is illustrated.

  7. Development of a process model for intelligent control of gas metal arc welding

    International Nuclear Information System (INIS)

    Smartt, H.B.; Johnson, J.A.; Einerson, C.J.; Watkins, A.D.; Carlson, N.M.

    1991-01-01

    This paper discusses work in progress on the development of an intelligent control scheme for arc welding. A set of four sensors is used to detect weld bead cooling rate, droplet transfer mode, weld pool and joint location and configuration, and weld defects during welding. A neural network is being developed as the bridge between the multiple sensor set a conventional proportional-integral controller that provides independent control of process variables. This approach is being developed for the gas metal arc welding process. 20 refs., 8 figs

  8. Attitudes of Special Education Teachers and School Psychologists toward Individualized Education Plan IEPs Developed Using Traditional Assessments versus IEPs Developed Using a Multiple Intelligence Assessment

    Science.gov (United States)

    Alhajri, Meshari A SH A.

    2011-01-01

    The purpose of this research was to determine the usefulness of Multiple Intelligence for educational planning for students in special education. More specifically, this study applied the Multiple Intelligences Developmental Assessment Scales (MIDAS) to a sample of students receiving special education services who had IEPs developed using…

  9. Building the competitive intelligence knowledge: processes and activities in a corporate organisation

    OpenAIRE

    Sreenivasulu, V.

    1999-01-01

    This paper discusses the process of building and developing comprehensive tools, techniques, support systems, and better methods of harnessing the competitive intelligence knowledge processes. The author stresses the need for building sophisticated methodological competitive intelligence knowledge acquisition, systematic collection of competitive intelligence knowledge from various sources for critical analysis, process, organization, synthesis, assessment, screening, filtering and interpreta...

  10. BUSINESS INTELLIGENCE

    OpenAIRE

    Bogdan Mohor Dumitrita

    2011-01-01

    The purpose of this work is to present business intelligence systems. These systems can be extremely complex and important in modern market competition. Its effectiveness also reflects in price, so we have to exlore their financial potential before investment. The systems have 20 years long history and during that time many of such tools have been developed, but they are rarely still in use. Business intelligence system consists of three main areas: Data Warehouse, ETL tools and tools f...

  11. Guiding rules for development of intelligent monitoring system of nuclear power plants

    International Nuclear Information System (INIS)

    Kitamura, M.; Furukawa, H.; Kozma, R.; Washio, T.

    1996-01-01

    General frameworks and major component techniques for intelligent monitoring of nuclear power plants are presented. The key concept, diversity-based design, is to provide advisory information through consensus of multiple agents, each performing operational decision-making by focusing on mutually different information obtained from the plant. The multi-agent design scheme allows to attain high credibility and tolerance against sensor failure in fault detection and causal reasoning. The advantage of the proposed scheme realized by multiple neural networks was clearly demonstrated through numerical experiments with anomalies in a pressurized water reactor. Relevant techniques are also introduced for diagnostic information evaluation in specified symptoms, and for remedial procedure synthesis. A new architecture for future implementation of the proposed scheme, worm-type multi-agent system, is also proposed as a promising candidate. (author)

  12. HClass: Automatic classification tool for health pathologies using artificial intelligence techniques.

    Science.gov (United States)

    Garcia-Chimeno, Yolanda; Garcia-Zapirain, Begonya

    2015-01-01

    The classification of subjects' pathologies enables a rigorousness to be applied to the treatment of certain pathologies, as doctors on occasions play with so many variables that they can end up confusing some illnesses with others. Thanks to Machine Learning techniques applied to a health-record database, it is possible to make using our algorithm. hClass contains a non-linear classification of either a supervised, non-supervised or semi-supervised type. The machine is configured using other techniques such as validation of the set to be classified (cross-validation), reduction in features (PCA) and committees for assessing the various classifiers. The tool is easy to use, and the sample matrix and features that one wishes to classify, the number of iterations and the subjects who are going to be used to train the machine all need to be introduced as inputs. As a result, the success rate is shown either via a classifier or via a committee if one has been formed. A 90% success rate is obtained in the ADABoost classifier and 89.7% in the case of a committee (comprising three classifiers) when PCA is applied. This tool can be expanded to allow the user to totally characterise the classifiers by adjusting them to each classification use.

  13. Security Guidelines for the Development of Accessible Web Applications through the implementation of intelligent systems

    Directory of Open Access Journals (Sweden)

    Luis Joyanes Aguilar

    2009-12-01

    Full Text Available Due to the significant increase in threats, attacks and vulnerabilities that affect the Web in recent years has resulted the development and implementation of pools and methods to ensure security measures in the privacy, confidentiality and data integrity of users and businesses. Under certain circumstances, despite the implementation of these tools do not always get the flow of information which is passed in a secure manner. Many of these security tools and methods cannot be accessed by people who have disabilities or assistive technologies which enable people to access the Web efficiently. Among these security tools that are not accessible are the virtual keyboard, the CAPTCHA and other technologies that help to some extent to ensure safety on the Internet and are used in certain measures to combat malicious code and attacks that have been increased in recent times on the Web. Through the implementation of intelligent systems can detect, recover and receive information on the characteristics and properties of the different tools and hardware devices or software with which the user is accessing a web application and through analysis and interpretation of these intelligent systems can infer and automatically adjust the characteristics necessary to have these tools to be accessible by anyone regardless of disability or navigation context. This paper defines a set of guidelines and specific features that should have the security tools and methods to ensure the Web accessibility through the implementation of intelligent systems.

  14. ANALYSIS AND CONCEPTION DEVELOPMENT OF INFORMATION DEFENSE CID AND CLOUD PLATFORM ON THE BASE OF INTELLIGENCE TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    V. A. Vishniakov

    2014-01-01

    Full Text Available Two problems the use of intelligence technologies in information defense (ITID – creating specialized knowledge bases with threats simulation and high the security level in corporative nets and cloud computing are presented. The analysis of t wo directions of the second ITID problem: the intelligence decision support systems and the malt y-agent system use are given. As trends and conception development of intelligence technologies are the perfection of methods. models, architectures, and hard-sot ware tools for ITID in corporative systems and cloud computing.

  15. Development of SPIES (Space Intelligent Eyeing System) for smart vehicle tracing and tracking

    Science.gov (United States)

    Abdullah, Suzanah; Ariffin Osoman, Muhammad; Guan Liyong, Chua; Zulfadhli Mohd Noor, Mohd; Mohamed, Ikhwan

    2016-06-01

    SPIES or Space-based Intelligent Eyeing System is an intelligent technology which can be utilized for various applications such as gathering spatial information of features on Earth, tracking system for the movement of an object, tracing system to trace the history information, monitoring driving behavior, security and alarm system as an observer in real time and many more. SPIES as will be developed and supplied modularly will encourage the usage based on needs and affordability of users. SPIES are a complete system with camera, GSM, GPS/GNSS and G-Sensor modules with intelligent function and capabilities. Mainly the camera is used to capture pictures and video and sometimes with audio of an event. Its usage is not limited to normal use for nostalgic purpose but can be used as a reference for security and material of evidence when an undesirable event such as crime occurs. When integrated with space based technology of the Global Navigational Satellite System (GNSS), photos and videos can be recorded together with positioning information. A product of the integration of these technologies when integrated with Information, Communication and Technology (ICT) and Geographic Information System (GIS) will produce innovation in the form of information gathering methods in still picture or video with positioning information that can be conveyed in real time via the web to display location on the map hence creating an intelligent eyeing system based on space technology. The importance of providing global positioning information is a challenge but overcome by SPIES even in areas without GNSS signal reception for the purpose of continuous tracking and tracing capability

  16. Computational Intelligence and Decision Making Trends and Applications

    CERN Document Server

    Madureira, Ana; Marques, Viriato

    2013-01-01

    This book provides a general overview and original analysis of new developments and applications in several areas of Computational Intelligence and Information Systems. Computational Intelligence has become an important tool for engineers to develop and analyze novel techniques to solve problems in basic sciences such as physics, chemistry, biology, engineering, environment and social sciences.   The material contained in this book addresses the foundations and applications of Artificial Intelligence and Decision Support Systems, Complex and Biological Inspired Systems, Simulation and Evolution of Real and Artificial Life Forms, Intelligent Models and Control Systems, Knowledge and Learning Technologies, Web Semantics and Ontologies, Intelligent Tutoring Systems, Intelligent Power Systems, Self-Organized and Distributed Systems, Intelligent Manufacturing Systems and Affective Computing. The contributions have all been written by international experts, who provide current views on the topics discussed and pr...

  17. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor

    International Nuclear Information System (INIS)

    Oliveira, Mauro V.; Schirru, Roberto

    2000-01-01

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  18. Designing training programs for the development of emotional intelligence in adolescents with behavioral problems

    Directory of Open Access Journals (Sweden)

    A.V. Degtyarev

    2013-10-01

    Full Text Available In this article, deviant behavior is considered as a combination of different manifestations of personality, leading eventually to its social desaptation. It is shown that an effective method of preventing deviant behavior is psychological training. Group training activity helps to solve the problems associated with the development of various behavioral skills, to provide psychological support, and can be used as a means of psychological work with teenagers with behavioral problems. We discuss the basic points required to effectively create and conduct training programs in general, as well as the challenges and opportunities of designing trainings in order to develop emotional intelligence as a method of prevention of deviant behavior

  19. Ion bombardment techniques - recent developments in SIMS

    International Nuclear Information System (INIS)

    Konarski, P.; Miśnik, M.

    2013-01-01

    We present a short review of cluster ion bombardment technique recently applied in SIMS. Many advantages of using cluster ion beams are specified over monoatomic ion species. Cluster ions open really new perspectives especially in organic based structures analysis. Nevertheless cluster ions are not the perfect solution and still new ideas of ion erosion in SIMS are needed. Another issue discussed is 'storing matter' technique applied for quantitative analysis in SIMS. Simple idea of sputter deposition of eroded material onto rotating substrate and then analysing the stored material allows to avoid strong matrix effects in SIMS. Presented are the results performed in Tele and Radio Research Institute, Warszawa, Poland. These are the first results of ‘storing matter’ technique performed in one analytical chamber of SIMS instrument. (authors)

  20. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Directory of Open Access Journals (Sweden)

    Min-Chao He

    2012-06-01

    Full Text Available Two artificial intelligence techniques, namely artificial neural network (ANN and genetic algorithm (GA were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl carbodiimide (EDC concentration, N-hydroxysuccinimide (NHS concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99. Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

  1. Big data for development : applications and techniques

    NARCIS (Netherlands)

    Ali, Anwaar; Qadir, Junaid; ur Rasool, Raihan; Sathiaseelan, Arjuna; Zwitter, Andrej; Crowcroft, Jon

    2016-01-01

    With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data is being generated on a daily basis. Efficient techniques/algorithms to analyze this massive amount of data can provide near real-time information about

  2. The IGISOL technique : three decades of developments

    NARCIS (Netherlands)

    Moore, I.D.; Dendooven, Peter; Ärje, J.

    The Ion Guide Isotope SeparatorOn-Line (IGISOL) technique, conceived in the early 1980s as a novel variation to the helium-jet method, has been used to provide radioactive ion beams of short-lived exotic nuclei for fundamental nuclear structure research and applications for three decades. This

  3. Prediction of Marshall Parameters of Modified Bituminous Mixtures Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Sunil Khuntia

    2014-09-01

    Full Text Available This study presents the application of artificial neural networks (ANN and least square support vector machine (LS-SVM for prediction of Marshall parameters obtained from Marshall tests for waste polyethylene (PE modified bituminous mixtures. Waste polyethylene in the form of fibres processed from utilized milk packets has been used to modify the bituminous mixes in order to improve their engineering properties. Marshall tests were carried out on mix specimens with variations in polyethylene and bitumen contents. It has been observed that the addition of waste polyethylene results in the improvement of Marshall characteristics such as stability, flow value and air voids, used to evaluate a bituminous mix. The proposed neural network (NN model uses the quantities of ingredients used for preparation of Marshall specimens such as polyethylene, bitumen and aggregate in order to predict the Marshall stability, flow value and air voids obtained from the tests. Out of two techniques used, the NN based model is found to be compact, reliable and predictable when compared with LS-SVM model. A sensitivity analysis has been performed to identify the importance of the parameters considered.

  4. Individual Differences in Moral Development: Does Intelligence Really Affect Children?s Moral Reasoning and Moral Emotions?

    OpenAIRE

    Bei?ert, Hanna M.; Hasselhorn, Marcus

    2016-01-01

    This study investigates the relationship between intelligence and individual differences in children’s moral development across a range of different moral transgressions. Taking up prior research that showed morality and intelligence to be related in adolescents and adults, the current study wants to test if these findings can be extended to younger children. The study was designed to address some of the shortcomings in prior research by examining young children aged between 6 years; 4 months...

  5. Development of the decommissioning techniques for nuclear fuel cycle facilities

    International Nuclear Information System (INIS)

    Tanimoto, Ken-ichi; Sugaya, Toshikatsu; Hara, Mitsuo; Kikuchi, Yutaka; Tobita, Hiroo; Enokido, Yuji

    1992-01-01

    Being developed the basement techniques such as measurement, decontamination, dismantling, remote handling and data base. For the elevating and systematizing the basement techniques, thinking over the application, forward to the facility decommissionings in the future, including the technique of waste treatment in WDF and the achievement using the dismantling and recycling technique in renewaling the research facilities. (author)

  6. An approach to modeling operator's cognitive behavior using artificial intelligence techniques in emergency operating event sequences

    International Nuclear Information System (INIS)

    Cheon, Se Woo; Sur, Sang Moon; Lee, Yong Hee; Park, Young Taeck; Moon, Sang Joon

    1994-01-01

    Computer modeling of an operator's cognitive behavior is a promising approach for the purpose of human factors study and man-machine systems assessment. In this paper, the states of the art in modeling operator behavior and the current status in developing an operator's model (MINERVA - NPP) are presented. The model is constructed as a knowledge-based system of a blackboard framework and is simulated based on emergency operating procedures

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

    Science.gov (United States)

    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…

  8. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  9. Advanced interfacing techniques for sensors measurement circuits and systems for intelligent sensors

    CERN Document Server

    Roy, Joyanta; Kumar, V; Mukhopadhyay, Subhas

    2017-01-01

    This book presents ways of interfacing sensors to the digital world, and discusses the marriage between sensor systems and the IoT: the opportunities and challenges. As sensor output is often affected by noise and interference, the book presents effective schemes for recovering the data from a signal that is buried in noise. It also explores interesting applications in the area of health care, un-obstructive monitoring and the electronic nose and tongue. It is a valuable resource for engineers and scientists in the area of sensors and interfacing wanting to update their knowledge of the latest developments in the field and learn more about sensing applications and challenges.

  10. Modeling of biodistribution of 90 Y-DOTA-hR3 by using artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ondarse, Dianelys; Quiza, Ramon; Leyva, Rene; Zamora, Minely; Ducat, Luis; Hernandez, Ignacio; Alonso, Luis Michel

    2011-01-01

    In this work the biodistribution of radioimmunoconjugate 9 0Y-DOTA-hR3 was modeled by using an artificial neural network. In vivo stability of 9 0Y-DOTA-hR3 was determined in healthy male Wistar rats at 4, 24 and 48 hours, in different organs. A model describing the relationship between, by one hand, the incorporated dose and, by the other hand, organ and time was developed by using a multilayer perceptron neural network. Adjusted model was analyzed by several statistical tests. Outcomes shown that proposed neural model describes the relationship between the studied variables in a proper way. (Author)

  11. Artificial Intelligence: Applications in Education.

    Science.gov (United States)

    Thorkildsen, Ron J.; And Others

    1986-01-01

    Artificial intelligence techniques are used in computer programs to search out rapidly and retrieve information from very large databases. Programing advances have also led to the development of systems that provide expert consultation (expert systems). These systems, as applied to education, are the primary emphasis of this article. (LMO)

  12. Research and applications: Artificial intelligence

    Science.gov (United States)

    Chaitin, L. J.; Duda, R. O.; Johanson, P. A.; Raphael, B.; Rosen, C. A.; Yates, R. A.

    1970-01-01

    The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness.

  13. Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Ozer, Ozgen; Güneri, Tamer; York, Peter

    2012-12-01

    The publication of the International Conference of Harmonization (ICH) Q8, Q9, and Q10 guidelines paved the way for the standardization of quality after the Food and Drug Administration issued current Good Manufacturing Practices guidelines in 2003. "Quality by Design", mentioned in the ICH Q8 guideline, offers a better scientific understanding of critical process and product qualities using knowledge obtained during the life cycle of a product. In this scope, the "knowledge space" is a summary of all process knowledge obtained during product development, and the "design space" is the area in which a product can be manufactured within acceptable limits. To create the spaces, artificial neural networks (ANNs) can be used to emphasize the multidimensional interactions of input variables and to closely bind these variables to a design space. This helps guide the experimental design process to include interactions among the input variables, along with modeling and optimization of pharmaceutical formulations. The objective of this study was to develop an integrated multivariate approach to obtain a quality product based on an understanding of the cause-effect relationships between formulation ingredients and product properties with ANNs and genetic programming on the ramipril tablets prepared by the direct compression method. In this study, the data are generated through the systematic application of the design of experiments (DoE) principles and optimization studies using artificial neural networks and neurofuzzy logic programs.

  14. Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

    Science.gov (United States)

    Citakoglu, Hatice

    2017-10-01

    Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient ( R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

  15. Intelligent Processing Equipment Developments Within the Navy's Manufacturing Technology Centers of Excellence

    Science.gov (United States)

    Nanzetta, Philip

    1992-01-01

    The U.S. Navy has had an active Manufacturing Technology (MANTECH) Program aimed at developing advanced production processes and equipment since the late-1960's. During the past decade, however, the resources of the MANTECH program were concentrated in Centers of Excellence. Today, the Navy sponsors four manufacturing technology Centers of Excellence: the Automated Manufacturing Research Facility (AMRF); the Electronics Manufacturing Productivity Facility (EMPF); the National Center for Excellence in Metalworking Technology (NCEMT); and the Center of Excellence for Composites Manufacturing Technology (CECMT). This paper briefly describes each of the centers and summarizes typical Intelligent Equipment Processing (IEP) projects that were undertaken.

  16. Applications of artificial intelligence to space station and automated software techniques: High level robot command language

    Science.gov (United States)

    Mckee, James W.

    1989-01-01

    The objective is to develop a system that will allow a person not necessarily skilled in the art of programming robots to quickly and naturally create the necessary data and commands to enable a robot to perform a desired task. The system will use a menu driven graphical user interface. This interface will allow the user to input data to select objects to be moved. There will be an imbedded expert system to process the knowledge about objects and the robot to determine how they are to be moved. There will be automatic path planning to avoid obstacles in the work space and to create a near optimum path. The system will contain the software to generate the required robot instructions.

  17. Developing remote techniques for liquid metal reactors

    International Nuclear Information System (INIS)

    Fenemore, Peter

    1987-01-01

    Three devices have been designed in Britain to meet the need for special remote equipment and techniques required to inspect the reactor vessel and internals of liquid metal reactors. The ''Links Manipulator Under-Sodium Viewing System'' - a device to be used for the surveillance of reactor internals, which are submerged in sodium. An ''Automatic Guided Vehicle'' - a free roving vehicle to be used to survey the externals of the reactor vessel. The ''Snake Manipulator'' - an articulated arm used to gain access to restricted areas. (author)

  18. Recent developments in magnet measuring techniques

    International Nuclear Information System (INIS)

    Billan, J.; Henrichsen, K.N.; Walckiers, L.

    1985-01-01

    The main problems related to magnetic measurements of particle accelerator components are discussed. Measurements of the properties of magnetic materials as well as the measurements of field distribution in the electromagnets for the Large Electron-Positron Collider (LEP) are illustrated. The fluxmeter method is extensively employed in this work. The impact of recent advances in electronic technology on measurement techniques is explained. Magnetic measurements (including the harmonic coil method) can be performed with improved accuracy applying modern technology to the classical methods. New methods for the non-destructive testing of magnetic materials and for the measurement of magnetic geometry are described. (orig.) [de

  19. A general-purpose development environment for intelligent computer-aided training systems

    Science.gov (United States)

    Savely, Robert T.

    1990-01-01

    Space station training will be a major task, requiring the creation of large numbers of simulation-based training systems for crew, flight controllers, and ground-based support personnel. Given the long duration of space station missions and the large number of activities supported by the space station, the extension of space shuttle training methods to space station training may prove to be impractical. The application of artificial intelligence technology to simulation training can provide the ability to deliver individualized training to large numbers of personnel in a distributed workstation environment. The principal objective of this project is the creation of a software development environment which can be used to build intelligent training systems for procedural tasks associated with the operation of the space station. Current NASA Johnson Space Center projects and joint projects with other NASA operational centers will result in specific training systems for existing space shuttle crew, ground support personnel, and flight controller tasks. Concurrently with the creation of these systems, a general-purpose development environment for intelligent computer-aided training systems will be built. Such an environment would permit the rapid production, delivery, and evolution of training systems for space station crew, flight controllers, and other support personnel. The widespread use of such systems will serve to preserve task and training expertise, support the training of many personnel in a distributed manner, and ensure the uniformity and verifiability of training experiences. As a result, significant reductions in training costs can be realized while safety and the probability of mission success can be enhanced.

  20. Development of an intertidal mangrove nursery and afforestation techniques

    Digital Repository Service at National Institute of Oceanography (India)

    Untawale, A.G.

    The development of an intertidal mangrove nursery and afforestation technique for regeneration and restoration of mangroves of Goa is described. Site selection, source of plant material, nursery plantation, season of transplantation, technique...

  1. [The impact of malnutrition on brain development, intelligence and school work performance].

    Science.gov (United States)

    Leiva Plaza, B; Inzunza Brito, N; Pérez Torrejón, H; Castro Gloor, V; Jansana Medina, J M; Toro Díaz, T; Almagiá Flores, A; Navarro Díaz, A; Urrutia Cáceres, M S; Cervilla Oltremari, J; Ivanovic Marincovich, D

    2001-03-01

    The findings from several authors confirm that undernutrition at an early age affects brain growth and intellectual quotient. Most part of students with the lowest scholastic achievement scores present suboptimal head circumference (anthropometric indicator of past nutrition and brain development) and brain size. On the other hand, intellectual quotient measured through intelligence tests (Weschler-R, or the Raven Progressives Matrices Test) has been described positively and significantly correlated with brain size measured by magnetic resonance imaging (MRI); in this respect, intellectual ability has been recognized as one of the best predictors of scholastic achievement. Considering that education is the change lever for the improvement of the quality of life and that the absolute numbers of undernourished children have been increasing in the world, is of major relevance to analyse the long-term effects of undernutrition at an early age. The investigations related to the interrelationships between nutritional status, brain development, intelligence and scholastic achievement are of greatest importance, since nutritional problems affect the lowest socioeconomic stratum with negative consequences manifested in school-age, in higher levels of school dropout, learning problems and a low percentage of students enrolling into higher education. This limits the development of people by which a clear economic benefit to increase adult productivity for government policies might be successful preventing childhood malnutrition.

  2. Development of radiation preservation technique in Beijing

    International Nuclear Information System (INIS)

    Zhang Hongdi; Li Guixiang; Pang Mei

    1990-12-01

    The 60 Co radiation preservation technique which was used to preserve persimmons, green peppers and four varieties of apple was studied. Apples and persimmons were irradiated with 0.1 ∼ 0.7kGy and 0.1 ∼ 1.0kGy respectively, then they were stored under a constant environmental temperature. Green peppers were treated with heat, irradiated with low dose and stored at low temperature. After a certain time of storing, the results showed that the quality of irradiated groups was better than control group, and there was no difference of main nutrient components between the irradiated groups and the control group. Finally, the radiation processing does not cause radioactivity increasing and microelements decreasing in the food

  3. Development of PSI and ISI technique

    International Nuclear Information System (INIS)

    Chung, M.K.; Park, D.Y.; Choi, S.P.; Kim, H.J.; Moon, Y.S.; Shon, G.H.; Kim, T.S.

    1983-01-01

    This report describes the experimental results of the subjects selected from the PSI/ISI related problems which encountered by us in 1982. The main contents are 1) the characteristics of the typical ECT signals from the steam generator tubes of nuclear power plant and the results of ECT evaluation of Kori-1 steam generators, 2) the experimental result for the research for directional effects of ultrasonic transducers, 3) the basic experiment for the ultrasonic testing technique by immersion testing method, 4) how to write the scan plan of the mechanized ultrasonic testing for nuclear reactor. Attached appendix is a part of necessary materials for the scan plan of the mechanized ultrasonic testing for Kori-2 nuclear reactor. (Author)

  4. Development of material balance evaluation technique(2)

    International Nuclear Information System (INIS)

    Lee, Byung Doo

    2000-06-01

    IAEA considers that the evaluation on material balance is one of the important activities for detecting the diversion of nuclear materials as well as measurement uncertainties and measurement bias. Nuclear material accounting reports, the results of DA and NDA, the summarized lists of material stratified by inspector are necessary for the material balance evaluation. In this report, the concepts and evaluation methods of material balance evaluation such as the estimation techniques of random and systematic errors, MUF, D and MUF-D are described. As a conclusion, it is possible for national inspection to evaluate the material balance by applying the evaluation methods of the IAEA such as error estimation using operator-inspector paired data, inspector MUF(IMUF) evaluation

  5. Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

    Directory of Open Access Journals (Sweden)

    Cenk Demirkır

    2014-04-01

    Full Text Available Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bonding strength of plywood panels. This study has composed of two main parts as experimental and analytical. Scots pine, maritime pine and European black pine logs were used as wood species. The pine veneers peeled at 32°C and 50°C were dried at 110°C, 140°C and 160°C temperatures. Phenol formaldehyde and melamine urea formaldehyde resins were used as adhesive types. EN 314-1 standard was used to determine the bonding shear strength values of plywood panels in experimental part of this study. Then the intuitive k-nearest neighbor estimator (IKE and adaptive artificial neural network (AANN were used to estimate bonding strength of plywood panels. The best estimation performance was obtained from MA metric for k-value=10. The most effective factor on bonding strength was determined as adhesive type. Error rates were determined less than 5% for both of the IKE and AANN. It may be recommended that proposed methods could be used in applying to estimation of bonding strength values of plywood panels.

  6. Design and development of an intelligent nursing bed - a pilot project of "joint assignment".

    Science.gov (United States)

    Jiehui Jiang; Tingwei Liu; Yuting Zhang; Yu Song; Mi Zhou; Xiaosong Zheng; Zhuangzhi Yan

    2017-07-01

    The "joint assignment" is a creative bachelor education project for Biomedical Engineering (BME) in Shanghai University (SHU), China. The objective of this project is to improve students' capabilities in design thinking and teamwork through practices in the process of the design and development of complex medical product. As the first step, a pilot project "design and development of intelligent nursing bed" was set up in May 2015. This paper describes details of how project organization and management, various teaching methods and scientific evaluation approaches were achieved in this pilot project. For example, a method containing one main line and four branches is taken to manage the project and "prototyping model" was used as the main research approach. As a result a multi-win situation was achieved. The results showed, firstly, 62 bachelor students including 16 BME students were well trained. They improved themselves in use of practical tools, communication skills and scientific writing; Secondly, commercial companies received a nice product design on intelligent nursing bed, and have been working on industrializing it; Thirdly, the university and associated schools obtained an excellent practical education experience to supplement traditional class education; Fourthly and most importantly, requirements from end-users will be met. The results also showed that the "joint assignment" task could become a significant component in BME bachelor education.

  7. The Relationship between a Business Simulator, Constructivist Practices, and Motivation toward Developing Business Intelligence Skills

    Directory of Open Access Journals (Sweden)

    Ju Long

    2016-11-01

    Full Text Available Developing Business Intelligence (BI has been a top priority for enterprise executives in recent years. To meet these demands, universities need to prepare students to work with BI in enterprise settings. In this study, we considered a business simulator that offers students opportunities to apply BI and make top-management decisions in a system used by real-world professionals. The simulation-based instruction can be effective only if students are not discouraged by the difficulty of using the BI computer system and comprehending the complex BI subjects. Constructivist practices embedded in the business simulation are investigated to understand their potentials for helping the students to overcome the perceived difficulty. Consequently, it would enable instructors to more efficiently use the simulator by providing insights on its pedagogical practices. Our findings showed that the constructivist practices such as collaboration and subject integration positively influence active learning and meaningful learning respectively. In turn, both active learning and meaningful learning positively influence business intelligence motivational behavior. These findings can be further used to develop a robust learning environment in BI classes.

  8. Development and Psychometric Properties of the Emotional Intelligence Admission Essay Scale

    Directory of Open Access Journals (Sweden)

    Sharon A. Gutman

    2016-07-01

    Full Text Available The purpose was to describe the development and psychometric properties of the Emotional Intelligence Admission Essay scale. The authors developed an admission essay question and rating scale designed to provide information about applicants’ emotional intelligence (EI. Content validity, convergent validity, interrater reliability, and internal consistency were established. The scale was also examined to determine if it could discriminate between students with and without professional behavior problems in the academic and fieldwork settings. Content validity was found to be high by a panel of three experts in EI (content validity index = 1.0. Convergent validity with the Assessing Emotions Scale was moderate (r = .46, p < .02. Interrater reliability between two trained faculty raters was high (ICC = .91, p < .000. Internal consistency of the scale was high with a Cronbach’s alpha of .95. This version of the scale was not able to discriminate between students with and without professional behavior problems. The moderate to strong psychometric properties suggest that the EI Admission Essay Scale has the ability to provide information about applicants’ EI. The wording of the essay question must be modified to better instruct applicants to address interpersonal conflict.

  9. Design of information-measuring and control systems for intelligent buildings. Trends of development

    Directory of Open Access Journals (Sweden)

    Petrova Irina Yur’evna

    2015-12-01

    Full Text Available The article considers the modern requirements for integrated management systems of a smart home. The authors propose a hierarchical classification of the levels of house automation, which allows allocating different levels of information transfer. The article considers the trends of development of information-measuring and control systems of intelligent buildings. The generalized scheme of information-measuring and control subsystems of an intelligent building are given. The energy-information model of the knowledge base of physical and technical effects described in the article allows developing a system of automated support of the conceptual stage of elements design in information measuring and control systems. With the help of this knowledge base the system allows dozens of times expanding the scope of knowledge actively used by specialists and two or three times reducing the time of creating new solutions by selecting the most efficient of the options and the underlying calculation of the essential characteristics of their conceptual models, which significantly reduces the number of created prototypes and field tests.

  10. An Intelligent System for Aggression De-escalation Training

    NARCIS (Netherlands)

    Bosse, T.; Gerritsen, C.; de Man, J.

    2016-01-01

    Artificial Intelligence techniques are increasingly being used to develop smart training applications for professionals in various domains. This paper presents an intelligent training system that enables professionals in the public domain to practice their aggression de-escalation skills. The system

  11. The Synthesis of Intelligent Real-Time Systems

    Science.gov (United States)

    1990-11-09

    Synthesis of Intelligent Real - Time Systems . The purpose of the effort was to develop and extend theories and techniques that facilitate the design and...implementation of intelligent real - time systems . In particular, Teleos has extended situated-automata theory to apply to situations in which the system has

  12. An artificial-intelligence technique for qualitatively deriving enzyme kinetic mechanisms from initial-velocity measurements and its application to hexokinase.

    Science.gov (United States)

    Garfinkel, L; Cohen, D M; Soo, V W; Garfinkel, D; Kulikowski, C A

    1989-01-01

    We have developed a computer method based on artificial-intelligence techniques for qualitatively analysing steady-state initial-velocity enzyme kinetic data. We have applied our system to experiments on hexokinase from a variety of sources: yeast, ascites and muscle. Our system accepts qualitative stylized descriptions of experimental data, infers constraints from the observed data behaviour and then compares the experimentally inferred constraints with corresponding theoretical model-based constraints. It is desirable to have large data sets which include the results of a variety of experiments. Human intervention is needed to interpret non-kinetic information, differences in conditions, etc. Different strategies were used by the several experimenters whose data was studied to formulate mechanisms for their enzyme preparations, including different methods (product inhibitors or alternate substrates), different experimental protocols (monitoring enzyme activity differently), or different experimental conditions (temperature, pH or ionic strength). The different ordered and rapid-equilibrium mechanisms proposed by these experimenters were generally consistent with their data. On comparing the constraints derived from the several experimental data sets, they are found to be in much less disagreement than the mechanisms published, and some of the disagreement can be ascribed to different experimental conditions (especially ionic strength). PMID:2690819

  13. Development of Radiation Technique for Environmental Treatment

    International Nuclear Information System (INIS)

    Lee, Myun Joo; Kuk, Il Hiun; Jin, Joon Ha

    2007-02-01

    The purpose of this research is to development of technologies for 1) the removal of toxic organic chemicals in sewage sludges and the volume reduction of the sewage sludge 2) the recycling/reuse of sewage sludge 3) the reconvey of resource from fishery waste by using radiation technologies. This research project focused on the study of treatment, disposal, and recycling/reuse of sewage sludge by radiation technology, and recovery of highly value-added resources from the wastes. As basic studies with a radiation technology, an enhancement of dewaterbilities of sewage sludge, development of dewatering conditioner, reduction of trace toxic organic chemicals, and the toxicities of the byproducts were studied. Based on the basic experimental results, we developed the pilot-scale system with the continuous e-beam and dewatering unit and the advanced treatment system with the use of carbon source recovered from sewage sludge

  14. Development of Radiation Technique for Environmental Treatment

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Myun Joo; Kuk, Il Hiun; Jin, Joon Ha [and others

    2007-02-15

    The purpose of this research is to development of technologies for 1) the removal of toxic organic chemicals in sewage sludges and the volume reduction of the sewage sludge 2) the recycling/reuse of sewage sludge 3) the reconvey of resource from fishery waste by using radiation technologies. This research project focused on the study of treatment, disposal, and recycling/reuse of sewage sludge by radiation technology, and recovery of highly value-added resources from the wastes. As basic studies with a radiation technology, an enhancement of dewaterbilities of sewage sludge, development of dewatering conditioner, reduction of trace toxic organic chemicals, and the toxicities of the byproducts were studied. Based on the basic experimental results, we developed the pilot-scale system with the continuous e-beam and dewatering unit and the advanced treatment system with the use of carbon source recovered from sewage sludge.

  15. Professional tears: developing emotional intelligence around death and dying in emergency work.

    Science.gov (United States)

    Bailey, Cara; Murphy, Roger; Porock, Davina

    2011-12-01

    This paper explores how emergency nurses manage the emotional impact of death and dying in emergency work and presents a model for developing expertise in end-of-life care delivery. Care of the dying, the deceased and the bereaved is largely conducted by nurses and nowhere is this more demanding than at the front door of the hospital, the Emergency Department. Whilst some nurses find end-of-life care a rewarding aspect of their role, others avoid opportunities to develop a relationship with the dying and bereaved because of the intense and exhausting nature of the associated emotional labour. Qualitative study using unstructured observations of practice and semistructured interviews. Observation was conducted in a large Emergency Department over 12 months. We also conducted 28 in-depth interviews with emergency staff, patients with terminal illnesses and their relatives. Emergency nurses develop expertise in end-of-life care giving by progressing through three stages of development: (1) investment of the self in the nurse-patient relationship, (2) management of emotional labour and (3) development of emotional intelligence. Barriers that prevent the transition to expertise contribute to occupational stress and can lead to burnout and withdrawal from practice. Despite the emotional impact of emergency deaths, nurses who invest their therapeutic self into the nurse-patient relationship are able to manage the emotional labour of caring for the dying and their relatives through the development of emotional intelligence. They find reward in end-of-life care that ultimately creates a more positive experience for patients and their relatives. The emergency nurse caring for the dying patient is placed in a unique and privileged position to make a considerable impact on the care of the patient and the experience for their family. This model can build awareness in managing the emotive aspects involved in care delivery and develop fundamental skills of nursing patients near

  16. The potential of folk tabletop games in the development of the intelligence and creativity of children

    Directory of Open Access Journals (Sweden)

    Mariia Baisheva

    2017-11-01

    Full Text Available The modern education is dominantly targeted at the left hemisphere. It draws insufficient attention to the harmonization of the functioning of both brain hemispheres. This has a negative impact on the development of the abilities of children and is especially detrimental to boys and those children who are brought up in the natural environment. In this regard, one of the solutions is folk tabletop games, but their potential in the development of the intelligence and creativity of children has been insufficiently explored. The goal of the research is to identify and substantiate the potential of the Sakha’s tabletop games for the development of the intellectual and creative abilities of children aged 5-7 years. The scientific novelty of the research consists in the fact that the problem under study enriches the theoretical and methodological bases of using tabletop games in the intellectual development of children in preschool education. The study was carried out longitudinally. The following was studied: the influence of games on the development of intellectual, creative, and insight abilities of children aged 5-7 years, as well as their interconditionality. The obtained results are discussed from the point of view of their correspondence with both the data available in science and the hypothesis of the study. The discussion emphasizes that the tabletop games of the Sakha are the most meaningfully represented in the study as the functional space for the development of intellectual and creative abilities of children. In the conclusion, it is emphasized that folk tabletop games are the means for qualitative enrichment of all the basic factors of intelligence in operations, contents, and final products of thinking. The study has proven the idea of treating tabletop games as a substantial source of development of the harmonious activity of both brain hemispheres.

  17. Development of automatic radiographic inspection system using digital image processing and artificial intelligence

    International Nuclear Information System (INIS)

    Itoga, Kouyu; Sugimoto, Koji; Michiba, Koji; Kato, Yuhei; Sugita, Yuji; Onda, Katsuhiro.

    1991-01-01

    The application of computers to welding inspection is expanding rapidly. The classification of the application is the collection, analysis and processing of data, the graphic display of results, the distinction of the kinds of defects and the evaluation of the harmufulness of defects and the judgement of acceptance or rejection. The application of computer techniques to the automation of data collection was realized at the relatively early stage. Data processing and the graphic display of results are the techniques in progress now, and the application of artificial intelligence to the distinction of the kinds of defects and the evaluation of harmfulness is expected to expand rapidly. In order to computerize radiographic inspection, the abilities of image processing technology and knowledge engineering must be given to computers. The object of this system is the butt joints by arc welding of the steel materials of up to 30 mm thickness. The digitizing transformation of radiographs, the distinction and evaluation of transmissivity and gradation by image processing, and only as for those, of which the picture quality satisfies the standard, the extraction of defect images, their display, the distinction of the kinds and the final judgement are carried out. The techniques of image processing, the knowledge for distinguishing the kinds of defects and the concept of the practical system are reported. (K.I.)

  18. Development of lidar techniques for environmental studies

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Mats

    1996-09-01

    The lidar group in Lund has performed many DIAL measurements with a mobile lidar system that was first described in 1987. The lidar system is based on a Nd:YAG-pumped dye laser. During the last few years the lidar group has focused on fluorescence imaging and mercury measurements in the troposphere. In 1994 we performed two campaigns: one fluorescence imaging measurement campaign outside Avignon, France and one unique lidar campaign at a mercury mine in Almaden, Spain. Both campaigns are described in this thesis. This thesis also describes how the mobile lidar system was updated with the graphical programming language LabVIEW to obtain a user friendly lidar system. The software controls the lidar system and analyses measured data. The measurement results are shown as maps of species concentration. All electronics and the major parts of the program are described. A new graphical technique to estimate wind speed from plumes is also discussed. First measurements have been performed with the new system. 31 refs, 19 figs, 1 tab

  19. Development of an intelligent hydroinformatic system for real-time monitoring and assessment of civil infrastructure

    Science.gov (United States)

    Cahill, Paul; Michalis, Panagiotis; Solman, Hrvoje; Kerin, Igor; Bekic, Damir; Pakrashi, Vikram; McKeogh, Eamon

    2017-04-01

    With the effects of climate change becoming more apparent, extreme weather events are now occurring with greater frequency throughout the world. Such extreme events have resulted in increased high intensity flood events which are having devastating consequences on hydro-structures, especially on bridge infrastructure. The remote and often inaccessible nature of such bridges makes inspections problematic, a major concern if safety assessments are required during and after extreme flood events. A solution to this is the introduction of smart, low cost sensing solutions at locations susceptible to hydro-hazards. Such solutions can provide real-time information on the health of the bridge and its environments, with such information aiding in the mitigation of the risks associated with extreme weather events. This study presents the development of an intelligent system for remote, real-time monitoring of hydro-hazards to bridge infrastructure. The solution consists of two types of remote monitoring stations which have the capacity to monitor environmental conditions and provide real-time information to a centralized, big data database solution, from which an intelligent decision support system will accommodate the results to control and manage bridge, river and catchment assets. The first device developed as part of the system is the Weather Information Logging Device (WILD), which monitors rainfall, temperature and air and soil moisture content. The ability of the WILD to monitor rainfall in real time enables flood early warning alerts and predictive river flow conditions, thereby enabling decision makers the ability to make timely and effective decisions about critical infrastructures in advance of extreme flood events. The WILD is complemented by a second monitoring device, the Bridge Information Recording Device (BIRD), which monitors water levels at a given location in real-time. The monitoring of water levels of a river allows for, among other applications

  20. Gestalt Therapy: Development, Theory, and Techniques.

    Science.gov (United States)

    Witchel, Robert

    This paper presents a full review of the literature in the area of Gestalt Therapy and could be helpful in familiarizing people with this discipline. The roots contributing to the development of Gestalt therapy as presently practiced are explored briefly. Gestalt theory is presented in a developmental way, initially exploring the relationship…